WorldWideScience

Sample records for nonlinear image restoration

  1. Constrained optimization for image restoration using nonlinear programming

    Science.gov (United States)

    Yeh, C.-L.; Chin, R. T.

    1985-01-01

    The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.

  2. IMAGE RESTORATION: DESIGN OF NON-LINEAR FILTER (LR

    Directory of Open Access Journals (Sweden)

    Shenbagarajan Anantharajan

    2012-11-01

    Full Text Available In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.

  3. Rigorous mathematical investigation of a nonlinear anisotropic diffusion-based image restoration model

    Directory of Open Access Journals (Sweden)

    Tudor Barbu

    2014-06-01

    Full Text Available A nonlinear diffusion based image denoising technique is introduced in this paper. The proposed PDE denoising and restoration scheme is based on a novel diffusivity function that uses an automatically detected conductance parameter. A robust mathematical treatment is also provided for our anisotropic diffusion model. We demonstrate that edge-stopping function model is properly chosen, explaining the mathematical reasons behind it. Also, we perform a rigorous mathematical investigation on of the existence and uniqueness of the solution of our nonlinear diffusion equation. This PDE-based noise removal approach outperforms most diffusion-based methods, producing considerably better smoothing results and providing a much better edge preservation.

  4. Iterative restoration algorithms for nonlinear constraint computing

    Science.gov (United States)

    Szu, Harold

    A general iterative-restoration principle is introduced to facilitate the implementation of nonlinear optical processors. The von Neumann convergence theorem is generalized to include nonorthogonal subspaces which can be reduced to a special orthogonal projection operator by applying an orthogonality condition. This principle is shown to permit derivation of the Jacobi algorithm, the recursive principle, the van Cittert (1931) deconvolution method, the iteration schemes of Gerchberg (1974) and Papoulis (1975), and iteration schemes using two Fourier conjugate domains (e.g., Fienup, 1981). Applications to restoring the image of a double star and division by hard and soft zeros are discussed, and sample results are presented graphically.

  5. FFT-Based Methods for Nonlinear Image Restoration in Confocal Microscopy

    NARCIS (Netherlands)

    Roerdink, J.B.T.M.

    1994-01-01

    Recently we developed a new method for attenuation correction in 3D imaging by a confocal scanning laser microscope (CSLM) in the (epi)fluorescence mode. The fundamental element in our approach consisted of multiplying the measured fluorescent intensity by a correction factor involving a convolution

  6. Image restoration scale space

    Science.gov (United States)

    Alvarez, Luis; Mazorra, L.; Santana, F.

    1995-09-01

    We present a study of some image resoration techniques based on partial differential equations. We study separately the denoising problem and the restoration of discontinuities. We analyze the capabilities of the differential operators to restore images. In particular, we analyze a number of models present in the literature, and we present comparative results. Finally, we present a model based in the combination of the anisotropic diffusion of Alvarez, Lions, and Morel and the shock filters of Osher and Rudin.

  7. Adaptive wiener image restoration kernel

    Science.gov (United States)

    Yuan, Ding

    2007-06-05

    A method and device for restoration of electro-optical image data using an adaptive Wiener filter begins with constructing imaging system Optical Transfer Function, and the Fourier Transformations of the noise and the image. A spatial representation of the imaged object is restored by spatial convolution of the image using a Wiener restoration kernel.

  8. Restoration of nonlinear motion-distorted composite frame

    Science.gov (United States)

    Yitzhaky, Yitzhak; Stern, Adrian; Kopeika, Norman S.

    2000-12-01

    A composite frame image is an interlaced composition of two sub-image odd and even fields. Such image type is common in many imaging systems that produce video sequences. When relative motion between the camera and the scene occurs during the imaging process, two types of distortion degrade the image: the edge 'staircase effect' due to the shifted appearances of the objects in successive fields, and blur due to the scene motion during each field exposure. This paper deals with restoration of composite frame images degraded by motion. In contrast to other previous works that dealt with only uniform velocity motion, here we consider a more general case of nonlinear motion. Since conventional motion identification techniques used in other works can not be employed in the case of nonlinear motion, a new method for identification of the motion from each field is used. Results of motion identification and image restoration for various motion types are presented.

  9. Image Restoration And Resolution Enhancement

    Science.gov (United States)

    Byrne, Charles L.; Fitzgerald, Raymond M.

    1983-09-01

    We consider mathematical algorithms for the restoration of object information from finitely many measurements of the object's spectrum, with particular emphasis on the development of linear and nonlinear non-iterative methods that can incorporate prior information about object extent and shape. The linear method presented here generalizes the minimum energy bandlimited extrapolation procedure, which is the closed form limit of Gerchberg-Papoulis iteration in this case. The nonlinear method generalizes the maximum entropy method (MEM) of Burg.

  10. Nonlinear phased array imaging

    Science.gov (United States)

    Croxford, Anthony J.; Cheng, Jingwei; Potter, Jack N.

    2016-04-01

    A technique is presented for imaging acoustic nonlinearity within a specimen using ultrasonic phased arrays. Acoustic nonlinearity is measured by evaluating the difference in energy of the transmission bandwidth within the diffuse field produced through different focusing modes. The two different modes being classical beam forming, where delays are applied to different element of a phased array to physically focus the energy at a single location (parallel firing) and focusing in post processing, whereby one element at a time is fired and a focused image produced in post processing (sequential firing). Although these two approaches are linearly equivalent the difference in physical displacement within the specimen leads to differences in nonlinear effects. These differences are localized to the areas where the amplitude is different, essentially confining the differences to the focal point. Direct measurement at the focal point are however difficult to make. In order to measure this the diffuse field is used. It is a statistical property of the diffuse field that it represents the total energy in the system. If the energy in the diffuse field for both the sequential and parallel firing case is measured then the difference between these, within the input signal bandwidth, is largely due to differences at the focal spot. This difference therefore gives a localized measurement of where energy is moving out of the transmission bandwidth due to nonlinear effects. This technique is used to image fatigue cracks and other damage types undetectable with conventional linear ultrasonic measurements.

  11. Image Restoration with New Technology

    DEFF Research Database (Denmark)

    Bülow-Møller, Anne Marie

    The article examines the role played by the corporate website while a company - Arla - attempted to restore an image tarnished by unethical behaviour. The company's strategy focussed on dialogue: it introduced a large number of authentic employees in their natural role as cook, dairy farmer, etc...... their image as a faceless monopoly with a humanized, personalised version. However, it should also be questioned if, in the long run, it was the image campaign rather than the visible efforts of the company to behave with consideration that brought about the desired change. Keywords: Image restoration......., and made them available to readers as experts providing inspiration and advice, or as writers blogging about the world of company, or as responsible people answering readers' frank questions about their practices in an open forum. It is argued that the electronic platform allowed the company to substitute...

  12. Bayesian image restoration, using configurations

    DEFF Research Database (Denmark)

    Thorarinsdottir, Thordis

    configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed...

  13. Bayesian image restoration, using configurations

    DEFF Research Database (Denmark)

    Thorarinsdottir, Thordis Linda

    2006-01-01

    configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for the salt and pepper noise. The inference in the model is discussed...

  14. Image Restoration with New Technology

    DEFF Research Database (Denmark)

    Bülow-Møller, Anne Marie

    The article examines the role played by the corporate website while a company - Arla - attempted to restore an image tarnished by unethical behaviour. The company's strategy focussed on dialogue: it introduced a large number of authentic employees in their natural role as cook, dairy farmer, etc...

  15. Image restoration using spectrum estimation

    Science.gov (United States)

    Na, Ki-Woon; Paik, Joon-Ki

    1994-09-01

    A stochastic approach to image restoration is proposed by using various spectrum estimation techniques. In order to estimate the original image from the knowledge of observed image, the minimum mean square error filter or Wiener filter is known to be optimum in the sense of minimizing the mean square error. The optimality of Wiener filter, however, holds only when the power spectra of the original image and noise are given in addition to the transfer function of the imaging system. In practice, the information of the original image is generally not available. In the present paper additive noise is assumed to be white with known variance and the Wiener filter is implemented using various estimation techniques for the original spectrum. The proposed method shows significant improvement over the conventional methods, such as the Wiener filter using constant signal-to-noise power ratio, particularly for images with low signal-to-noise ratio.

  16. Nonlinear Ultrasonic Phased Array Imaging

    Science.gov (United States)

    Potter, J. N.; Croxford, A. J.; Wilcox, P. D.

    2014-10-01

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging through depth.

  17. Nonlinear ultrasonic phased array imaging

    OpenAIRE

    Potter, J N; Croxford, A.J.; Wilcox, P. D.

    2014-01-01

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging t...

  18. Nonlinear ultrasonic phased array imaging.

    Science.gov (United States)

    Potter, J N; Croxford, A J; Wilcox, P D

    2014-10-03

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging through depth.

  19. Image Enhancement and Restoration by Image Inpainting

    Directory of Open Access Journals (Sweden)

    Nishant Trivedi

    2014-12-01

    Full Text Available Inpainting is the process of reconstructing lost or deteriorated part of images based on the background information. i. e .it fills the missing or damaged region in an image utilizing spatial information of its neighboring region. Inpainting algorithm have numerous applications. It is helpfully used for restoration of old films and object removal in digital photographs. The main goal of the algorithm is to modify the damaged region in an image in such a way that the inpainted region is undetectable to the ordinary observers who are not familiar with the original image. This proposed work presents image inpainting process for image enhancement and restoration by using structural, texture and exemplar techniques. This paper presents efficient algorithm that combines the advantages of these two approaches. We first note that exemplar-based texture synthesis contains the essential process required to replicate both texture and structure; the success of structure propagation, however, is highly dependent on the order in which the filling proceeds. We propose a best-first algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting. The actual color values are computed using exemplar-based synthesis. Computational efficiency is achieved by a blockbased sampling process.

  20. BAYESIAN IMAGE RESTORATION, USING CONFIGURATIONS

    Directory of Open Access Journals (Sweden)

    Thordis Linda Thorarinsdottir

    2011-05-01

    Full Text Available In this paper, we develop a Bayesian procedure for removing noise from images that can be viewed as noisy realisations of random sets in the plane. The procedure utilises recent advances in configuration theory for noise free random sets, where the probabilities of observing the different boundary configurations are expressed in terms of the mean normal measure of the random set. These probabilities are used as prior probabilities in a Bayesian image restoration approach. Estimation of the remaining parameters in the model is outlined for salt and pepper noise. The inference in the model is discussed in detail for 3 X 3 and 5 X 5 configurations and examples of the performance of the procedure are given.

  1. Super-resolution Restoration of Remote-sensing Images

    Institute of Scientific and Technical Information of China (English)

    LIU Yang-yang; JIN Wei-qi; SU Bing-hua; CHEN Hua; ZHANG Nan

    2006-01-01

    A novel image restoration scheme, which is super-resolution image restoration algorithm Poisson-maximum-afterword-probability based on Markvo constraint (MPMAP) combined with evaluating image detail parameter D, has been proposed. The advantage of super-resolution algorithm MPMAP incorporated with parameter D lies in the fact that super-resolution algorithm MPMAP model is discrete, which is in accordance with remote-sensing imaging model, and the algorithm MPMAP is proved applicable to linear and non-linear imaging models with a unique solution when noise is not severe. According to simulation experiments for practical images, super-resolution algorithm MPMAP can retain image details better than most of traditional restoration methods; at the same time, the proposed parameter D can help to identify real point spread function (PSF) value of degradation process. Processing result of practical remote-sensing images by MPMAP combined with parameter D are given, it illustrates that MPMAP restoration scheme combined PSF estimation has a better restoration result than that of Photoshop processing, based on the same original images. It is proved that the proposed scheme is helpful to offset the lack of resolution of the original remote-sensing images and has its extensive application foreground.

  2. Error image aware content restoration

    Science.gov (United States)

    Choi, Sungwoo; Lee, Moonsik; Jung, Byunghee

    2015-12-01

    As the resolution of TV significantly increased, content consumers have become increasingly sensitive to the subtlest defect in TV contents. This rising standard in quality demanded by consumers has posed a new challenge in today's context where the tape-based process has transitioned to the file-based process: the transition necessitated digitalizing old archives, a process which inevitably produces errors such as disordered pixel blocks, scattered white noise, or totally missing pixels. Unsurprisingly, detecting and fixing such errors require a substantial amount of time and human labor to meet the standard demanded by today's consumers. In this paper, we introduce a novel, automated error restoration algorithm which can be applied to different types of classic errors by utilizing adjacent images while preserving the undamaged parts of an error image as much as possible. We tested our method to error images detected from our quality check system in KBS(Korean Broadcasting System) video archive. We are also implementing the algorithm as a plugin of well-known NLE(Non-linear editing system), which is a familiar tool for quality control agent.

  3. ROV Based Underwater Blurred Image Restoration

    Institute of Scientific and Technical Information of China (English)

    LIU Zhishen; DING Tianfu; WANG Gang

    2003-01-01

    In this paper, we present a method of ROV based image processing to restore underwater blurry images from the theory of light and image transmission in the sea. Computer is used to simulate the maximum detection range of the ROV under different water body conditions. The receiving irradiance of the video camera at different detection ranges is also calculated. The ROV's detection performance under different water body conditions is given by simulation. We restore the underwater blurry images using the Wiener filter based on the simulation. The Wiener filter is shown to be a simple useful method for underwater image restoration in the ROV underwater experiments. We also present examples of restored images of an underwater standard target taken by the video camera in these experiments.

  4. Nonlinear intravascular ultrasound contrast imaging

    NARCIS (Netherlands)

    Goertz, David E.; Frijlink, Martijn E.; de Jong, N.; van der Steen, Antonius F.W.

    2006-01-01

    Nonlinear contrast agent imaging with intravascular ultrasound (IVUS) is investigated using a prototype IVUS system and an experimental small bubble contrast agent. The IVUS system employed a mechanically scanned single element transducer and was operated at a 20 MHz transmit frequency (F20) for

  5. Restoration of multichannel microwave radiometric images

    Science.gov (United States)

    Chin, R. T.; Yeh, C.-L.; Olson, W. S.

    1985-01-01

    A constrained iterative image restoration method is applied to multichannel diffraction-limited imagery. This method is based on the Gerchberg-Papoulis algorithm utilizing incomplete information and partial constraints. The procedure is described using the orthogonal projection operators which project onto two prescribed subspaces iteratively. Its properties and limitations are presented. The effect of noise was investigated and a better understanding of the performance of the algorithm with noisy data has been achieved. The restoration scheme with the selection of appropriate constraints was applied to a practical problem. The 6.6, 10.7, 18, and 21 GHz satellite images obtained by the scanning multichannel microwave radiometer (SMMR), each having different spatial resolution, were restored to a common, high resolution (that of the 37 GHz channels) to demonstrate the effectiveness of the method. Both simulated data and real data were used in this study. The restored multichannel images may be utilized to retrieve rainfall distributions.

  6. Restoration of multichannel microwave radiometric images

    Science.gov (United States)

    Chin, R. T.; Yeh, C.-L.; Olson, W. S.

    1985-01-01

    A constrained iterative image restoration method is applied to multichannel diffraction-limited imagery. This method is based on the Gerchberg-Papoulis algorithm utilizing incomplete information and partial constraints. The procedure is described using the orthogonal projection operators which project onto two prescribed subspaces iteratively. Its properties and limitations are presented. The effect of noise was investigated and a better understanding of the performance of the algorithm with noisy data has been achieved. The restoration scheme with the selection of appropriate constraints was applied to a practical problem. The 6.6, 10.7, 18, and 21 GHz satellite images obtained by the scanning multichannel microwave radiometer (SMMR), each having different spatial resolution, were restored to a common, high resolution (that of the 37 GHz channels) to demonstrate the effectiveness of the method. Both simulated data and real data were used in this study. The restored multichannel images may be utilized to retrieve rainfall distributions.

  7. Image Restoration After Pixel Binning in Image Sensors

    Institute of Scientific and Technical Information of China (English)

    LI Hao; ZHANG Hui; GUO Xiaolian; HU Guangshu

    2009-01-01

    A method was developed to restore degraded images to some extent after the pixel binning pro-cess in image sensors to improve the resolution. A pixel binning model was used to approximate the original un-binned image. Then, the least squares error criterion was used as a constraint to reconstruct the re-stored pixel values from the binning model. The technique achieves about a one-decibel increase in the peak signal-to-noise ratio compared with the odginal estimated image. The technique has good detail pre-servation performance as well as low computation load. Thus, this restoration technique provides valuable improvements in practical, real time image processing.

  8. Spatially Adaptive Intensity Bounds for Image Restoration

    Directory of Open Access Journals (Sweden)

    Kaaren L. May

    2003-11-01

    Full Text Available Spatially-adaptive intensity bounds on the image estimate are shown to be an effective means of regularising the ill-posed image restoration problem. For blind restoration, the local intensity constraints also help to further define the solution, thereby reducing the number of multiple solutions and local minima. The bounds are defined in terms of the local statistics of the image estimate and a control parameter which determines the scale of the bounds. Guidelines for choosing this parameter are developed in the context of classical (nonblind image restoration. The intensity bounds are applied by means of the gradient projection method, and conditions for convergence are derived when the bounds are refined using the current image estimate. Based on this method, a new alternating constrained minimisation approach is proposed for blind image restoration. On the basis of the experimental results provided, it is found that local intensity bounds offer a simple, flexible method of constraining both the nonblind and blind restoration problems.

  9. Matrix Krylov subspace methods for image restoration

    Directory of Open Access Journals (Sweden)

    khalide jbilou

    2015-09-01

    Full Text Available In the present paper, we consider some matrix Krylov subspace methods for solving ill-posed linear matrix equations and in those problems coming from the restoration of blurred and noisy images. Applying the well known Tikhonov regularization procedure leads to a Sylvester matrix equation depending the Tikhonov regularized parameter. We apply the matrix versions of the well known Krylov subspace methods, namely the Least Squared (LSQR and the conjugate gradient (CG methods to get approximate solutions representing the restored images. Some numerical tests are presented to show the effectiveness of the proposed methods.

  10. Non-linear Ultrasound Imaging

    DEFF Research Database (Denmark)

    Du, Yigang

    without iteration steps. The ASA is implemented in combination with Field II and extended to simulate the pulsed ultrasound fields. The simulated results from a linear array transducer are made by the ASA based on Field II, and by a released non-linear simulation program- Abersim, respectively....... The calculation speed of the ASA is increased approximately by a factor of 140. For the second harmonic point spread function the error of the full width is 1.5% at -6 dB and 6.4% at -12 dB compared to Abersim. To further investigate the linear and non-linear ultrasound fields, hydrophone measurements.......3% relative to the measurement from a 1 inch diameter transducer. A preliminary study for harmonic imaging using synthetic aperture sequential beamforming (SASB) has been demonstrated. A wire phantom underwater measurement is made by an experimental synthetic aperture real-time ultrasound scanner (SARUS...

  11. Restoration for Noise Removal in Quantum Images

    Science.gov (United States)

    Liu, Kai; Zhang, Yi; Lu, Kai; Wang, Xiaoping

    2017-09-01

    Quantum computation has become increasingly attractive in the past few decades due to its extraordinary performance. As a result, some studies focusing on image representation and processing via quantum mechanics have been done. However, few of them have considered the quantum operations for images restoration. To address this problem, three noise removal algorithms are proposed in this paper based on the novel enhanced quantum representation model, oriented to two kinds of noise pollution (Salt-and-Pepper noise and Gaussian noise). For the first algorithm Q-Mean, it is designed to remove the Salt-and-Pepper noise. The noise points are extracted through comparisons with the adjacent pixel values, after which the restoration operation is finished by mean filtering. As for the second method Q-Gauss, a special mask is applied to weaken the Gaussian noise pollution. The third algorithm Q-Adapt is effective for the source image containing unknown noise. The type of noise can be judged through the quantum statistic operations for the color value of the whole image, and then different noise removal algorithms are used to conduct image restoration respectively. Performance analysis reveals that our methods can offer high restoration quality and achieve significant speedup through inherent parallelism of quantum computation.

  12. Robust Image Restoration for Motion Blur of Image Sensors.

    Science.gov (United States)

    Yang, Fasheng; Huang, Yongmei; Luo, Yihan; Li, Lixing; Li, Hongwei

    2016-06-09

    Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly. To deal with these problems, we present a robust image restoration algorithm for motion blur of general image sensors in this paper. Firstly, we propose a self-adaptive structure extraction method based on the total variation (TV) to separate the reliable structures from textures and small details of a blurred image which may damage the kernel estimation and interim latent image restoration. Secondly, we combine the reliable structures with priors of the blur kernel, such as sparsity and continuity, by a two-step method with which noise can be removed during iterations of the estimation to improve the precision of the estimated blur kernel. Finally, we use a MR-based Wiener filter as the non-blind deconvolution algorithm to restore the final latent image. Experimental results demonstrate that our algorithm can restore large blur images with rich, small details effectively.

  13. Radiopacity of restorative materials using digital images.

    Science.gov (United States)

    Salzedas, Leda Maria Pescinini; Louzada, Mário Jefferson Quirino; de Oliveira Filho, Antonio Braz

    2006-04-01

    The radiopacity of esthetic restorative materials has been established as an important requirement, improving the radiographic diagnosis. The aim of this study was to evaluate the radiopacity of six restorative materials using a direct digital image system, comparing them to the dental tissues (enamel-dentin), expressed as equivalent thickness of aluminum (millimeters of aluminum). Five specimens of each material were made. Three 2-mm thick longitudinal sections were cut from an intact extracted permanent molar tooth (including enamel and dentin). An aluminum step wedge with 9 steps was used. The samples of different materials were placed on a phosphor plate together with a tooth section, aluminum step wedge and metal code letter, and were exposed using a dental x-ray unit. Five measurements of radiographic density were obtained from each image of each item assessed (restorative material, enamel, dentin, each step of the aluminum step wedge) and the mean of these values was calculated. Radiopacity values were subsequently calculated as equivalents of aluminum thickness. Analysis of variance (ANOVA) indicated significant differences in radiopacity values among the materials (Pcomposite restorations it is important that the restorative material to be used has enough radiopacity, in order to be easily distinguished from the tooth structure in the radiographic image. Knowledge on the radiopacity of different materials helps professionals to select the most suitable material, along with other properties such as biocompatibility, adhesion and esthetic.

  14. Adaptive nonlinear microscopy for whole tissue imaging

    Science.gov (United States)

    Müllenbroich, M. Caroline; McGhee, Ewan J.; Wright, Amanda J.; Anderson, Kurt I.; Mathieson, Keith

    2013-02-01

    Nonlinear microscopy is capable of imaging biological tissue non-invasively with sub-cellular resolution in three dimensions. For efficient multiphoton signal generation, it is necessary to focus high power, ultra-fast laser pulses into a volume of femtolitres. Aberrations introduced either by the system's optical setup or the sample under investigation cause a broadening of the diffraction limited focal spot which leads to loss of image intensity and resolution. Adaptive optics provides a means to compensate for these aberrations and is capable of restoring resolution and signal strength when imaging at depth. We describe the use of a micro-electro-mechanical systems (MEMS) deformable membrane mirror in a multiphoton adaptive microscope. The aberration correction is determined in a wavefront sensorless approach by rapidly altering the mirror shape with a random search algorithm until the fluorescence or second harmonic signal intensity is improved. We demonstrate the benefits of wavefront correction in a wide-variety of samples, including urea crystals, convallaria and organotypic tissue cultures. We show how the optimization algorithm can be adjusted, for example by including a bleaching compensation, to allow the user to switch between different imaging modalities, producing a versatile approach to aberration correction.

  15. Ghost suppression in image restoration filtering

    Science.gov (United States)

    Riemer, T. E.; Mcgillem, C. D.

    1975-01-01

    An optimum image restoration filter is described in which provision is made to constrain the spatial extent of the restoration function, the noise level of the filter output and the rate of falloff of the composite system point-spread away from the origin. Experimental results show that sidelobes on the composite system point-spread function produce ghosts in the restored image near discontinuities in intensity level. By redetermining the filter using a penalty function that is zero over the main lobe of the composite point-spread function of the optimum filter and nonzero where the point-spread function departs from a smoothly decaying function in the sidelobe region, a great reduction in sidelobe level is obtained. Almost no loss in resolving power of the composite system results from this procedure. By iteratively carrying out the same procedure even further reductions in sidelobe level are obtained. Examples of original and iterated restoration functions are shown along with their effects on a test image.

  16. Blind Image Deblurring Driven by Nonlinear Processing in the Edge Domain

    Directory of Open Access Journals (Sweden)

    Stefania Colonnese

    2004-12-01

    Full Text Available This work addresses the problem of blind image deblurring, that is, of recovering an original image observed through one or more unknown linear channels and corrupted by additive noise. We resort to an iterative algorithm, belonging to the class of Bussgang algorithms, based on alternating a linear and a nonlinear image estimation stage. In detail, we investigate the design of a novel nonlinear processing acting on the Radon transform of the image edges. This choice is motivated by the fact that the Radon transform of the image edges well describes the structural image features and the effect of blur, thus simplifying the nonlinearity design. The effect of the nonlinear processing is to thin the blurred image edges and to drive the overall blind restoration algorithm to a sharp, focused image. The performance of the algorithm is assessed by experimental results pertaining to restoration of blurred natural images.

  17. Satellite image blind restoration based on surface fitting and multivariate model

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-bing; YANG Shi-zhi; WANG Xian-hua; QIAO Yan-li

    2009-01-01

    Owing to the blurring effect from atmosphere and camera system in the satellite imaging a blind image restoration algo-rithm is proposed which includes the modulation transfer function (MTF) estimation and the image restoration. In the MTF estimation stage, based on every degradation process of satellite imaging-chain, a combined parametric model of MTF is given and used to fit the surface of normalized logarithmic amplitude spectrum of degraded image. In the image restoration stage, a maximum a posteriori (MAP) based edge-preserving image restoration method is presented which introduces multivariate Laplacian model to characterize the prior distribution of wavelet coefficients of original image. During the image restoration, in order to avoid solving high nonlinear equations, optimization transfer algorithm is adopted to decom-pose the image restoration procedure into two simple steps: Landweber iteration and wavelet thresholding denoising. In the numerical experiment, the satellite image restoration results from SPOT-5 and high resolution camera (HR) of China & Brazil earth resource satellite (CBERS-02B) ane compared, and the proposed algorithm is superior in the image edge preservation and noise inhibition.

  18. A Survey on Various Image Inpainting Techniques to Restore Image

    Directory of Open Access Journals (Sweden)

    Rajul Suthar,

    2014-02-01

    Full Text Available Image Inpainting or Image Restore is technique which is used to recover the damaged image and to fill the regions which are missing in original image in visually plausible way. Inpainting, the technique of modifying an image in an invisible form, it is art which is used from the early year. Applications of this technique include rebuilding of damaged photographs& films, removal of superimposed text, removal/replacement of unwanted objects, red eye correction, image coding. The main goal of the Inpainting is to change the damaged region in an image. In this paper we provide a review of different techniques used for image Inpainting. We discuss different inpainting techniques like Exemplar based image inpainting, PDE based image inpainting, texture synthesis based image inpainting, structural inpainting and textural inpainting.

  19. Nonlinear susceptibility magnitude imaging of magnetic nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Ficko, Bradley W., E-mail: Bradley.W.Ficko@Dartmouth.edu; Giacometti, Paolo; Diamond, Solomon G.

    2015-03-15

    This study demonstrates a method for improving the resolution of susceptibility magnitude imaging (SMI) using spatial information that arises from the nonlinear magnetization characteristics of magnetic nanoparticles (mNPs). In this proof-of-concept study of nonlinear SMI, a pair of drive coils and several permanent magnets generate applied magnetic fields and a coil is used as a magnetic field sensor. Sinusoidal alternating current (AC) in the drive coils results in linear mNP magnetization responses at primary frequencies, and nonlinear responses at harmonic frequencies and intermodulation frequencies. The spatial information content of the nonlinear responses is evaluated by reconstructing tomographic images with sequentially increasing voxel counts using the combined linear and nonlinear data. Using the linear data alone it is not possible to accurately reconstruct more than 2 voxels with a pair of drive coils and a single sensor. However, nonlinear SMI is found to accurately reconstruct 12 voxels (R{sup 2}=0.99, CNR=84.9) using the same physical configuration. Several time-multiplexing methods are then explored to determine if additional spatial information can be obtained by varying the amplitude, phase and frequency of the applied magnetic fields from the two drive coils. Asynchronous phase modulation, amplitude modulation, intermodulation phase modulation, and frequency modulation all resulted in accurate reconstruction of 6 voxels (R{sup 2}>0.9) indicating that time multiplexing is a valid approach to further increase the resolution of nonlinear SMI. The spatial information content of nonlinear mNP responses and the potential for resolution enhancement with time multiplexing demonstrate the concept and advantages of nonlinear SMI. - Highlights: • Development of a nonlinear susceptibility magnitude imaging model • Demonstration of nonlinear SMI with primary and harmonic frequencies • Demonstration of nonlinear SMI with primary and intermodulation

  20. Multi-scale retinex with color restoration image enhancement based on Gaussian filtering and guided filtering

    Science.gov (United States)

    Ma, Jinxiang; Fan, Xinnan; Ni, Jianjun; Zhu, Xifang; Xiong, Chao

    2017-07-01

    In order to restore image color and enhance contrast of remote sensing image without suffering from color cast and insufficient detail enhancement, a novel improved multi-scale retinex with color restoration (MSRCR) image enhancement algorithm based on Gaussian filtering and guided filtering was proposed in this paper. Firstly, multi-scale Gaussian filtering functions were used to deal with the original image to obtain the rough illumination components. Secondly, accurate illumination components were acquired by using the guided filtering functions. Then, combining with four-direction Sobel edge detector, a self-adaptive weight selection nonlinear image enhancement was carried out. Finally, a series of evaluate metrics such as mean, MSE, PSNR, contrast and information entropy were used to assess the enhancement algorithm. The results showed that the proposed algorithm can suppress effectively noise interference, enhance the image quality and restore image color effectively.

  1. Nonlinear Filter Based Image Denoising Using AMF Approach

    CERN Document Server

    Thivakaran, T K

    2010-01-01

    This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly e...

  2. Radial Basis Function Neural Network Based Super-Resolution Restoration for an Underspled Image

    Institute of Scientific and Technical Information of China (English)

    苏秉华; 金伟其; 牛丽红

    2004-01-01

    To achieve restoration of high frequency information for an underspled and degraded low-resolution image, a nonlinear and real-time processing method-the radial basis function (RBF) neural network based super-resolution method of restoration is proposed. The RBF network configuration and processing method is suitable for a high resolution restoration from an underspled low-resolution image. The soft-competition learning scheme based on the k-means algorithm is used, and can achieve higher mapping approximation accuracy without increase in the network size. Experiments showed that the proposed algorithm can achieve a super-resolution restored image from an underspled and degraded low-resolution image, and requires a shorter training time when compared with the multiplayer perception (MLP) network.

  3. A Variational Bayesian Approach to Multiframe Image Restoration.

    Science.gov (United States)

    Sonogashira, Motoharu; Funatomi, Takuya; Iiyama, Masaaki; Minoh, Michihiko

    2017-03-06

    Image restoration is a fundamental problem in the field of image processing. The key objective of image restoration is to recover clean images from images degraded by noise and blur. Recently, a family of new statistical techniques called variational Bayes (VB) has been introduced to image restoration, which enables us to automatically tune parameters that control restoration. While information from one image is often insufficient for high-quality restoration, however, current state-of-theart methods of image restoration via VB approaches use only a single degraded image to recover a clean image. In this paper, we propose a novel method of multiframe image restoration via a VB approach, which can achieve higher image quality while tuning parameters automatically. Given multiple degraded images, this method jointly estimates a clean image and other parameters, including an image warping parameter introduced for the use of multiple images, through Bayesian inference that we enable by making full use of VB techniques. Through various experiments, we demonstrate the effectiveness of our multiframe method by comparing it with single-frame one, and also show the advantages of our VB approach over non-VB approaches.

  4. Effective Image Restorations Using a Novel Spatial Adaptive Prior

    Directory of Open Access Journals (Sweden)

    Limin Luo

    2010-01-01

    Full Text Available Bayesian or Maximum a posteriori (MAP approaches can effectively overcome the ill-posed problems of image restoration or deconvolution through incorporating a priori image information. Many restoration methods, such as nonquadratic prior Bayesian restoration and total variation regularization, have been proposed with edge-preserving and noise-removing properties. However, these methods are often inefficient in restoring continuous variation region and suppressing block artifacts. To handle this, this paper proposes a Bayesian restoration approach with a novel spatial adaptive (SA prior. Through selectively and adaptively incorporating the nonlocal image information into the SA prior model, the proposed method effectively suppress the negative disturbance from irrelevant neighbor pixels, and utilizes the positive regularization from the relevant ones. A two-step restoration algorithm for the proposed approach is also given. Comparative experimentation and analysis demonstrate that, bearing high-quality edge-preserving and noise-removing properties, the proposed restoration also has good deblocking property.

  5. Efficient blind image restoration using discrete periodic radon transform.

    Science.gov (United States)

    Lun, Daniel P K; Chan, Tommy C L; Hsung, Tai-Chiu; Feng, David Dagan; Chan, Yuk-Hee

    2004-02-01

    Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. Many approaches have been proposed to solve the problem and they have shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of these approaches are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration based on the discrete periodic Radon transform (DPRT). With DPRT, the original two-dimensional blind image restoration problem is converted into one-dimensional ones, which greatly reduces the memory size and computational time required. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.

  6. Preconditioned Iterative Methods for Algebraic Systems from Multiplicative Half-Quadratic Regularization Image Restorations

    Institute of Scientific and Technical Information of China (English)

    Zhong-Zhi; Yu-Mei; K.

    2010-01-01

    Image restoration is often solved by minimizing an energy function consisting of a data-fidelity term and a regularization term. A regularized convex term can usually preserve the image edges well in the restored image. In this paper, we consider a class of convex and edge-preserving regularization functions, I.e., multiplicative half-quadratic regularizations, and we use the Newton method to solve the correspondingly reduced systems of nonlinear equations. At each Newton iterate, the preconditioned conjugate gradient method, incorporated with a constraint preconditioner, is employed to solve the structured Newton equation that has a symmetric positive definite coefficient matrix.The igenvalue bounds of the preconditioned matrix are deliberately derived, which can be used to estimate the convergence speed of the preconditioned conjugate gradient method. We use experimental results to demonstrate that this new approach is efficient,and the effect of image restoration is r0easonably well.

  7. Dynamical Imaging using Spatial Nonlinearity

    Science.gov (United States)

    2014-01-29

    Imin )/ (Imax + Imin ) = 0.15 for detection of the bars (from maxima to central dip). For our experimental measurements, the best linear visibility is...Statistical theory for incoherent light propagation in nonlinear media, Physical Review E, 65 (2002) 035602. [52] M.J. Bastiaans, Application of the...1238. [53] M.E. Testorf, B.M. Hennelly, J. Ojeda-Castañeda, Phase-space optics : fundamentals and applications , McGraw-Hill, New York, 2010. [54] K.H

  8. Nonlinear susceptibility magnitude imaging of magnetic nanoparticles

    Science.gov (United States)

    Ficko, Bradley W.; Giacometti, Paolo; Diamond, Solomon G.

    2015-03-01

    This study demonstrates a method for improving the resolution of susceptibility magnitude imaging (SMI) using spatial information that arises from the nonlinear magnetization characteristics of magnetic nanoparticles (mNPs). In this proof-of-concept study of nonlinear SMI, a pair of drive coils and several permanent magnets generate applied magnetic fields and a coil is used as a magnetic field sensor. Sinusoidal alternating current (AC) in the drive coils results in linear mNP magnetization responses at primary frequencies, and nonlinear responses at harmonic frequencies and intermodulation frequencies. The spatial information content of the nonlinear responses is evaluated by reconstructing tomographic images with sequentially increasing voxel counts using the combined linear and nonlinear data. Using the linear data alone it is not possible to accurately reconstruct more than 2 voxels with a pair of drive coils and a single sensor. However, nonlinear SMI is found to accurately reconstruct 12 voxels (R2=0.99, CNR=84.9) using the same physical configuration. Several time-multiplexing methods are then explored to determine if additional spatial information can be obtained by varying the amplitude, phase and frequency of the applied magnetic fields from the two drive coils. Asynchronous phase modulation, amplitude modulation, intermodulation phase modulation, and frequency modulation all resulted in accurate reconstruction of 6 voxels (R2>0.9) indicating that time multiplexing is a valid approach to further increase the resolution of nonlinear SMI. The spatial information content of nonlinear mNP responses and the potential for resolution enhancement with time multiplexing demonstrate the concept and advantages of nonlinear SMI.

  9. Image denoising using modified nonlinear diffusion approach

    Science.gov (United States)

    Upadhyay, Akhilesh R.; Talbar, Sanjay N.; Sontakke, Trimbak R.

    2006-01-01

    Partial Differential Equation (PDE) based, non-linear diffusion approaches are an effective way to denoise the images. In this paper, the work is extended to include anisotropic diffusion, where the diffusivity is a tensor valued function, which can be adapted to local edge orientation. This allows smoothing along the edges, but not perpendicular to it. The diffusion tensor is a function of differential structure of the evolving image itself. Such a feedback leads to nonlinear diffusion filters. It shows improved performance in the presence of noise. The original anisotropic diffusion algorithm updates each point based on four nearest-neighbor differences, the progress of diffusion results in improved edges. In the proposed method the edges are better preserved because diffusion is controlled by the gray level differences of diagonal neighbors in addition to 4 nearest neighbors using coupled PDF formulation. The proposed algorithm gives excellent results for MRI images, Biomedical images and Fingerprint images with noise.

  10. Image Restoration Technology Based on Discrete Neural network

    Directory of Open Access Journals (Sweden)

    Zhou Duoying

    2015-01-01

    Full Text Available With the development of computer science and technology, the development of artificial intelligence advances rapidly in the field of image restoration. Based on the MATLAB platform, this paper constructs a kind of image restoration technology of artificial intelligence based on the discrete neural network and feedforward network, and carries out simulation and contrast of the restoration process by the use of the bionic algorithm. Through the application of simulation restoration technology, this paper verifies that the discrete neural network has a good convergence and identification capability in the image restoration technology with a better effect than that of the feedforward network. The restoration technology based on the discrete neural network can provide a reliable mathematical model for this field.

  11. Joint Multi-Focus Fusion and Bayer ImageRestoration

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    In this paper, a joint multifocus image fusion and Bayer pattern image restoration algorithm for raw images of single-sensor colorimaging devices is proposed. Different from traditional fusion schemes, the raw Bayer pattern images are fused before colorrestoration. Therefore, the Bayer image restoration operation is only performed one time. Thus, the proposed algorithm is moreefficient than traditional fusion schemes. In detail, a clarity measurement of Bayer pattern image is defined for raw Bayer patternimages, and the fusion operator is performed on superpixels which provide powerful grouping cues of local image feature. Theraw images are merged with refined weight map to get the fused Bayer pattern image, which is restored by the demosaicingalgorithm to get the full resolution color image. Experimental results demonstrate that the proposed algorithm can obtain betterfused results with more natural appearance and fewer artifacts than the traditional algorithms.

  12. Theoretical aspects of nonlinear echo image system

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ruiquan; FENG Shaosong

    2003-01-01

    In order to develop the nonlinear echo image system to diagnose pathological changes in biological tissue , a simple physical model to analyse the character of nonlinear reflected wave in biological medium is postulated. The propagation of large amplitude plane sound wave in layered biological media is analysed for the one dimensional case by the method of successive approximation and the expression for the second order wave reflected from any interface of layered biological media is obtained. The relations between the second order reflection coefficients and the nonlinear parameters of medium below the interface are studied in three layers interfaces. Finally, the second order reflection coefficients of four layered media are calculated numerically. The results indicate that the nonlinear parameter B/A of each layer of biological media can be determined by the reflection method.

  13. Nonlinear spectral imaging of biological tissues

    Science.gov (United States)

    Palero, J. A.

    2007-07-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal. Because biological intrinsic emission is generally very weak and extends from the ultraviolet to the visible spectral range, a broad-spectral range and high sensitivity 3D spectral imaging system is developed. Imaging the spectral characteristics of the biological intrinsic emission reveals the structure and biochemistry of the cells and extra-cellular components. By using different methods in visualizing the spectral images, discrimination between different tissue structures is achieved without the use of any stain or fluorescent label. For instance, RGB real color spectral images of the intrinsic emission of mouse skin tissues show blue cells, green hair follicles, and purple collagen fibers. The color signature of each tissue component is directly related to its characteristic emission spectrum. The results of this study show that skin tissue nonlinear intrinsic emission is mainly due to the autofluorescence of reduced nicotinamide adenine dinucleotide (phosphate), flavins, keratin, melanin, phospholipids, elastin and collagen and nonlinear Raman scattering and second-harmonic generation in Type I collagen. In vivo time-lapse spectral imaging is implemented to study metabolic changes in epidermal cells in tissues. Optical scattering in tissues, a key factor in determining the maximum achievable imaging depth, is also investigated in this work.

  14. Resolution enhancement in nonlinear photoacoustic imaging

    Energy Technology Data Exchange (ETDEWEB)

    Goy, Alexandre S.; Fleischer, Jason W. [Department of Electrical Engineering, Princeton University, Olden St., Princeton, New Jersey 08544 (United States)

    2015-11-23

    Nonlinear processes can be exploited to gain access to more information than is possible in the linear regime. Nonlinearity modifies the spectra of the excitation signals through harmonic generation, frequency mixing, and spectral shifting, so that features originally outside the detector range can be detected. Here, we present an experimental study of resolution enhancement for photoacoustic imaging of thin metal layers immersed in water. In this case, there is a threshold in the excitation below which no acoustic signal is detected. Above threshold, the nonlinearity reduces the width of the active area of the excitation beam, resulting in a narrower absorption region and thus improved spatial resolution. This gain is limited only by noise, as the active area of the excitation can be arbitrarily reduced when the fluence becomes closer to the threshold. Here, we demonstrate a two-fold improvement in resolution and quantify the image quality as the excitation fluence goes through threshold.

  15. Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    Full Text Available Due to the rapid development of motor vehicle Driver Assistance Systems (DAS, the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

  16. Nonlinear spectral imaging of biological tissues

    NARCIS (Netherlands)

    Palero, J.A.

    2007-01-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal.

  17. Nonlinear spectral imaging of biological tissues

    NARCIS (Netherlands)

    Palero, J.A.

    2007-01-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal.

  18. Nonlinear ultrasound imaging of nanoscale acoustic biomolecules

    Science.gov (United States)

    Maresca, David; Lakshmanan, Anupama; Lee-Gosselin, Audrey; Melis, Johan M.; Ni, Yu-Li; Bourdeau, Raymond W.; Kochmann, Dennis M.; Shapiro, Mikhail G.

    2017-02-01

    Ultrasound imaging is widely used to probe the mechanical structure of tissues and visualize blood flow. However, the ability of ultrasound to observe specific molecular and cellular signals is limited. Recently, a unique class of gas-filled protein nanostructures called gas vesicles (GVs) was introduced as nanoscale (˜250 nm) contrast agents for ultrasound, accompanied by the possibilities of genetic engineering, imaging of targets outside the vasculature and monitoring of cellular signals such as gene expression. These possibilities would be aided by methods to discriminate GV-generated ultrasound signals from anatomical background. Here, we show that the nonlinear response of engineered GVs to acoustic pressure enables selective imaging of these nanostructures using a tailored amplitude modulation strategy. Finite element modeling predicted a strongly nonlinear mechanical deformation and acoustic response to ultrasound in engineered GVs. This response was confirmed with ultrasound measurements in the range of 10 to 25 MHz. An amplitude modulation pulse sequence based on this nonlinear response allows engineered GVs to be distinguished from linear scatterers and other GV types with a contrast ratio greater than 11.5 dB. We demonstrate the effectiveness of this nonlinear imaging strategy in vitro, in cellulo, and in vivo.

  19. Extended arrays for nonlinear susceptibility magnitude imaging

    Science.gov (United States)

    Ficko, Bradley W.; Giacometti, Paolo; Diamond, Solomon G.

    2016-01-01

    This study implements nonlinear susceptibility magnitude imaging (SMI) with multifrequency intermodulation and phase encoding. An imaging grid was constructed of cylindrical wells of 3.5-mm diameter and 4.2-mm height on a hexagonal two-dimensional 61-voxel pattern with 5-mm spacing. Patterns of sample wells were filled with 40-μl volumes of Fe3O4 starch-coated magnetic nanoparticles (mNPs) with a hydrodynamic diameter of 100 nm and a concentration of 25 mg/ml. The imaging hardware was configured with three excitation coils and three detection coils in anticipation that a larger imaging system will have arrays of excitation and detection coils. Hexagonal and bar patterns of mNP were successfully imaged (R2 > 0.9) at several orientations. This SMI demonstration extends our prior work to feature a larger coil array, enlarged field-of-view, effective phase encoding scheme, reduced mNP sample size, and more complex imaging patterns to test the feasibility of extending the method beyond the pilot scale. The results presented in this study show that nonlinear SMI holds promise for further development into a practical imaging system for medical applications. PMID:26124044

  20. Effects of vibration measurement error on remote sensing image restoration

    Science.gov (United States)

    Sun, Xuan; Wei, Zhang; Zhi, Xiyang

    2016-10-01

    Satellite vibrations would lead to image motion blur. Since the vibration isolators cannot fully suppress the influence of vibrations, image restoration methods are usually adopted, and the vibration characteristics of imaging system are usually required as algorithm inputs for better restoration results, making the vibration measurement error strongly connected to the final outcome. If the measurement error surpass a certain range, the restoration may not be implemented successfully. Therefore it is important to test the applicable scope of restoration algorithms and control the vibrations within the range, on the other hand, if the algorithm is robust, then the requirements for both vibration isolator and vibration detector can be lowered and thus less financial cost is needed. In this paper, vibration-induced degradation is first analyzed, based on which the effects of measurement error on image restoration are further analyzed. The vibration-induced degradation is simulated using high resolution satellite images and then the applicable working condition of typical restoration algorithms are tested with simulation experiments accordingly. The research carried out in this paper provides a valuable reference for future satellite design which plan to implement restoration algorithms.

  1. Color Restoration of Monochrome Image Formatted by Y800

    National Research Council Canada - National Science Library

    Jun Luo; Rui Su; Ying Chen

    2013-01-01

    ...) directly, we design a Bayer mode color filter array start with specific pixels to satisfy the imaging condition and then we use bilinear interpolation algorithm to restore the color of original...

  2. Enhancing retinal images by nonlinear registration

    CERN Document Server

    Molodij, Guillaume; Glanc, Marie; Chenegros, Guillaume

    2014-01-01

    Being able to image the human retina in high resolution opens a new era in many important fields, such as pharmacological research for retinal diseases, researches in human cognition, nervous system, metabolism and blood stream, to name a few. In this paper, we propose to share the knowledge acquired in the fields of optics and imaging in solar astrophysics in order to improve the retinal imaging at very high spatial resolution in the perspective to perform a medical diagnosis. The main purpose would be to assist health care practitioners by enhancing retinal images and detect abnormal features. We apply a nonlinear registration method using local correlation tracking to increase the field of view and follow structure evolutions using correlation techniques borrowed from solar astronomy technique expertise. Another purpose is to define the tracer of movements after analyzing local correlations to follow the proper motions of an image from one moment to another, such as changes in optical flows that would be o...

  3. Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2016-03-01

    Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using

  4. Image and video restorations via nonlocal kernel regression.

    Science.gov (United States)

    Zhang, Haichao; Yang, Jianchao; Zhang, Yanning; Huang, Thomas S

    2013-06-01

    A nonlocal kernel regression (NL-KR) model is presented in this paper for various image and video restoration tasks. The proposed method exploits both the nonlocal self-similarity and local structural regularity properties in natural images. The nonlocal self-similarity is based on the observation that image patches tend to repeat themselves in natural images and videos, and the local structural regularity observes that image patches have regular structures where accurate estimation of pixel values via regression is possible. By unifying both properties explicitly, the proposed NL-KR framework is more robust in image estimation, and the algorithm is applicable to various image and video restoration tasks. In this paper, we apply the proposed model to image and video denoising, deblurring, and superresolution reconstruction. Extensive experimental results on both single images and realistic video sequences demonstrate that the proposed framework performs favorably with previous works both qualitatively and quantitatively.

  5. Adaptive Image Restoration and Segmentation Method Using Different Neighborhood Sizes

    Directory of Open Access Journals (Sweden)

    Chengcheng Li

    2003-04-01

    Full Text Available The image restoration methods based on the Bayesian's framework and Markov random fields (MRF have been widely used in the image-processing field. The basic idea of all these methods is to use calculus of variation and mathematical statistics to average or estimate a pixel value by the values of its neighbors. After applying this averaging process to the whole image a number of times, the noisy pixels, which are abnormal values, are filtered out. Based on the Tea-trade model, which states that the closer the neighbor, more contribution it makes, almost all of these methods use only the nearest four neighbors for calculation. In our previous research [1, 2], we extended the research on CLRS (image restoration and segmentation by using competitive learning algorithm to enlarge the neighborhood size. The results showed that the longer neighborhood range could improve or worsen the restoration results. We also found that the autocorrelation coefficient was an important factor to determine the proper neighborhood size. We then further realized that the computational complexity increased dramatically along with the enlargement of the neighborhood size. This paper is to further the previous research and to discuss the tradeoff between the computational complexity and the restoration improvement by using longer neighborhood range. We used a couple of methods to construct the synthetic images with the exact correlation coefficients we want and to determine the corresponding neighborhood size. We constructed an image with a range of correlation coefficients by blending some synthetic images. Then an adaptive method to find the correlation coefficients of this image was constructed. We restored the image by applying different neighborhood CLRS algorithm to different parts of the image according to its correlation coefficient. Finally, we applied this adaptive method to some real-world images to get improved restoration results than by using single

  6. Scattering removal for finger-vein image restoration.

    Science.gov (United States)

    Yang, Jinfeng; Zhang, Ben; Shi, Yihua

    2012-01-01

    Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy.

  7. Accelerated Edge-Preserving Image Restoration Without Boundary Artifacts

    OpenAIRE

    Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A.

    2013-01-01

    To reduce blur in noisy images, regularized image restoration methods have been proposed that use non-quadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a non-circulant model could prevent these arti...

  8. Nonlinear Polarimetric Microscopy for Biomedical Imaging

    Science.gov (United States)

    Samim, Masood

    A framework for the nonlinear optical polarimetry and polarimetric microscopy is developed. Mathematical equations are derived in terms of linear and nonlinear Stokes Mueller formalism, which comprehensively characterize the polarization properties of the incoming and outgoing radiations, and provide structural information about the organization of the investigated materials. The algebraic formalism developed in this thesis simplifies many predictions for a nonlinear polarimetry study and provides an intuitive understanding of various polarization properties for radiations and the intervening medium. For polarimetric microscopy experiments, a custom fast-scanning differential polarization microscope is developed, which is also capable of real-time three-dimensional imaging. The setup is equipped with a pair of high-speed resonant and galvanometric scanning mirrors, and supplemented by advanced adaptive optics and data acquisition modules. The scanning mirrors when combined with the adaptive optics deformable mirror enable fast 3D imaging. Deformable membrane mirrors and genetic algorithm optimization routines are employed to improve the imaging conditions including correcting the optical aberrations, maximizing signal intensities, and minimizing point-spread-functions of the focal volume. A field-programmable-gate array (FPGA) chip is exploited to rapidly acquire and process the multidimensional data. Using the nonlinear optical polarimetry framework and the home-built polarization microscope, a few biologically important tissues are measured and analyzed to gain insight as to their structure and dynamics. The structure and distribution of muscle sarcomere myosins, connective tissue collagen, carbohydrate-rich starch, and fruit fly eye retinal molecules are characterized with revealing polarization studies. In each case, using the theoretical framework, polarization sensitive data are analyzed to decipher the molecular orientations and nonlinear optical

  9. A Good Image Model Eases Restoration

    Science.gov (United States)

    2002-02-06

    algorithms, and various classical as well as unexpected new applications of the BV ( bounded variation ) image model, first introduced into image processing by Rudin, Osher, and Fatemi in 1992 Physica D, 60:259-268.

  10. Image restoration by minimizing zero norm of wavelet frame coefficients

    Science.gov (United States)

    Bao, Chenglong; Dong, Bin; Hou, Likun; Shen, Zuowei; Zhang, Xiaoqun; Zhang, Xue

    2016-11-01

    In this paper, we propose two algorithms, namely the extrapolated proximal iterative hard thresholding (EPIHT) algorithm and the EPIHT algorithm with line-search, for solving the {{\\ell }}0-norm regularized wavelet frame balanced approach for image restoration. Under the theoretical framework of Kurdyka-Łojasiewicz property, we show that the sequences generated by the two algorithms converge to a local minimizer with linear convergence rate. Moreover, extensive numerical experiments on sparse signal reconstruction and wavelet frame based image restoration problems including CT reconstruction, image deblur, demonstrate the improvement of {{\\ell }}0-norm based regularization models over some prevailing ones, as well as the computational efficiency of the proposed algorithms.

  11. The Restoration of Textured Images Using Fractional-Order Regularization

    Directory of Open Access Journals (Sweden)

    Ying Fu

    2014-01-01

    Full Text Available Image restoration problem is ill-posed, so most image restoration algorithms exploit sparse prior in gradient domain to regularize it to yield high-quality results, reconstructing an image with piecewise smooth characteristics. While sparse gradient prior has good performance in noise removal and edge preservation, it also tends to remove midfrequency component such as texture. In this paper, we introduce the sparse prior in fractional-order gradient domain as texture-preserving strategy to restore textured images degraded by blur and/or noise. And we solve the unknown variables in the proposed model using method based on half-quadratic splitting by minimizing the nonconvex energy functional. Numerical experiments show our algorithm's robust outperformance.

  12. Hugh Grant's Image Restoration Discourse: An Actor Apologizes.

    Science.gov (United States)

    Benoit, William L.

    1997-01-01

    Examines the strategies used by actor Hugh Grant (in his appearances on talk shows) to help restore his reputation after he was arrested for lewd behavior with a prostitute. Uses this case as a springboard to contrast entertainment image repair with political and corporate image repair, arguing that important situational differences can be…

  13. The Tonya Harding Controversy: An Analysis of Image Restoration Strategies.

    Science.gov (United States)

    Benoit, William L.; Hanczor, Robert S.

    1994-01-01

    Analyzes Tonya Harding's defense of her image in "Eye to Eye with Connie Chung," applying the theory of image restoration discourse. Finds that the principal strategies employed in her behalf were bolstering, denial, and attacking her accuser, but that these strategies were not developed very effectively in this instance. (SR)

  14. Study of Image Processing, Enhancement and Restoration

    Directory of Open Access Journals (Sweden)

    Bhausaheb Shivajirao Shinde

    2011-11-01

    Full Text Available Digital image processing is a means by which the valuable information in observed raw image data can be revealed. A web-based image processing pipeline was created under the ambitious educational program Venus Transit 2004 (VT-2004. The active participants in the VT-2004 can apply the basic processing methods to the images obtained by their amateur telescopes and/or they can process an image observed at any observatory involved in the project. The processed result image is displayed immediately on the display. Above that all participants can follow the distance Sun-Venus centers computation performed at the professional observatory in the real time. There is a possibility to submit an image from their own observation into the database. It will be used for the distance Earth-Sun computation.

  15. Sparse representation for color image restoration.

    Science.gov (United States)

    Mairal, Julien; Elad, Michael; Sapiro, Guillermo

    2008-01-01

    Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. In particular, the design of well adapted dictionaries for images has been a major challenge. The K-SVD has been recently proposed for this task and shown to perform very well for various grayscale image processing tasks. In this paper, we address the problem of learning dictionaries for color images and extend the K-SVD-based grayscale image denoising algorithm that appears in. This work puts forward ways for handling nonhomogeneous noise and missing information, paving the way to state-of-the-art results in applications such as color image denoising, demosaicing, and inpainting, as demonstrated in this paper.

  16. Full Restoration of Visual Encrypted Color Images

    CERN Document Server

    Persson, Simeon

    2011-01-01

    While strictly black and white images have been the basis for visual cryptography, there has been a lack of an easily implemented format for colour images. This paper establishes a simple, yet secure way of implementing visual cryptography with colour, assuming a binary data representation.

  17. Scattering Removal for Finger-Vein Image Restoration

    OpenAIRE

    Jinfeng Yang; Ben Zhang; Yihua Shi

    2012-01-01

    Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of f...

  18. Nonlocal Mumford-Shah regularizers for color image restoration.

    Science.gov (United States)

    Jung, Miyoun; Bresson, Xavier; Chan, Tony F; Vese, Luminita A

    2011-06-01

    We propose here a class of restoration algorithms for color images, based upon the Mumford-Shah (MS) model and nonlocal image information. The Ambrosio-Tortorelli and Shah elliptic approximations are defined to work in a small local neighborhood, which are sufficient to denoise smooth regions with sharp boundaries. However, texture is nonlocal in nature and requires semilocal/non-local information for efficient image denoising and restoration. Inspired from recent works (nonlocal means of Buades, Coll, Morel, and nonlocal total variation of Gilboa, Osher), we extend the local Ambrosio-Tortorelli and Shah approximations to MS functional (MS) to novel nonlocal formulations, for better restoration of fine structures and texture. We present several applications of the proposed nonlocal MS regularizers in image processing such as color image denoising, color image deblurring in the presence of Gaussian or impulse noise, color image inpainting, color image super-resolution, and color filter array demosaicing. In all the applications, the proposed nonlocal regularizers produce superior results over the local ones, especially in image inpainting with large missing regions. We also prove several characterizations of minimizers based upon dual norm formulations.

  19. An Iterative Shrinkage Approach to Total-Variation Image Restoration

    CERN Document Server

    Michailovich, Oleg

    2009-01-01

    The problem of restoration of digital images from their degraded measurements plays a central role in a multitude of practically important applications. A particularly challenging instance of this problem occurs in the case when the degradation phenomenon is modeled by an ill-conditioned operator. In such a case, the presence of noise makes it impossible to recover a valuable approximation of the image of interest without using some a priori information about its properties. Such a priori information is essential for image restoration, rendering it stable and robust to noise. Particularly, if the original image is known to be a piecewise smooth function, one of the standard priors used in this case is defined by the Rudin-Osher-Fatemi model, which results in total variation (TV) based image restoration. The current arsenal of algorithms for TV-based image restoration is vast. In the present paper, a different approach to the solution of the problem is proposed based on the method of iterative shrinkage (aka i...

  20. Alternating Krylov subspace image restoration methods

    National Research Council Canada - National Science Library

    Abad, J.O; Morigi, S; Reichel, L; Sgallari, F

    2012-01-01

    ... of the Krylov subspace used. However, our solution methods, suitably modified, also can be applied when no bound for the norm of η δ is known. We determine an approximation of the desired image u ˆ by so...

  1. Enhancing retinal images by nonlinear registration

    Science.gov (United States)

    Molodij, G.; Ribak, E. N.; Glanc, M.; Chenegros, G.

    2015-05-01

    Being able to image the human retina in high resolution opens a new era in many important fields, such as pharmacological research for retinal diseases, researches in human cognition, nervous system, metabolism and blood stream, to name a few. In this paper, we propose to share the knowledge acquired in the fields of optics and imaging in solar astrophysics in order to improve the retinal imaging in the perspective to perform a medical diagnosis. The main purpose would be to assist health care practitioners by enhancing the spatial resolution of the retinal images and increase the level of confidence of the abnormal feature detection. We apply a nonlinear registration method using local correlation tracking to increase the field of view and follow structure evolutions using correlation techniques borrowed from solar astronomy technique expertise. Another purpose is to define the tracer of movements after analyzing local correlations to follow the proper motions of an image from one moment to another, such as changes in optical flows that would be of high interest in a medical diagnosis.

  2. Bregmanized Domain Decomposition for Image Restoration

    KAUST Repository

    Langer, Andreas

    2012-05-22

    Computational problems of large-scale data are gaining attention recently due to better hardware and hence, higher dimensionality of images and data sets acquired in applications. In the last couple of years non-smooth minimization problems such as total variation minimization became increasingly important for the solution of these tasks. While being favorable due to the improved enhancement of images compared to smooth imaging approaches, non-smooth minimization problems typically scale badly with the dimension of the data. Hence, for large imaging problems solved by total variation minimization domain decomposition algorithms have been proposed, aiming to split one large problem into N > 1 smaller problems which can be solved on parallel CPUs. The N subproblems constitute constrained minimization problems, where the constraint enforces the support of the minimizer to be the respective subdomain. In this paper we discuss a fast computational algorithm to solve domain decomposition for total variation minimization. In particular, we accelerate the computation of the subproblems by nested Bregman iterations. We propose a Bregmanized Operator Splitting-Split Bregman (BOS-SB) algorithm, which enforces the restriction onto the respective subdomain by a Bregman iteration that is subsequently solved by a Split Bregman strategy. The computational performance of this new approach is discussed for its application to image inpainting and image deblurring. It turns out that the proposed new solution technique is up to three times faster than the iterative algorithm currently used in domain decomposition methods for total variation minimization. © Springer Science+Business Media, LLC 2012.

  3. Restoration of uneven illumination in light sheet microscopy images.

    Science.gov (United States)

    Uddin, Mohammad Shorif; Lee, Hwee Kuan; Preibisch, Stephan; Tomancak, Pavel

    2011-08-01

    Light microscopy images suffer from poor contrast due to light absorption and scattering by the media. The resulting decay in contrast varies exponentially across the image along the incident light path. Classical space invariant deconvolution approaches, while very effective in deblurring, are not designed for the restoration of uneven illumination in microscopy images. In this article, we present a modified radiative transfer theory approach to solve the contrast degradation problem of light sheet microscopy (LSM) images. We confirmed the effectiveness of our approach through simulation as well as real LSM images.

  4. Digital image restoration based on pixel simultaneous detection probabilities

    CERN Document Server

    Grabskii, V

    2008-01-01

    Here an image restoration on the basis of pixel simultaneous detection probabilities (PSDP) is proposed. These probabilities can be precisely determined by means of correlations measurement [NIMA 586 (2008) 314-326]. The proposed image restoration is based on the solution of matrix equation. Non-zero elements of Toeplitz block matrix with ones on the main diagonal, is determined using PSDP. The number of non zero descending diagonals depends on the detector construction and is not always smaller than 8. To solve the matrix equation, the Gaussian elimination algorithm is used. The proposed restoration algorithm is studied by means of the simulated images (with and without additive noise using PSDP for General Electric Senographe 2000D mammography device detector) and a small area (160x160 pixels) of real images acquired by the above mentioned device. The estimation errors of PSDP and the additive noise magnitude permits to restore images with the precision better than 2% for the above mentioned detector. The a...

  5. Simultaneous measurements of nonlinear refraction and nonlinear absorption using a 4f imaging system

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A method is reported to simultaneously measure the nonlinear absorption and re-fraction coefficients of materials using a nonlinear-imaging technique with a phase object. In this technique, the sign and magnitude of both the nonlinear absorption and refraction can be acquired conveniently from the analysis of three experiment images: the linear image, the nonlinear image and the image without sample. In order to validate our approach, we demonstrate this method for ZnSe at 532 nm where two-photon absorption is present and the nonlinear refractive index n2 is negative. The values of β (nonlinear absorption coefficient) and n2 we measured are very close to the values found in other literature.

  6. Exploiting a nonlinear restoring force to improve the performance of flow energy harvesters

    Science.gov (United States)

    Bibo, Amin; Alhadidi, Ali H.; Daqaq, Mohammed F.

    2015-01-01

    This paper investigates employing a nonlinear restoring force to improve the performance of flow energy harvesters (FEHs). To that end, a galloping FEH possessing a quartic potential energy function of the form V =1/2 μy2+1/4 γy4 is considered. This potential function is used to model either a softening (μ > 0, γ 0, γ > 0), or bi-stable (μ 0) restoring force. A physics-based model of the harvester is obtained assuming piezoelectric transduction and a quasi-steady flow field. The model is validated against experimental data and used to obtain a closed-form solution of the response by employing a multiple scaling perturbation analysis using the Jacobi elliptic functions. The attained solution is subsequently used to investigate the influence of the nonlinearity on the performance of the harvester and to illustrate how to optimize the restoring force in order to maximize the output power for given design conditions and airflow parameters. Specifically, it is shown that for similar design parameters and equal magnitudes of μ, and γ, a bi-stable energy harvester outperforms all other configurations as long as the inter-well motions are activated. On the other hand, if the motion of the bi-stable harvester is limited to a single well, then a harvester incorporating a softening nonlinear restoring force outperforms all other configurations. Furthermore, when comparing two FEHs incorporating the same type of restoring force at the optimal load and similar values of μ, then the FEH with the smaller γ is shown to provide higher output power levels.

  7. Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model.

    Science.gov (United States)

    Altmann, Yoann; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2013-04-01

    This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated by polynomials leading to a polynomial post-nonlinear mixing model. We have shown in a previous paper that the parameters involved in the resulting model can be estimated using least squares methods. A generalized likelihood ratio test based on the estimator of the nonlinearity parameter is proposed to decide whether a pixel of the image results from the commonly used linear mixing model or from a more general nonlinear mixing model. To compute the test statistic associated with the nonlinearity detection, we propose to approximate the variance of the estimated nonlinearity parameter by its constrained Cramér-Rao bound. The performance of the detection strategy is evaluated via simulations conducted on synthetic and real data. More precisely, synthetic data have been generated according to the standard linear mixing model and three nonlinear models from the literature. The real data investigated in this study are extracted from the Cuprite image, which shows that some minerals seem to be nonlinearly mixed in this image. Finally, it is interesting to note that the estimated abundance maps obtained with the post-nonlinear mixing model are in good agreement with results obtained in previous studies.

  8. PIZZARO: Forensic analysis and restoration of image and video data.

    Science.gov (United States)

    Kamenicky, Jan; Bartos, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozamsky, Adam; Saic, Stanislav; Sroubek, Filip; Sorel, Michal; Zita, Ales; Zitova, Barbara; Sima, Zdenek; Svarc, Petr; Horinek, Jan

    2016-07-01

    This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.

  9. Application of the Characteristic Time Expansion Method for Estimating Nonlinear Restoring Forces

    Directory of Open Access Journals (Sweden)

    Yung-Wei Chen

    2013-01-01

    Full Text Available This paper proposes a characteristic time expansion method (CTEM for estimating nonlinear restoring forces. Because noisy data and numerical instability are the main causes of numerical developing problems in an inverse field, a polynomial to identify restoring forces is usually adopted to eliminate these problems. However, results of the way doing are undesirable for a high order of polynomial. To overcome this difficulty, the characteristic length (CL is introduced into the power series, and a natural regularization technique is applied to ensure numerical stability and determine the existence of a solution. As compared to previous solutions presented in other researches, the proposed method is a desirable and accurate solver for the problem of restoring the force in the inverse vibration problems.

  10. Restoration of images possessing a finite Fourier series.

    Science.gov (United States)

    Montgomery, W D

    1982-02-01

    A standard matrix-inversion method is applied to a problem of image restoration that commonly occurs. The relation of this method to the more powerful methods using von Neumann's alternating-projection theorem or the prolate-spheroidal wave functions is indicated.

  11. Restoration algorithms for imaging through atmospheric turbulence

    Science.gov (United States)

    2017-02-18

    imaging based super-resolution algorithm, as well as our current work on the simplification of the Fried kernel for deconvolution purposes. 22...imagemagick library2) and saved as individual PNG sequences. Since the Matlab R© software is widely used by the community, we also provide each...sequence using the GIMP3 software (this procedure is summarized in Figure 2). The dynamic sequences are also provided with their respective 1https

  12. Nonlinear Deep Kernel Learning for Image Annotation.

    Science.gov (United States)

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

    Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

  13. Image Restoration Using the Damped Richardson-Lucy Iteration

    Science.gov (United States)

    White, R. L.

    The most widely used image restoration technique for optical astronomical data is the Richardson-Lucy (RL) iteration. The RL method is well-suited to optical and ultraviolet because it converges to the maximum likelihood solution for Poisson statistics in the data, which is appropriate for astronomical images taken with CCD or photon-counting detectors. Images restored using the RL iteration have good good photometric linearity and can be used for quantitative analysis, and typical RL restorations require a manageable amount of computer time. Despite its advantages, the RL method has some serious shortcomings. Noise amplification is a problem, as for all maximum likelihood techniques. If one performs many RL iterations on an image containing an extended object such as a galaxy, the extended emission develops a ``speckled'' appearance. The speckles are the result of fitting the noise in the data too closely. The only limit on the amount of noise amplification in the RL method is the requirement that the image not become negative. The usual practical approach to limiting noise amplification is simply to stop the iteration when the restored image appears to become too noisy. However, in most cases the number of iterations needed is different for different parts of the image. Hundreds of iterations may be required to get a good fit to the high signal-to-noise image of a bright star, while a smooth, extended object may be fitted well after only a few iterations. Thus, one would like to be able to slow or stop the iteration automatically in regions where a smooth model fits the data adequately, while continuing to iterate in regions where there are sharp features (edges or point sources). The need for a spatially adaptive convergence criterion is exacerbated when CCD readout noise is included in the RL algorithm (Snyder, Hammoud, & White, 1993, JOSA A , 10 , 1014), because the rate of convergence is then slower for faint stars than for bright stars. This paper will

  14. Coherent fiber supercontinuum laser for nonlinear biomedical imaging

    Science.gov (United States)

    Tu, Haohua; Liu, Yuan; Liu, Xiaomin; Lægsgaard, Jesper; Turchinovich, Dmitry; Boppart, Stephen A.

    2012-12-01

    Nonlinear biomedical imaging has not benefited from the well-known techniques of fiber supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, low spectral power intensity, and inadequate portability. Fortunately, a few techniques involving nonlinear fiber optics and femtosecond fiber laser development have emerged to overcome these critical limitations. These techniques pave the way for conducting point-of-care nonlinear biomedical imaging by a low-maintenance cost-effective coherent fiber supercontinuum laser, which covers a broad emission wavelength of 350-1700 nm. A prototype of this laser has been demonstrated in label-free multimodal nonlinear imaging of cell and tissue samples.

  15. Multi-Scale Patch-Based Image Restoration.

    Science.gov (United States)

    Papyan, Vardan; Elad, Michael

    2016-01-01

    Many image restoration algorithms in recent years are based on patch processing. The core idea is to decompose the target image into fully overlapping patches, restore each of them separately, and then merge the results by a plain averaging. This concept has been demonstrated to be highly effective, leading often times to the state-of-the-art results in denoising, inpainting, deblurring, segmentation, and other applications. While the above is indeed effective, this approach has one major flaw: the prior is imposed on intermediate (patch) results, rather than on the final outcome, and this is typically manifested by visual artifacts. The expected patch log likelihood (EPLL) method by Zoran and Weiss was conceived for addressing this very problem. Their algorithm imposes the prior on the patches of the final image, which in turn leads to an iterative restoration of diminishing effect. In this paper, we propose to further extend and improve the EPLL by considering a multi-scale prior. Our algorithm imposes the very same prior on different scale patches extracted from the target image. While all the treated patches are of the same size, their footprint in the destination image varies due to subsampling. Our scheme comes to alleviate another shortcoming existing in patch-based restoration algorithms--the fact that a local (patch-based) prior is serving as a model for a global stochastic phenomenon. We motivate the use of the multi-scale EPLL by restricting ourselves to the simple Gaussian case, comparing the aforementioned algorithms and showing a clear advantage to the proposed method. We then demonstrate our algorithm in the context of image denoising, deblurring, and super-resolution, showing an improvement in performance both visually and quantitatively.

  16. Nonlinear images of scatterers in chirped pulsed laser beams

    Institute of Scientific and Technical Information of China (English)

    Hu Yong-Hua; Wang You-Wen; Wen Shuang-Chun; Fan Dian-Yuan

    2010-01-01

    The bandwidth and the duration of incident pulsed beam are proved to play important roles in modifying the nonlinear image of amplitude-type scatterer.It is found that the initially positive chirp-type bandwidth can suppress the nonlinear image,while the negative one can enhance it,and that both effects are inversely proportional to the incident pulse duration.Numerical simulations further demonstrate that the location of nonlinear image is at the conjugate plane of the scatterer and that,for negatively pre-chirped pulsed beam,the nonlinear image peak intensity can be higher than that in the corresponding monochromatic case under certain conditions.Moreover the effect of group velocity dispersion on nonlinear image is found to be similar to that of chirp-type bandwidth.

  17. Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images.

    Science.gov (United States)

    Elad, M; Feuer, A

    1997-01-01

    The three main tools in the single image restoration theory are the maximum likelihood (ML) estimator, the maximum a posteriori probability (MAP) estimator, and the set theoretic approach using projection onto convex sets (POCS). This paper utilizes the above known tools to propose a unified methodology toward the more complicated problem of superresolution restoration. In the superresolution restoration problem, an improved resolution image is restored from several geometrically warped, blurred, noisy and downsampled measured images. The superresolution restoration problem is modeled and analyzed from the ML, the MAP, and POCS points of view, yielding a generalization of the known superresolution restoration methods. The proposed restoration approach is general but assumes explicit knowledge of the linear space- and time-variant blur, the (additive Gaussian) noise, the different measured resolutions, and the (smooth) motion characteristics. A hybrid method combining the simplicity of the ML and the incorporation of nonellipsoid constraints is presented, giving improved restoration performance, compared with the ML and the POCS approaches. The hybrid method is shown to converge to the unique optimal solution of a new definition of the optimization problem. Superresolution restoration from motionless measurements is also discussed. Simulations demonstrate the power of the proposed methodology.

  18. Multilayer Array Transducer for Nonlinear Ultrasound Imaging

    Science.gov (United States)

    Owen, Neil R.; Kaczkowski, Peter J.; Li, Tong; Gross, Dan; Postlewait, Steven M.; Curra, Francesco P.

    2011-09-01

    The properties of nonlinear acoustic wave propagation are known to be able to improve the resolution of ultrasound imaging, and could be used to dynamically estimate the physical properties of tissue. However, transducers capable of launching a wave that becomes nonlinear through propagation do not typically have the necessary bandwidth to detect the higher harmonics. Here we present the design and characterization of a novel multilayer transducer for high intensity transmit and broadband receive. The transmit layer was made from a narrow-band, high-power piezoceramic (PZT), with nominal frequency of 2.0 MHz, that was diced into an array of 32 elements. Each element was 0.300 mm wide and 6.3 mm in elevation, and with a pitch of 0.400 mm the overall aperture width was 12.7 mm. A quarter-wave matching layer was attached to the PZT substrate to improve transmit efficiency and bandwidth. The overlaid receive layer was made from polyvinylidene fluoride (PVDF) that had gold metalization on one side. A custom two-sided flex circuit routed electrical connections to the PZT elements and patterned the PVDF elements; the PZT and PVDF elements had identical apertures. A low viscosity and electrically nonconductive epoxy was used for all adhesion layers. Characterization of electrical parameters and acoustic output were performed per standard methods, where transmit and receive events were driven by a software-controlled ultrasound engine. Echo data, collected from ex vivo tissue and digitized at 45 MS/s, exhibited frequency content up to the 4th harmonic of the 2 MHz transmit frequency.

  19. Wavelet-Based Diffusion Approach for DTI Image Restoration

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiang-fen; CHEN Wu-fan; TIAN Wei-feng; YE Hong

    2008-01-01

    The Rician noise introduced into the diffusion tensor images (DTIs) can bring serious impacts on tensor calculation and fiber tracking. To decrease the effects of the Rician noise, we propose to consider the wavelet-based diffusion method to denoise multichannel typed diffusion weighted (DW) images. The presented smoothing strategy, which utilizes anisotropic nonlinear diffusion in wavelet domain, successfully removes noise while preserving both texture and edges. To evaluate quantitatively the efficiency of the presented method in accounting for the Rician noise introduced into the DW images, the peak-to-peak signal-to-noise ratio (PSNR) and signal-to-mean squared error ratio (SMSE) metrics are adopted. Based on the synthetic and real data, we calculated the apparent diffusion coefficient (ADC) and tracked the fibers. We made comparisons between the presented model,the wave shrinkage and regularized nonlinear diffusion smoothing method. All the experiment results prove quantitatively and visually the better performance of the presented filter.

  20. Nonlinear optical microscopy for imaging thin films and surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Smilowitz, L.B.; McBranch, D.W.; Robinson, J.M.

    1995-03-01

    We have used the inherent surface sensitivity of second harmonic generation to develop an instrument for nonlinear optical microscopy of surfaces and interfaces. We have demonstrated the use of several nonlinear optical responses for imaging thin films. The second harmonic response of a thin film of C{sub 60} has been used to image patterned films. Two photon absorption light induced fluorescence has been used to image patterned thin films of Rhodamine 6G. Applications of nonlinear optical microscopy include the imaging of charge injection and photoinduced charge transfer between layers in semiconductor heterojunction devices as well as across membranes in biological systems.

  1. Image Restoration Phase-Filtering Lateral Superresolution Confocal Microscopy

    Institute of Scientific and Technical Information of China (English)

    ZHAO Wei-Qian; QIU Li-Rong; CHEN Shan-Shan; FENG Zheng-De

    2006-01-01

    @@ Image restoration phase-filtering lateral superresolution confocal microscopy, a new approach, is proposed to achieve lateral superresolution using a confocal microscope. This approach uses a lateral superresolution pupil filter to preliminarily improve its lateral resolution and uses a single-image superresolution restoration technique based on a maximum likelihood estimate to further improve its lateral resolution. The new approach has the advantages of a low cost and the remarkable superresolution effect without excessive system complexity. Experiments indicate that the proposed approach can improve the lateral resolution of a confocal microscope from 0.3μm to less than 0.1 μm when λ = 632.8 nm and NA =0.85.

  2. Nonlinear spectral unmixing of hyperspectral images using Gaussian processes

    CERN Document Server

    Altmann, Yoann; McLaughlin, Steve; Tourneret, Jean-Yves

    2012-01-01

    This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components. We assume that the spectral signatures of the pure components and the nonlinear function are unknown. The first step of the proposed method consists of the Bayesian estimation of the abundance vectors for all the image pixels and the nonlinear function relating the abundance vectors to the observations. The endmembers are subsequently estimated using Gaussian process regression. The performance of the unmixing strategy is evaluated with simulations conducted on synthetic and real data.

  3. A new trust region algorithm for image restoration

    Institute of Scientific and Technical Information of China (English)

    WEN Zaiwen; WANG Yanfei

    2005-01-01

    The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter α. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious finding the regularization parameters and truncation levels. Some numerical tests on remotely sensed images are given to show that the trust region method is promising.

  4. Bifurcations and chaotic threshold for a nonlinear system with an irrational restoring force

    Institute of Scientific and Technical Information of China (English)

    Tian Rui-Lan; Yang Xin-Wei; Cao Qing-Jie; Wu Qi-Liang

    2012-01-01

    Nonlinear dynamical systems with an irrational restoring force often occur in both science and engineering,and always lead to a barrier for conventional nonlinear techniques.In this paper,we have investigated the global bifurcations and the chaos directly for a nonlinear system with irrational nonlinearity avoiding the conventional Taylor's expansion to retain the natural characteristics of the system.A series of transformations are proposed to convert the homoclinic orbits of the unperturbed system to the heteroclinic orbits in the new coordinate,which can be transformed back to the analytical expressions of the homoclinic orbits.Melnikov's method is employed to obtain the criteria for chaotic motion,which implies that the existence of homoclinic orbits to chaos arose from the breaking of homoclinic orbits under the perturbation of damping and external forcing.The efficiency of the criteria for chaotic motion obtained in this paper is verified via bifurcation diagrams,Lyapunov exponents,and numerical simulations.It is worthwhile noting that our study is an attempt to make a step toward the solution of the problem proposed by Cao Q Jet al.(Cao Q J,Wiercigroch M,Pavlovskaia E E,Thompson J M T and Grebogi C 2008 Phil.Trans.R.Soc.A 366 635).

  5. Bifurcations and chaotic threshold for a nonlinear system with an irrational restoring force

    Science.gov (United States)

    Tian, Rui-Lan; Yang, Xin-Wei; Cao, Qing-Jie; Wu, Qi-Liang

    2012-02-01

    Nonlinear dynamical systems with an irrational restoring force often occur in both science and engineering, and always lead to a barrier for conventional nonlinear techniques. In this paper, we have investigated the global bifurcations and the chaos directly for a nonlinear system with irrational nonlinearity avoiding the conventional Taylor's expansion to retain the natural characteristics of the system. A series of transformations are proposed to convert the homoclinic orbits of the unperturbed system to the heteroclinic orbits in the new coordinate, which can be transformed back to the analytical expressions of the homoclinic orbits. Melnikov's method is employed to obtain the criteria for chaotic motion, which implies that the existence of homoclinic orbits to chaos arose from the breaking of homoclinic orbits under the perturbation of damping and external forcing. The efficiency of the criteria for chaotic motion obtained in this paper is verified via bifurcation diagrams, Lyapunov exponents, and numerical simulations. It is worthwhile noting that our study is an attempt to make a step toward the solution of the problem proposed by Cao Q J et al. (Cao Q J, Wiercigroch M, Pavlovskaia E E, Thompson J M T and Grebogi C 2008 Phil. Trans. R. Soc. A 366 635).

  6. Peplography: an image restoration technique through scattering media

    Science.gov (United States)

    Cho, Myungjin; Cho, Ki-Ok; Kim, Youngjun

    2016-06-01

    In this paper, we propose an image restoration technique through scattering media. Under natural light an imaging through scattering media is a big challenge in many applications. To overcome this challenge, many methods have been reported such as non-invasive imaging, ghost imaging, and wavefront shaping. However, their results have not been sufficient for observers. In this paper, we estimate the scattering media by statistical estimation such as maximum likelihood estimation. By removing this estimated scattering media from the original image, we can obtain the image with only ballistic photons. Then, the ballistic photons can be detected by photon counting imaging concept. In addition, since each basic color channel has its own wavelength, color photon counting process can be implemented. To enhance the visual quality of the result image, a passive three-dimensional (3D) imaging technique such as integral imaging is used. To prove our method and show the better performance, we carried out optical experiments and calculate mean square error (MSE).

  7. Group-based sparse representation for image restoration.

    Science.gov (United States)

    Zhang, Jian; Zhao, Debin; Gao, Wen

    2014-08-01

    Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception.

  8. Efficient cultural heritage image restoration with nonuniform illumination enhancement

    Science.gov (United States)

    Jmal, Marwa; Souidene, Wided; Attia, Rabah

    2017-01-01

    Cultural heritage digitization has been of research interest for several decades. For such, the quality of the stored images should be pleasant to see. However, as images captured by digital devices may include undesirable effects, conducting an enhancement on the image is essential. In this context, we present a framework for the purpose of cultural heritage image illumination enhancement. First, a mapping curve based on saturation feedback is created to adjust the contrast. Then illumination is enhanced by applying a modified homomorphic filter in the frequency domain. The technique employs an optimization search process based on the efficient golden section search algorithm to compute the optimal parameters to produce the enhanced image. Finally, a color restoration function is applied to overcome the problem of color violation. The resulted image represents a trade-off among local contrast improvement, detail enhancement, and preserving the naturalness of the image. Experiments are conducted on a collected dataset of cultural heritage images and compared to some of the state-of-the-art image enhancement methods using a set of quantitative assessments criteria. Results have shown that our proposed approach is able to accomplish a wide set of the performance goals.

  9. A Nonlinear Restoring Effect Study of Mooring System and its Application

    Institute of Scientific and Technical Information of China (English)

    Jian Zhang; Huilong Ren; Lijie Zhang

    2012-01-01

    Mooring system plays an important role in station keeping of floating offshore structures.Coupled analysis on mooring-buoy interactions has been increasingly studied in recent years.At present,chains and wire ropes are widely used in offshore engineering practice.On the basis of mooring line statics,an explicit formulation of single mooring chain/wire rope stiffness coefficients and mooring stiffness matrix of the mooring system were derived in this article,taking into account the horizontal restoring force,vertical restoring force and their coupling terms.The nonlinearity of mooring stiffness was analyzed,and the influences of various parameters,such as material,displacement,pre-tension and water depth,were investigated.Finally some application cases of the mooring stiffness in hydrodynamic calculation were presented.Data shows that this kind of stiffness can reckon in linear and nonlinear forces of mooring system.Also,the stiffness can be used in hydrodynamic analysis to get the eigenfrequency of slow drift motions.

  10. Image Restoration Using Functional and Anatomical Information Fusion with Application to SPECT-MRI Images

    Directory of Open Access Journals (Sweden)

    S. Benameur

    2009-01-01

    Full Text Available Image restoration is usually viewed as an ill-posed problem in image processing, since there is no unique solution associated with it. The quality of restored image closely depends on the constraints imposed of the characteristics of the solution. In this paper, we propose an original extension of the NAS-RIF restoration technique by using information fusion as prior information with application in SPECT medical imaging. That extension allows the restoration process to be constrained by efficiently incorporating, within the NAS-RIF method, a regularization term which stabilizes the inverse solution. Our restoration method is constrained by anatomical information extracted from a high resolution anatomical procedure such as magnetic resonance imaging (MRI. This structural anatomy-based regularization term uses the result of an unsupervised Markovian segmentation obtained after a preliminary registration step between the MRI and SPECT data volumes from each patient. This method was successfully tested on 30 pairs of brain MRI and SPECT acquisitions from different subjects and on Hoffman and Jaszczak SPECT phantoms. The experiments demonstrated that the method performs better, in terms of signal-to-noise ratio, than a classical supervised restoration approach using a Metz filter.

  11. Image restoration for indirectly far-field image using microlenses array integrated with LCD

    Science.gov (United States)

    Yang, Fugui; Wang, Anting; Lei, Dong; Zhe, Cui; Ming, Hai

    2010-10-01

    Image restoration for constructing high-spatial-resolution images in an imaging system which realizes indirectly far-filed imaging by integrating the microlenses array with LCD is reported. We have investigated the indirectly far-field imaging condition where adjacent sampling points contribute the detected signal. Experimental setup with microlens of 500 μm diameter and 8 mm focal length is built to prove this condition by studying performance of image restoration using modified point spread function (PSF). Since any one iterative method is not optimal for all image deblurring problems, some deblurring algorithms including direct deconvolution and iterative deconvolution are applied to our imaging system and we compared the effectiveness of these iterative procedures to choose right one for our use.

  12. Spatially Adaptive Image Restoration Using Fuzzy Punctual Kriging

    Institute of Scientific and Technical Information of China (English)

    Anwar M. Mirza; Asmatullah Chaudhry; Badre Munir

    2007-01-01

    We present a general formulation based on punctual kriging and fuzzy concepts for image restoration in spatial domain. Gray-level images degraded with Gaussian white noise have been considered. Based on the pixel local neighborhood, fuzzy logic has been employed intelligently to avoid unnecessary estimation of a pixel. The intensity estimation of the selected pixels is then carried out by employing punctual kriging in conjunction with the method of Lagrange multipliers and estimates of local semi-variances. Application of such a hybrid technique performing both selection and intensity estimation of a pixel demonstrates substantial improvement in the image quality as compared to the adaptive Wiener filter and existing fuzzy- kriging approaches. It has been found that these filters achieve noise reduction without loss of structural detail information, as indicated by their higher structure similarity indices, peak signal to noise ratios and the new variogram based quality measures.

  13. Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

    KAUST Repository

    Desmal, Abdulla

    2015-04-13

    A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

  14. Image mathematical morphology and image restoration application in detecting underground bin level

    Institute of Scientific and Technical Information of China (English)

    SUN Ji-ping; WU Bing

    2004-01-01

    By using image recognition technology, the underground bin level can be detdcted. The bin image is noised by vibration, atomy, backgroun and so on. The image restoration and image mathematical morphology were used based on neural network.A modified Hopfield network was presented for image restoration. The greed algorithm with n-simultaneous updates and apartially asynchronous algorithm were combined, improving convergence and avoiding synchronization penalties. Mathematical morphology was widely applicated in digital image processing. The basic idea of mathematical morphology is to use construction element measure image morphology for solving understand problem. Presented advanced Cellular neural network that forms MMCNN equation to be suit for mathematical morphology filter. It gave the theory of MMCNN dynamic extent and stable state. It was evidenced that arrived mathematical morphology filter through steady of dynamic precess in definite condition. The results of implementation were applied in detecting undergroug bin level.

  15. Image Restoration and Denoising By Using Nonlocally Centralized Sparse Representation and Histogram Clipping

    Directory of Open Access Journals (Sweden)

    Dr. T. V. S. Prasad Gupta

    2014-10-01

    Full Text Available Due to the degradation of observed image the noisy, blurred, Distorted image can be occurred .for restoring image information we propose the sparse representations by conventional modelsmay not be accurate enough for a faithful reconstruction of the original image. To improve the performance of sparse representation-based image restoration,In this method the sparse coding noise is added for image restoration, due to this image restoration the sparse coefficients of original image can be detected. The so-called nonlocally centralized sparse representation (NCSR model is as simple as the standard sparse representation model,for denoising the image here we use the Histogram clipping method by using histogram based sparse representation effectively reduce the noise.and also implement the TMR filter for Quality image.various types of image restoration problems, including denoising, deblurring and super-resolution, validate the generality and state-of-the-art performance of the proposed algorithm.

  16. SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS

    KAUST Repository

    Desmal, Abdulla

    2015-07-29

    A scheme for efficiently solving the nonlinear electromagnetic inverse scattering problem on sparse investigation domains is described. The proposed scheme reconstructs the (complex) dielectric permittivity of an investigation domain from fields measured away from the domain itself. Least-squares data misfit between the computed scattered fields, which are expressed as a nonlinear function of the permittivity, and the measured fields is constrained by the L0/L1-norm of the solution. The resulting minimization problem is solved using nonlinear Landweber iterations, where at each iteration a thresholding function is applied to enforce the sparseness-promoting L0/L1-norm constraint. The thresholded nonlinear Landweber iterations are applied to several two-dimensional problems, where the ``measured\\'\\' fields are synthetically generated or obtained from actual experiments. These numerical experiments demonstrate the accuracy, efficiency, and applicability of the proposed scheme in reconstructing sparse profiles with high permittivity values.

  17. Nonlinear plasmonic imaging techniques and their biological applications

    Science.gov (United States)

    Deka, Gitanjal; Sun, Chi-Kuang; Fujita, Katsumasa; Chu, Shi-Wei

    2017-01-01

    Nonlinear optics, when combined with microscopy, is known to provide advantages including novel contrast, deep tissue observation, and minimal invasiveness. In addition, special nonlinearities, such as switch on/off and saturation, can enhance the spatial resolution below the diffraction limit, revolutionizing the field of optical microscopy. These nonlinear imaging techniques are extremely useful for biological studies on various scales from molecules to cells to tissues. Nevertheless, in most cases, nonlinear optical interaction requires strong illumination, typically at least gigawatts per square centimeter intensity. Such strong illumination can cause significant phototoxicity or even photodamage to fragile biological samples. Therefore, it is highly desirable to find mechanisms that allow the reduction of illumination intensity. Surface plasmon, which is the collective oscillation of electrons in metal under light excitation, is capable of significantly enhancing the local field around the metal nanostructures and thus boosting up the efficiency of nonlinear optical interactions of the surrounding materials or of the metal itself. In this mini-review, we discuss the recent progress of plasmonics in nonlinear optical microscopy with a special focus on biological applications. The advancement of nonlinear imaging modalities (including incoherent/coherent Raman scattering, two/three-photon luminescence, and second/third harmonic generations that have been amalgamated with plasmonics), as well as the novel subdiffraction limit imaging techniques based on nonlinear behaviors of plasmonic scattering, is addressed.

  18. Nonlinear plasmonic imaging techniques and their biological applications

    Directory of Open Access Journals (Sweden)

    Deka Gitanjal

    2016-07-01

    Full Text Available Nonlinear optics, when combined with microscopy, is known to provide advantages including novel contrast, deep tissue observation, and minimal invasiveness. In addition, special nonlinearities, such as switch on/off and saturation, can enhance the spatial resolution below the diffraction limit, revolutionizing the field of optical microscopy. These nonlinear imaging techniques are extremely useful for biological studies on various scales from molecules to cells to tissues. Nevertheless, in most cases, nonlinear optical interaction requires strong illumination, typically at least gigawatts per square centimeter intensity. Such strong illumination can cause significant phototoxicity or even photodamage to fragile biological samples. Therefore, it is highly desirable to find mechanisms that allow the reduction of illumination intensity. Surface plasmon, which is the collective oscillation of electrons in metal under light excitation, is capable of significantly enhancing the local field around the metal nanostructures and thus boosting up the efficiency of nonlinear optical interactions of the surrounding materials or of the metal itself. In this mini-review, we discuss the recent progress of plasmonics in nonlinear optical microscopy with a special focus on biological applications. The advancement of nonlinear imaging modalities (including incoherent/coherent Raman scattering, two/three-photon luminescence, and second/third harmonic generations that have been amalgamated with plasmonics, as well as the novel subdiffraction limit imaging techniques based on nonlinear behaviors of plasmonic scattering, is addressed.

  19. Test images for the maximum entropy image restoration method

    Science.gov (United States)

    Mackey, James E.

    1990-01-01

    One of the major activities of any experimentalist is data analysis and reduction. In solar physics, remote observations are made of the sun in a variety of wavelengths and circumstances. In no case is the data collected free from the influence of the design and operation of the data gathering instrument as well as the ever present problem of noise. The presence of significant noise invalidates the simple inversion procedure regardless of the range of known correlation functions. The Maximum Entropy Method (MEM) attempts to perform this inversion by making minimal assumptions about the data. To provide a means of testing the MEM and characterizing its sensitivity to noise, choice of point spread function, type of data, etc., one would like to have test images of known characteristics that can represent the type of data being analyzed. A means of reconstructing these images is presented.

  20. Nonlinear Image Restoration in Confocal Microscopy : Stability under Noise

    NARCIS (Netherlands)

    Roerdink, J.B.T.M.

    1995-01-01

    In this paper we study the noise stability of iterative algorithms developed for attenuation correction in Fluorescence Confocal Microscopy using FT methods. In each iteration the convolution of the previous estimate is computed. It turns out that the estimators are robust to noise perturbation.

  1. Nonlinear Image Restoration in Confocal Microscopy : Stability under Noise

    NARCIS (Netherlands)

    Roerdink, J.B.T.M.

    1995-01-01

    In this paper we study the noise stability of iterative algorithms developed for attenuation correction in Fluorescence Confocal Microscopy using FT methods. In each iteration the convolution of the previous estimate is computed. It turns out that the estimators are robust to noise perturbation.

  2. A Stochastic Approach for Blurred Image Restoration and Optical Flow Computation on Field Image Sequence

    Institute of Scientific and Technical Information of China (English)

    高文; 陈熙霖

    1997-01-01

    The blur in target images caused by camera vibration due to robot motion or hand shaking and by object(s) moving in the background scene is different to deal with in the computer vision system.In this paper,the authors study the relation model between motion and blur in the case of object motion existing in video image sequence,and work on a practical computation algorithm for both motion analysis and blut image restoration.Combining the general optical flow and stochastic process,the paper presents and approach by which the motion velocity can be calculated from blurred images.On the other hand,the blurred image can also be restored using the obtained motion information.For solving a problem with small motion limitation on the general optical flow computation,a multiresolution optical flow algoritm based on MAP estimation is proposed. For restoring the blurred image ,an iteration algorithm and the obtained motion velocity are used.The experiment shows that the proposed approach for both motion velocity computation and blurred image restoration works well.

  3. Fast approach to infrared image restoration based on shrinkage functions calibration

    Science.gov (United States)

    Zhang, Chengshuo; Shi, Zelin; Xu, Baoshu; Feng, Bin

    2016-05-01

    High-quality image restoration in real time is a challenge for infrared imaging systems. We present a fast approach to infrared image restoration based on shrinkage functions calibration. Rather than directly modeling the prior of sharp images to obtain the shrinkage functions, we calibrate them for restoration directly by using the acquirable sharp and blurred image pairs from the same infrared imaging system. The calibration method is employed to minimize the sum of squared errors between sharp images and restored images from the blurred images. Our restoration algorithm is noniterative and its shrinkage functions are stored in the look-up tables, so an architecture solution of pipeline structure can work in real time. We demonstrate the effectiveness of our approach by testing its quantitative performance from simulation experiments and its qualitative performance from a developed wavefront coding infrared imaging system.

  4. Accurate approximate solution to nonlinear oscillators in which the restoring force is inversely proportional to the dependent variable

    Energy Technology Data Exchange (ETDEWEB)

    Belendez, A; Gimeno, E; Mendez, D I; Alvarez, M L [Departamento de Fisica, IngenierIa de Sistemas y TeorIa de la Senal, Universidad de Alicante, Apartado 99, E-03080 Alicante (Spain); Fernandez, E [Departamento de Optica, FarmacologIa y AnatomIa, Universidad de Alicante, Apartado 99, E-03080 Alicante (Spain)], E-mail: a.belendez@ua.es

    2008-06-15

    A modified generalized, rational harmonic balance method is used to construct approximate frequency-amplitude relations for a conservative nonlinear singular oscillator in which the restoring force is inversely proportional to the dependent variable. The procedure is used to solve the nonlinear differential equation approximately. The approximate frequency obtained using this procedure is more accurate than those obtained using other approximate methods and the discrepancy between the approximate frequency and the exact one is lower than 0.40%.

  5. Nonlinear unmixing of hyperspectral images: models and algorithms

    CERN Document Server

    Dobigeon, Nicolas; Richard, Cédric; Bermudez, José C M; McLaughlin, Stephen; Hero, Alfred O

    2013-01-01

    When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas rely on the widely acknowledged linear mixing model (LMM). However, in specific but common contexts, the LMM may be not valid and other nonlinear models should be invoked. Consequently, over the last few years, several significant contributions have been proposed to overcome the limitations inherent in the LMM. In this paper, we present an overview of recent advances that deal with the nonlinear unmixing problem. The main nonlinear models are introduced and their validity discussed. Then, we describe the main classes of unmixing strategies designed to solve the problem in supervised and unsupervised frameworks. Finally, the problem of detecting nonlinear mixtures in hyperspectral images is addressed.

  6. Coherent fiber supercontinuum laser for nonlinear biomedical imaging

    DEFF Research Database (Denmark)

    Tu, Haohua; Liu, Yuan; Liu, Xiaomin;

    2012-01-01

    Nonlinear biomedical imaging has not benefited from the well-known techniques of fiber supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, low spectral power intensity, and inadequate portability. Fortunately, a few techniques involving...... nonlinear fiber optics and femtosecond fiber laser development have emerged to overcome these critical limitations. These techniques pave the way for conducting point-of-care nonlinear biomedical imaging by a low-maintenance cost-effective coherent fiber supercontinuum laser, which covers a broad emission...... wavelength of 350-1700 nm. A prototype of this laser has been demonstrated in label-free multimodal nonlinear imaging of cell and tissue samples.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only....

  7. A new reliable analytical solution for strongly nonlinear oscillator with cubic and harmonic restoring force

    Directory of Open Access Journals (Sweden)

    Md. Alal Hosen

    2015-01-01

    Full Text Available In the present paper, a complicated strongly nonlinear oscillator with cubic and harmonic restoring force, has been analysed and solved completely by harmonic balance method (HBM. Investigating analytically such kinds of oscillator is very difficult task and cumbersome. In this study, the offered technique gives desired results and to avoid numerical complexity. An excellent agreement was found between approximate and numerical solutions, which prove that HBM is very efficient and produces high accuracy results. It is remarkably important that, second-order approximate results are almost same with exact solutions. The advantage of this method is its simple procedure and applicable for many other oscillatory problems arising in science and engineering.

  8. Image restoration based on the discrete fraction Fourier transform

    Science.gov (United States)

    Yan, Peimin; Mo, Yu L.; Liu, Hong

    2001-09-01

    The fractional Fourier transform is the powerful tool for time-variant signal analysis. For space-variant degradation and non-stationary processes the filtering in fractional Fourier domains permits reduction of the error compared with ordinary Fourier domain filtering. In this paper the concept of filtering in fractional Fourier domains is applied to the problem of estimating degraded images. Efficient digital implementation using discrete Hermite eigenvectors can provide similar results to match the continuous outputs. Expressions for the 2D optimal filter function in fractional domains will be given for transform domains characterized by the two rotation angle parameters of the 2D fractional Fourier transform. The proposed method is used to restore images that have several degradations in the experiments. The results show that the method presented in this paper is valid.

  9. Accelerated edge-preserving image restoration without boundary artifacts.

    Science.gov (United States)

    Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A

    2013-05-01

    To reduce blur in noisy images, regularized image restoration methods have been proposed that use nonquadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a noncirculant model could prevent these artifacts at the cost of increased computational complexity. In this paper, we propose to use a circulant blur model combined with a masking operator that prevents wraparound artifacts. The resulting model is noncirculant, so we propose an efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies. Our variable splitting scheme, when combined with the AL framework and alternating minimization, leads to simple linear systems that can be solved noniteratively using fast Fourier transforms (FFTs), eliminating the need for more expensive conjugate gradient-type solvers. The proposed method can also efficiently tackle a variety of convex regularizers, including edge-preserving (e.g., total-variation) and sparsity promoting (e.g., l1-norm) regularizers. Simulation results show fast convergence of the proposed method, along with improved image quality at the boundaries where the circulant model is inaccurate.

  10. Accelerated Edge-Preserving Image Restoration Without Boundary Artifacts

    Science.gov (United States)

    Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A.

    2013-01-01

    To reduce blur in noisy images, regularized image restoration methods have been proposed that use non-quadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a non-circulant model could prevent these artifacts at the cost of increased computational complexity. In this work we propose to use a circulant blur model combined with a masking operator that prevents wraparound artifacts. The resulting model is non-circulant, so we propose an efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies. Our variable splitting scheme, when combined with the AL framework and alternating minimization, leads to simple linear systems that can be solved non-iteratively using FFTs, eliminating the need for more expensive CG-type solvers. The proposed method can also efficiently tackle a variety of convex regularizers including edge-preserving (e.g., total-variation) and sparsity promoting (e.g., l1 norm) regularizers. Simulation results show fast convergence of the proposed method, along with improved image quality at the boundaries where the circulant model is inaccurate. PMID:23372080

  11. In vivo multimodal nonlinear optical imaging of mucosal tissue

    Science.gov (United States)

    Sun, Ju; Shilagard, Tuya; Bell, Brent; Motamedi, Massoud; Vargas, Gracie

    2004-05-01

    We present a multimodal nonlinear imaging approach to elucidate microstructures and spectroscopic features of oral mucosa and submucosa in vivo. The hamster buccal pouch was imaged using 3-D high resolution multiphoton and second harmonic generation microscopy. The multimodal imaging approach enables colocalization and differentiation of prominent known spectroscopic and structural features such as keratin, epithelial cells, and submucosal collagen at various depths in tissue. Visualization of cellular morphology and epithelial thickness are in excellent agreement with histological observations. These results suggest that multimodal nonlinear optical microscopy can be an effective tool for studying the physiology and pathology of mucosal tissue.

  12. Hierarchical Non-linear Image Registration Integrating Deformable Segmentation

    Institute of Scientific and Technical Information of China (English)

    RAN Xin; QI Fei-hu

    2005-01-01

    A hierarchical non-linear method for image registration was presented, which integrates image segmentation and registration under a variational framework. An improved deformable model is used to simultaneously segment and register feature from multiple images. The objects in the image pair are segmented by evolving a single contour and meanwhile the parameters of affine registration transformation are found out. After that, a contour-constrained elastic registration is applied to register the images correctly. The experimental results indicate that the proposed approach is effective to segment and register medical images.

  13. Extraction and restoration of hippocampal spatial memories with nonlinear dynamical modeling

    Directory of Open Access Journals (Sweden)

    Dong eSong

    2014-05-01

    Full Text Available To build a cognitive prosthesis that can replace the memory function of the hippocampus, it is essential to model the input-output function of the damaged hippocampal region, so the prosthetic device can stimulate the downstream hippocampal region, e.g., CA1, with the output signal, e.g., CA1 spike trains, predicted from the ongoing input signal, e.g., CA3 spike trains, and the identified input-output function, e.g., CA3-CA1 model. In order for the downstream region to form appropriate long-term memories based on the restored output signal, furthermore, the output signal should contain sufficient information about the memories that the animal has formed. In this study, we verify this premise by applying regression and classification modelings of the spatio-temporal patterns of spike trains to the hippocampal CA3 and CA1 data recorded from rats performing a memory-dependent delayed nonmatch-to-sample (DNMS task. The regression model is essentially the multiple-input, multiple-output (MIMO nonlinear dynamical model of spike train transformation. It predicts the output spike trains based on the input spike trains and thus restores the output signal. In addition, the classification model interprets the signal by relating the spatio-temporal patterns to the memory events. We have found that: (1 both hippocampal CA3 and CA1 spike trains contain sufficient information for predicting the locations of the sample responses (i.e., left and right memories during the DNMS task; and more importantly (2 the CA1 spike trains predicted from the CA3 spike trains by the MIMO model also are sufficient for predicting the locations on a single-trial basis. These results show quantitatively that, with a moderate number of unitary recordings from the hippocampus, the MIMO nonlinear dynamical model is able to extract and restore spatial memory information for the formation of long-term memories and thus can serve as the computational basis of the hippocampal memory

  14. Extraction and restoration of hippocampal spatial memories with non-linear dynamical modeling.

    Science.gov (United States)

    Song, Dong; Harway, Madhuri; Marmarelis, Vasilis Z; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W

    2014-01-01

    To build a cognitive prosthesis that can replace the memory function of the hippocampus, it is essential to model the input-output function of the damaged hippocampal region, so the prosthetic device can stimulate the downstream hippocampal region, e.g., CA1, with the output signal, e.g., CA1 spike trains, predicted from the ongoing input signal, e.g., CA3 spike trains, and the identified input-output function, e.g., CA3-CA1 model. In order for the downstream region to form appropriate long-term memories based on the restored output signal, furthermore, the output signal should contain sufficient information about the memories that the animal has formed. In this study, we verify this premise by applying regression and classification modelings of the spatio-temporal patterns of spike trains to the hippocampal CA3 and CA1 data recorded from rats performing a memory-dependent delayed non-match-to-sample (DNMS) task. The regression model is essentially the multiple-input, multiple-output (MIMO) non-linear dynamical model of spike train transformation. It predicts the output spike trains based on the input spike trains and thus restores the output signal. In addition, the classification model interprets the signal by relating the spatio-temporal patterns to the memory events. We have found that: (1) both hippocampal CA3 and CA1 spike trains contain sufficient information for predicting the locations of the sample responses (i.e., left and right memories) during the DNMS task; and more importantly (2) the CA1 spike trains predicted from the CA3 spike trains by the MIMO model also are sufficient for predicting the locations on a single-trial basis. These results show quantitatively that, with a moderate number of unitary recordings from the hippocampus, the MIMO non-linear dynamical model is able to extract and restore spatial memory information for the formation of long-term memories and thus can serve as the computational basis of the hippocampal memory prosthesis.

  15. Nonlinear Second-Order Partial Differential Equation-Based Image Smoothing Technique

    Directory of Open Access Journals (Sweden)

    Tudor Barbu

    2016-09-01

    Full Text Available A second-order nonlinear parabolic PDE-based restoration model is provided in this article. The proposed anisotropic diffusion-based denoising approach is based on some robust versions of the edge-stopping function and of the conductance parameter. Two stable and consistent approximation schemes are then developed for this differential model. Our PDE-based filtering technique achieves an efficient noise removal while preserving the edges and other image features. It outperforms both the conventional filters and also many PDE-based denoising approaches, as it results from the successful experiments and method comparison applied.

  16. Multimodal nonlinear imaging of arabidopsis thaliana root cell

    Science.gov (United States)

    Jang, Bumjoon; Lee, Sung-Ho; Woo, Sooah; Park, Jong-Hyun; Lee, Myeong Min; Park, Seung-Han

    2017-07-01

    Nonlinear optical microscopy has enabled the possibility to explore inside the living organisms. It utilizes ultrashort laser pulse with long wavelength (greater than 800nm). Ultrashort pulse produces high peak power to induce nonlinear optical phenomenon such as two-photon excitation fluorescence (TPEF) and harmonic generations in the medium while maintaining relatively low average energy pre area. In plant developmental biology, confocal microscopy is widely used in plant cell imaging after the development of biological fluorescence labels in mid-1990s. However, fluorescence labeling itself affects the sample and the sample deviates from intact condition especially when labelling the entire cell. In this work, we report the dynamic images of Arabidopsis thaliana root cells. This demonstrates the multimodal nonlinear optical microscopy is an effective tool for long-term plant cell imaging.

  17. Fruit fly optimization based least square support vector regression for blind image restoration

    Science.gov (United States)

    Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

    2014-11-01

    The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and

  18. Dictionary construction in sparse methods for image restoration

    Energy Technology Data Exchange (ETDEWEB)

    Wohlberg, Brendt [Los Alamos National Laboratory

    2010-01-01

    Sparsity-based methods have achieved very good performance in a wide variety of image restoration problems, including denoising, inpainting, super-resolution, and source separation. These methods are based on the assumption that the image to be reconstructed may be represented as a superposition of a few known components, and the appropriate linear combination of components is estimated by solving an optimization such as Basis Pursuit De-Noising (BPDN). Considering that the K-SVD constructs a dictionary which has been optimised for mean performance over a training set, it is not too surprising that better performance can be achieved by selecting a custom dictionary for each individual block to be reconstructed. The nearest neighbor dictionary construction can be understood geometrically as a method for estimating the local projection into the manifold of image blocks, whereas the K-SVD dictionary makes more sense within a source-coding framework (it is presented as a generalization of the k-means algorithm for constructing a VQ codebook), is therefore, it could be argued, less appropriate in principle, for reconstruction problems. One can, of course, motivate the use of the K-SVD in reconstruction application on practical grounds, avoiding the computational expense of constructing a different dictionary for each block to be denoised. Since the performance of the nearest neighbor dictionary decreases when the dictionary becomes sufficiently large, this method is also superior to the approach of utilizing the entire training set as a dictionary (and this can also be understood within the image block manifold model). In practical terms, the tradeoff is between the computational cost of a nearest neighbor search (which can be achieved very efficiently), or of increased cost at the sparse optimization.

  19. Nonlinear approximation of image based on monoscale orthonormal ridgelets frame

    Institute of Scientific and Technical Information of China (English)

    Lu Chengwu; Song Yimei; Song Guoxiang

    2007-01-01

    A new tight frame called as monoscale orthonormal ridgelet frame (MORF) is proposed. The localization principle and the orthonormal ridgelet constructed by Donoho are applied to construct the MORF, which are used to evaluate the order of nonlinear approximation for image with edge. Because the new tight frame not only has directionality but also bears orthonormality. It overcomes redundancy of Candes's monoscale ridgelets and provides many excellent properties in practical application. Theoretical analysis and experiments demonstrate that the new frame has remarkable potential for image compression, image reconstruction, and image denoising with the simple refinement for MORF.

  20. Investigation on the formation of intense fringe near nonlinear medium slab in nonlinear imaging

    Science.gov (United States)

    Hu, Yonghua; Qiu, Yaqiong; Peng, Xue

    2016-11-01

    It is well known that hot images of small-scale scatterers can be formed. For phase-typed scatterers, hot image and second-order hot-image can be formed. However, when the number of scatterer is larger than one, the interaction between the scatterered waves will lead to new nonlinear propagation results. In this paper, the propagation of flat-topped intense laser beam through Kerr medium slab is investigated, with the incident beam modulated by two parallel wirelike phase-typed scatterers. We demonstrate that an intense fringe together with hot image and second-order hot image can be formed when the distance of the two scatterers is several millimeters. It is found that the on-axis position of the plane of this intense fringe is in the middle part between the exit surface of the Kerr medium slab and the secondorder hot image plane. This intense fringe shows the following basic properties: Firstly, its intensity is apparently higher than that of corresponding second-order hot image and can be comparable with that of corresponding hot image; Secondly, the distances between it and the in-beam positions of the scatterers are identical. The intensity profile shows that this intense fringe is the only prominent bright fringe in the corresponding plane, and thus it is not a nonlinear image of any scatterer. Besides, the influences of the properties of scatterer on the intensity of the fringe are discussed.

  1. Imaging of discontinuities in nonlinear 3-D seismic inversion

    Energy Technology Data Exchange (ETDEWEB)

    Carrion, P.M.; Cerveny, V. (PPPG/UFBA, Salvador (Brazil))

    1990-09-01

    The authors present a nonlinear approach for reconstruction of discontinuities in geological environment (earth's crust, say). The advantage of the proposed method is that it is not limited to a Born approximation (small angles of propagation and weak scatterers). One can expect significantly better images since larger apertures including wide angle reflection arrivals can be incorporated into the imaging operator. In this paper, they treat only compressional body waves: shear and surface waves are considered as noise.

  2. Multi-crack imaging using nonclassical nonlinear acoustic method

    Science.gov (United States)

    Zhang, Lue; Zhang, Ying; Liu, Xiao-Zhou; Gong, Xiu-Fen

    2014-10-01

    Solid materials with cracks exhibit the nonclassical nonlinear acoustical behavior. The micro-defects in solid materials can be detected by nonlinear elastic wave spectroscopy (NEWS) method with a time-reversal (TR) mirror. While defects lie in viscoelastic solid material with different distances from one another, the nonlinear and hysteretic stress—strain relation is established with Preisach—Mayergoyz (PM) model in crack zone. Pulse inversion (PI) and TR methods are used in numerical simulation and defect locations can be determined from images obtained by the maximum value. Since false-positive defects might appear and degrade the imaging when the defects are located quite closely, the maximum value imaging with a time window is introduced to analyze how defects affect each other and how the fake one occurs. Furthermore, NEWS-TR-NEWS method is put forward to improve NEWS-TR scheme, with another forward propagation (NEWS) added to the existing phases (NEWS and TR). In the added phase, scanner locations are determined by locations of all defects imaged in previous phases, so that whether an imaged defect is real can be deduced. NEWS-TR-NEWS method is proved to be effective to distinguish real defects from the false-positive ones. Moreover, it is also helpful to detect the crack that is weaker than others during imaging procedure.

  3. Dual-frequency transducer for nonlinear contrast agent imaging.

    Science.gov (United States)

    Guiroy, Axel; Novell, Anthony; Ringgaard, Erling; Lou-Moeller, Rasmus; Grégoire, Jean-Marc; Abellard, André-Pierre; Zawada, Tomasz; Bouakaz, Ayache; Levassort, Franck

    2013-12-01

    Detection of high-order nonlinear components issued from microbubbles has emerged as a sensitive method for contrast agent imaging. Nevertheless, the detection of these high-frequency components, including the third, fourth, and fifth harmonics, remains challenging because of the lack of transducer sensitivity and bandwidth. In this context, we propose a new design of imaging transducer based on a simple fabrication process for high-frequency nonlinear imaging. The transducer is composed of two elements: the outer low-frequency (LF) element was centered at 4 MHz and used in transmit mode, whereas the inner high-frequency (HF) element centered at 14 MHz was used in receive mode. The center element was pad-printed using a lead zirconate titanate (PZT) paste. The outer element was molded using a commercial PZT, and curved porous unpoled PZT was used as backing. Each piezoelectric element was characterized to determine the electromechanical performance with thickness coupling factor around 45%. After the assembly of the two transducer elements, hydrophone measurements (electroacoustic responses and radiation patterns) were carried out and demonstrated a large bandwidth (70% at -3 dB) of the HF transducer. Finally, the transducer was evaluated for contrast agent imaging using contrast agent microbubbles. The results showed that harmonic components (up to the sixth harmonic) of the microbubbles were successfully detected. Moreover, images from a flow phantom were acquired and demonstrated the potential of the transducer for high-frequency nonlinear contrast imaging.

  4. Piecewise nonlinear image registration using DCT basis functions

    Science.gov (United States)

    Gan, Lin; Agam, Gady

    2015-03-01

    The deformation field in nonlinear image registration is usually modeled by a global model. Such models are often faced with the problem that a locally complex deformation cannot be accurately modeled by simply increasing degrees of freedom (DOF). In addition, highly complex models require additional regularization which is usually ineffective when applied globally. Registering locally corresponding regions addresses this problem in a divide and conquer strategy. In this paper we propose a piecewise image registration approach using Discrete Cosine Transform (DCT) basis functions for a nonlinear model. The contributions of this paper are three-folds. First, we develop a multi-level piecewise registration framework that extends the concept of piecewise linear registration and works with any nonlinear deformation model. This framework is then applied to nonlinear DCT registration. Second, we show how adaptive model complexity and regularization could be applied for local piece registration, thus accounting for higher variability. Third, we show how the proposed piecewise DCT can overcome the fundamental problem of a large curvature matrix inversion in global DCT when using high degrees of freedoms. The proposed approach can be viewed as an extension of global DCT registration where the overall model complexity is increased while achieving effective local regularization. Experimental evaluation results provide comparison of the proposed approach to piecewise linear registration using an affine transformation model and a global nonlinear registration using DCT model. Preliminary results show that the proposed approach achieves improved performance.

  5. Image nonlinearity and non-uniformity corrections using Papoulis - Gerchberg algorithm in gamma imaging systems

    Science.gov (United States)

    Shemer, A.; Schwarz, A.; Gur, E.; Cohen, E.; Zalevsky, Z.

    2015-04-01

    In this paper, the authors describe a novel technique for image nonlinearity and non-uniformity corrections in imaging systems based on gamma detectors. The limitation of the gamma detector prevents the producing of high quality images due to the radionuclide distribution. This problem causes nonlinearity and non-uniformity distortions in the obtained image. Many techniques have been developed to correct or compensate for these image artifacts using complex calibration processes. The presented method is based on the Papoulis - Gerchberg(PG) iterative algorithm and is obtained without need of detector calibration, tuning process or using any special test phantom.

  6. Scene matching based on non-linear pre-processing on reference image and sensed image

    Institute of Scientific and Technical Information of China (English)

    Zhong Sheng; Zhang Tianxu; Sang Nong

    2005-01-01

    To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.

  7. Non-linear imaging condition to image fractures as non-welded interfaces

    NARCIS (Netherlands)

    Minato, S.; Ghose, R.

    2014-01-01

    Hydraulic properties of a fractured reservoir are often controlled by large fractures. In order to seismically detect and characterize them, a high-resolution imaging method is necessary. We apply a non-linear imaging condition to image fractures, considered as non-welded interfaces. We derive the i

  8. Magnetic resonance imaging with nonlinear gradient fields signal encoding and image reconstruction

    CERN Document Server

    Schultz, Gerrit

    2013-01-01

    Within the past few decades magnetic resonance imaging has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This text deals with a radically new approach of image encoding: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics.   Contents n  Image Reconstruction in MRI n  Nonlinear Gradient Encoding: PatLoc Imaging n  Presentation of Initial Hardware Designs n  Basics of Signal Encoding and Image Reconstruction in PatLoc Imaging n ...

  9. Laser Imaging of Airborne Acoustic Emission by Nonlinear Defects

    Science.gov (United States)

    Solodov, Igor; Döring, Daniel; Busse, Gerd

    2008-06-01

    Strongly nonlinear vibrations of near-surface fractured defects driven by an elastic wave radiate acoustic energy into adjacent air in a wide frequency range. The variations of pressure in the emitted airborne waves change the refractive index of air thus providing an acoustooptic interaction with a collimated laser beam. Such an air-coupled vibrometry (ACV) is proposed for detecting and imaging of acoustic radiation of nonlinear spectral components by cracked defects. The photoelastic relation in air is used to derive induced phase modulation of laser light in the heterodyne interferometer setup. The sensitivity of the scanning ACV to different spatial components of the acoustic radiation is analyzed. The animated airborne emission patterns are visualized for the higher harmonic and frequency mixing fields radiated by planar defects. The results confirm a high localization of the nonlinear acoustic emission around the defects and complicated directivity patterns appreciably different from those observed for fundamental frequencies.

  10. Image restoration by the method of convex projections: part 2 applications and numerical results.

    Science.gov (United States)

    Sezan, M I; Stark, H

    1982-01-01

    The image restoration theory discussed in a previous paper by Youla and Webb [1] is applied to a simulated image and the results compared with the well-known method known as the Gerchberg-Papoulis algorithm. The results show that the method of image restoration by projection onto convex sets, by providing a convenient technique for utilizing a priori information, performs significantly better than the Gerchberg-Papoulis method.

  11. Ultrasonic image restoration based on support vector machine for surfacing interface testing

    Institute of Scientific and Technical Information of China (English)

    Gao Shuangsheng; Gang Tie; Chi Dazhao

    2007-01-01

    In order to restore the degraded ultrasonic C-scan image for testing surfacing interface, a method based on support vector regression (SVR) network is proposed. By using the image of a simulating defect, the network is trained and a mapping relationship between the degraded and restored image is founded. The degraded C-scan image of Cu-Steel surfacing interface is processed by the trained network and improved image is obtained. The result shows that the method can effectively suppress the noise and deblur the defect edge in the image, and provide technique support for quality and reliability evaluation of the surfacing weld.

  12. Bayesian Image Restoration Using a Large-Scale Total Patch Variation Prior

    Directory of Open Access Journals (Sweden)

    Yang Chen

    2011-01-01

    Full Text Available Edge-preserving Bayesian restorations using nonquadratic priors are often inefficient in restoring continuous variations and tend to produce block artifacts around edges in ill-posed inverse image restorations. To overcome this, we have proposed a spatial adaptive (SA prior with improved performance. However, this SA prior restoration suffers from high computational cost and the unguaranteed convergence problem. Concerning these issues, this paper proposes a Large-scale Total Patch Variation (LS-TPV Prior model for Bayesian image restoration. In this model, the prior for each pixel is defined as a singleton conditional probability, which is in a mixture prior form of one patch similarity prior and one weight entropy prior. A joint MAP estimation is thus built to ensure the iteration monotonicity. The intensive calculation of patch distances is greatly alleviated by the parallelization of Compute Unified Device Architecture(CUDA. Experiments with both simulated and real data validate the good performance of the proposed restoration.

  13. Comparison-based Image Quality Assessment for Selecting Image Restoration Parameters.

    Science.gov (United States)

    Liang, Haoyi; Weller, Daniel

    2016-08-19

    Image quality assessment (IQA) is traditionally classified into full-reference (FR) IQA, reduced-reference (RR) IQA, and no-reference (NR) IQA according to the amount of information required from the original image. Although NRIQA and RR-IQA are widely used in practical applications, room for improvement still remains because of the lack of the reference image. Inspired by the fact that in many applications, such as parameter selection for image restoration algorithms, a series of distorted images are available, the authors propose a novel comparison-based image quality assessment (C-IQA) framework. The new comparison-based framework parallels FRIQA by requiring two input images, and resembles NR-IQA by not using the original image. As a result, the new comparisonbased approach has more application scenarios than FR-IQA does, and takes greater advantage of the accessible information than the traditional single-input NR-IQA does. Further, C-IQA is compared with other state-of-the-art NR-IQA methods and another RR-IQA method on two widely used IQA databases. Experimental results show that C-IQA outperforms the other methods for parameter selection, and the parameter trimming framework combined with C-IQA saves the computation of iterative image reconstruction up to 80%.

  14. Imaging of contact acoustic nonlinearity using synthetic aperture technique.

    Science.gov (United States)

    Yun, Dongseok; Kim, Jongbeom; Jhang, Kyung-Young

    2013-09-01

    The angle beam incidence and reflection technique for the evaluation of contact acoustic nonlinearity (CAN) at solid-solid contact interfaces (e.g., closed cracks) has recently been developed to overcome the disadvantage of accessing both the inner and outer surfaces of structures for attaching pulsing and receiving transducers in the through-transmission of normal incidence technique. This paper proposes a technique for B-mode imaging of CAN based on the above reflection technique, which uses the synthetic aperture focusing technique (SAFT) and short-time Fourier transform (STFT) to visualize the distribution of the CAN-induced second harmonic magnitude as well as the nonlinear parameter. In order to verify the usefulness of the proposed method, a solid-solid contact interface was tested and the change of the contact acoustic nonlinearity according to the increasing contact pressure was visualized in images of the second harmonic magnitude and the relative nonlinear parameter. The experimental results showed good agreement with the previously developed theory identifying the dependence of the scattered second harmonics on the contact pressure. This technique can be used for the detection and improvement of the sizing accuracy of closed cracks that are difficult to detect using the conventional linear ultrasonic technique.

  15. Nonlinear optical imaging characteristics in rat tail tendon

    Science.gov (United States)

    Liu, N. R.; Zhang, X. Z.; Qiu, Y. S.; Chen, R.

    2013-04-01

    The aim of this study was to examine the characteristics of skeletal muscle fibers in tail tendons, explore the content of intrinsic components at different depths and ascertain the optimum excitation wavelength, which will help to establish a relationship between diagnosis and therapy and the tendon injury. A multiphoton microscopic imaging system was used to achieve the images and spectra via an imaging mode and a Lambda mode, respectively. This work demonstrates that the skeletal muscle fibers of the tail tendon are in good order. Second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) signals originating from certain intrinsic components are varied with depth, and the SHG/TPEF intensity ratios are varied at different excitation wavelengths. Below 800 nm is the optimum for cell TPEF, while above 800 nm is the optimum for SHG. With the development of imaging techniques, a nonlinear optical imaging system will be helpful to represent the functional behaviors of tissue related to tendon injury.

  16. Research on a novel restoration algorithm of turbulence-degraded images with alternant iterations

    Institute of Scientific and Technical Information of China (English)

    Liu Chunsheng; Hong Hanyu; Zhang Tianxu

    2006-01-01

    A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images. Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing.

  17. Image restoration using 2D autoregressive texture model and structure curve construction

    Science.gov (United States)

    Voronin, V. V.; Marchuk, V. I.; Petrosov, S. P.; Svirin, I.; Agaian, S.; Egiazarian, K.

    2015-05-01

    In this paper an image inpainting approach based on the construction of a composite curve for the restoration of the edges of objects in an image using the concepts of parametric and geometric continuity is presented. It is shown that this approach allows to restore the curved edges and provide more flexibility for curve design in damaged image by interpolating the boundaries of objects by cubic splines. After edge restoration stage, a texture restoration using 2D autoregressive texture model is carried out. The image intensity is locally modeled by a first spatial autoregressive model with support in a strongly causal prediction region on the plane. Model parameters are estimated by Yule-Walker method. Several examples considered in this paper show the effectiveness of the proposed approach for large objects removal as well as recovery of small regions on several test images.

  18. Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm

    KAUST Repository

    Desmal, Abdulla

    2017-04-03

    An efficient electromagnetic inversion scheme for imaging sparse 3-D domains is proposed. The scheme achieves its efficiency and accuracy by integrating two concepts. First, the nonlinear optimization problem is constrained using L₀ or L₁-norm of the solution as the penalty term to alleviate the ill-posedness of the inverse problem. The resulting Tikhonov minimization problem is solved using nonlinear Landweber iterations (NLW). Second, the efficiency of the NLW is significantly increased using a steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without sacrificing the convergence of the algorithm. Numerical results demonstrate the efficiency and accuracy of the proposed imaging scheme in reconstructing sparse 3-D dielectric profiles.

  19. Utilization of multiple frequencies in 3D nonlinear microwave imaging

    DEFF Research Database (Denmark)

    Jensen, Peter Damsgaard; Rubæk, Tonny; Mohr, Johan Jacob

    2012-01-01

    The use of multiple frequencies in a nonlinear microwave algorithm is considered. Using multiple frequencies allows for obtaining the improved resolution available at the higher frequencies while retaining the regularizing effects of the lower frequencies. However, a number of different challenges...... at lower frequencies are used as starting guesses for reconstructions at higher frequencies. The performance is illustrated using simulated 2-D data and data obtained with the 3-D DTU microwave imaging system....

  20. Restoration of Scanning Tunneling Microscope Images by means of Two-Dimensional Maximum Entropy Method

    Science.gov (United States)

    Matsumoto, Hisanori; Tokiwano, Kazuo; Hosoi, Hirotaka; Sueoka, Kazuhisa; Mukasa, Koichi

    2002-05-01

    We present a new technique for the restoration of scanning tunneling microscopy (STM) images, which is a two-dimensional extension of a recently developed statistical approach based on the one-dimensional least-squares method (LSM). An STM image is regarded as a realization of a stochastic process and assumed to be a composition of an underlying image and noise. We express the underlying image in terms of a two-dimensional generalized trigonometric polynomial suitable for representing the atomic protrusions in STM images. The optimization of the polynomial is performed by the two-dimensional LSM combined with the power spectral density function estimated by means of the maximum entropy method (MEM) iterative algorithm for two-dimensional signals. The restored images are obtained as the optimum least-squares fitting polynomial which is a continuous surface. We apply this technique to modeled and actual STM data. Results show that the present method yields a reasonable restoration of STM images.

  1. Label-free imaging through nonlinear optical signals

    Directory of Open Access Journals (Sweden)

    Ling Tong

    2011-06-01

    Full Text Available Strong intrinsic nonlinear optical (NLO signals not only make nanostructures promising agents for bio-imaging, but also advance NLO microscopy for the study of interactions between nanomaterials and live cells. Single beam modalities such as multiphoton luminescence, second harmonic generation, and third harmonic generation provide a simple way to probe many types of nanostructures. As for more advanced modalities, photothermal heterodyne imaging provides improved detection sensitivity for smaller objects, and transient absorption microscopy provides structural information to distinguish metal from semiconducting carbon nanotubes, and eumelanin from pheomelanin. The four-wave mixing signal achieves chemical selectivity in the presence of either vibrational or electronic resonance, as used in coherent Raman scattering imaging of molecules and in electronically resonance enhanced four-wave mixing imaging of nanostructures.

  2. Molecular Histopathology by Spectrally Reconstructed Nonlinear Interferometric Vibrational Imaging

    Science.gov (United States)

    Chowdary, Praveen D.; Jiang, Zhi; Chaney, Eric J.; Benalcazar, Wladimir A.; Marks, Daniel L.; Gruebele, Martin; Boppart, Stephen A.

    2011-01-01

    Sensitive assays for rapid quantitative analysis of histologic sections, resected tissue specimens, or in situ tissue are highly desired for early disease diagnosis. Stained histopathology is the gold standard but remains a subjective practice on processed tissue taking from hours to days. We describe a microscopy technique that obtains a sensitive and accurate color-coded image from intrinsic molecular markers. Spectrally reconstructed nonlinear interferometric vibrational imaging can differentiate cancer versus normal tissue sections with greater than 99% confidence interval in a preclinical rat breast cancer model and define cancer boundaries to ±100 μm with greater than 99% confidence interval, using fresh unstained tissue sections imaged in less than 5 minutes. By optimizing optical sources and beam delivery, this technique can potentially enable real-time point-of-care optical molecular imaging and diagnosis. PMID:21098699

  3. Label-free nonlinear optical imaging of mouse retina.

    Science.gov (United States)

    He, Sicong; Ye, Cong; Sun, Qiqi; Leung, Christopher K S; Qu, Jianan Y

    2015-03-01

    A nonlinear optical (NLO) microscopy system integrating stimulated Raman scattering (SRS), two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) was developed to image fresh mouse retinas. The morphological and functional details of various retinal layers were revealed by the endogenous NLO signals. Particularly, high resolution label-free imaging of retinal neurons and nerve fibers in the ganglion cell and nerve fiber layers was achieved by capturing endogenous SRS and TPEF signals. In addition, the spectral and temporal analysis of TPEF images allowed visualization of different fluorescent components in the retinal pigment epithelium (RPE). Fluorophores with short TPEF lifetime, such as A2E, can be differentiated from other long-lifetime components in the RPE. The NLO imaging method would provide important information for investigation of retinal ganglion cell degeneration and holds the potential to study the biochemical processes of visual cycle in the RPE.

  4. Novel recovery mechanism for the restoration of image contents in teleconsultation sessions.

    Science.gov (United States)

    Wang, Cheng-Hsiung; Ssu, Kuo-Feng; Chung, Pau-Choo; Jiau, Hewijin Christine; Shih, Wei-Te

    2012-01-01

    In teleconsultation sessions, a critical dependency exists between the image contents and the type and sequential order of the image processing commands used by the various participants. Accordingly, for re-entrant/late users, a significant challenge exists in restoring the image contents of the teleconsultation session in such a way that all the participants maintain a consistent view of the medical images. In this paper, this problem is resolved using a novel recovery mechanism comprising two major components, namely an enhanced content-recording scheme designated as three-level indexing hierarchy (TIH) and a prioritized recovery policy. TIH maintains a record of all the commands which affect the appearance of each of medical images such that when a restoration process is required, these image-affect commands can be rapidly identified and transmitted to the user. As a result, a significant reduction can be gained in both the command identification/transmission time and the image restoration time compared to traditional recovery schemes, which restore the contents by re-executing all of the commands invoked during the course of the session. The prioritized recovery policy further reduces the time required for re-entrant/late users to catch up with the on-going session by utilizing the cross-linkage design within the TIH architecture to restore the foreground image (i.e. the image under current discussion) before the background images are restored (i.e. the remaining images in the session). To resolve the problem which arises when a background image is selected as the new foreground image before the restoration process is completed, the prioritized recovery policy maintains a set of resuming pointers for each re-entrant/late user to facilitate the process of suspending the current restoration process and switching to the restoration of the new foreground image. The evaluation results confirm that the TIH architecture and prioritized recovery policy yield a

  5. Color image encryption based on Coupled Nonlinear Chaotic Map

    Energy Technology Data Exchange (ETDEWEB)

    Mazloom, Sahar [Faculty of Electrical, Computer and IT Engineering, Qazvin Islamic Azad University, Qazvin (Iran, Islamic Republic of)], E-mail: sahar.mazloom@gmail.com; Eftekhari-Moghadam, Amir Masud [Faculty of Electrical, Computer and IT Engineering, Qazvin Islamic Azad University, Qazvin (Iran, Islamic Republic of)], E-mail: eftekhari@qazviniau.ac.ir

    2009-11-15

    Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional methods. The desirable cryptographic properties of the chaotic maps such as sensitivity to initial conditions and random-like behavior have attracted the attention of cryptographers to develop new encryption algorithms. Therefore, recent researches of image encryption algorithms have been increasingly based on chaotic systems, though the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper proposes a Coupled Nonlinear Chaotic Map, called CNCM, and a novel chaos-based image encryption algorithm to encrypt color images by using CNCM. The chaotic cryptography technique which used in this paper is a symmetric key cryptography with a stream cipher structure. In order to increase the security of the proposed algorithm, 240 bit-long secret key is used to generate the initial conditions and parameters of the chaotic map by making some algebraic transformations to the key. These transformations as well as the nonlinearity and coupling structure of the CNCM have enhanced the cryptosystem security. For getting higher security and higher complexity, the current paper employs the image size and color components to cryptosystem, thereby significantly increasing the resistance to known/chosen-plaintext attacks. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for real-time image encryption and transmission.

  6. Nonlinear Interferometric Vibrational Imaging (NIVI) with Novel Optical Sources

    Science.gov (United States)

    Boppart, Stephen A.; King, Matthew D.; Liu, Yuan; Tu, Haohua; Gruebele, Martin

    Optical imaging is essential in medicine and in fundamental studies of biological systems. Although many existing imaging modalities can supply valuable information, not all are capable of label-free imaging with high-contrast and molecular specificity. The application of molecular or nanoparticle contrast agents may adversely influence the biological system under investigation. These substances also present ongoing concerns over toxicity or particle clearance, which must be properly addressed before their approval for in vivo human imaging. Hence there is an increasing appreciation for label-free imaging techniques. It is of primary importance to develop imaging techniques that can indiscriminately identify and quantify biochemical compositions to high degrees of sensitivity and specificity through only the intrinsic optical response of endogenous molecular species. The development and use of nonlinear interferometric vibrational imaging, which is based on the interferometric detection of optical signals from coherent anti-Stokes Raman scattering (CARS), along with novel optical sources, offers the potential for label-free molecular imaging.

  7. Non-linear image scanning microscopy (Conference Presentation)

    Science.gov (United States)

    Gregor, Ingo; Ros, Robert; Enderlein, Jörg

    2017-02-01

    Nowadays, multiphoton microscopy can be considered as a routine method for the observation of living cells, organs, up to whole organisms. Second-harmonics generation (SHG) imaging has evolved to a powerful qualitative and label-free method for studying fibrillar structures, like collagen networks. However, examples of super-resolution non-linear microscopy are rare. So far, such approaches require complex setups and advanced synchronization of scanning elements limiting the image acquisition rates. We describe theory and realization of a super-resolution image scanning microscope [1, 2] using two-photon excited fluorescence as well as second-harmonic generation. It requires only minor modifications compared to a classical two-photon laser-scanning microscope and allows image acquisition at the high frame rates of a resonant galvo-scanner. We achieve excellent sensitivity and high frame-rate in combination with two-times improved lateral resolution. We applied this method to fixed cells, collagen hydrogels, as well as living fly embryos. Further, we proofed the excellent image quality of our setup for deep tissue imaging. 1. Müller C.B. and Enderlein J. (2010) Image scanning microscopy. Phys. Rev. Lett. 104(19), 198101. 2. Sheppard C.J.R. (1988) Super-resolution in confocal imaging. Optik (Stuttg) 80 53-54.

  8. Design and implementation of non-linear image processing functions for CMOS image sensor

    Science.gov (United States)

    Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

    2012-11-01

    Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

  9. High resolution retinal image restoration with wavefront sensing and self-extracted filtering

    Science.gov (United States)

    Yang, Shuyu; Erry, Gavin; Nemeth, Sheila; Mitra, Sunanda; Soliz, Peter

    2005-04-01

    Diagnosis and treatment of retinal diseases such as diabetic retinopathy commonly rely on a clear view of the retina. The challenge in obtaining high quality retinal image lies in the design of the imaging system that can reduce the strong aberrations of the human eye. Since the amplitudes of human eye aberrations decrease rapidly as the aberration order goes up, it is more cost-effective to correct low order aberrations with adaptive optical devices while process high order aberrations through image processing. A cost effective fundus imaging device that can capture high quality retinal images with 2-5 times higher resolution than conventional retinal images has been designed [1]. This imager improves image quality by attaching complementary adaptive optical components to a conventional fundus camera. However, images obtained with the high resolution camera are still blurred due to some uncorrected aberrations as well as defocusing resulting from non-isoplanatic effect. Therefore, advanced image restoration algorithms have been employed for further improvement in image quality. In this paper, we use wavefront-based and self-extracted blind deconvolution techniques to restore images captured by the high resolution fundus camera. We demonstrate that through such techniques, pathologies that are critical to retinal disease diagnosis but not clear or not observable in the original image can be observed clearly in the restored images. Image quality evaluation is also used to finalize the development of a cost-effective, fast, and automated diagnostic system that can be used clinically.

  10. Non-linear Imaging using an Experimental Synthetic Aperture Real Time Ultrasound Scanner

    DEFF Research Database (Denmark)

    Rasmussen, Joachim; Du, Yigang; Jensen, Jørgen Arendt

    2011-01-01

    This paper presents the first non-linear B-mode image of a wire phantom using pulse inversion attained via an experimental synthetic aperture real-time ultrasound scanner (SARUS). The purpose of this study is to implement and validate non-linear imaging on SARUS for the further development of new...... non-linear techniques. This study presents non-linear and linear B-mode images attained via SARUS and an existing ultrasound system as well as a Field II simulation. The non-linear image shows an improved spatial resolution and lower full width half max and -20 dB resolution values compared to linear...

  11. Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2014-05-04

    Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

  12. Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2014-01-06

    Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

  13. Stokes imaging polarimetry using image restoration at the Swedish 1-m Solar Telescope

    CERN Document Server

    van Noort, M J

    2008-01-01

    Aims: We aim to achieve high spatial resolution as well as high polarimetric sensitivity, using an earth-based 1m-class solar telescope, for the study of magnetic fine structure on the Sun. Methods: We use a setup with 3 high-speed, low-noise cameras to construct datasets with interleaved polarimetric states, particularly suitable for Multi-Object Multi-Frame Blind Deconvolution image restorations. We discuss the polarimetric calibration routine as well as various potential sources of error in the results. Results: We obtained near diffraction limited images, with a noise level of approximately 10^(-3) I(cont). We confirm that dark-cores have a weaker magnetic field and at a lower inclination angle with respect to the solar surface than the edges of the penumbral filament. We show that the magnetic field strength in faculae-striations is significantly lower than in other nearby parts of the faculae.

  14. CT image sequence restoration based on sparse and low-rank decomposition.

    Directory of Open Access Journals (Sweden)

    Shuiping Gou

    Full Text Available Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA, Linearized Alternating Direction Method with Adaptive Penalty (LADMAP and Go Decomposition (GoDec. Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images.

  15. Selective mapping and restorable clipping joint scheme for light-emitting diode nonlinearity alleviation in visible light communication system

    Science.gov (United States)

    Yan, Chaowen; Wang, Jianping; Lu, Huimin; Shi, Yinjia; Zhang, Yini

    2016-05-01

    A joint algorithm, integrating selective mapping (SLM) and restorable clipping (RC), is proposed for the direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) and visible light communication (VLC) system to reduce the nonlinearity impacts of light-emitting diode (LED) aggravated by high peak-to-average power ratio (PAPR) and DC-bias. The performance of DCO-OFDM VLC system is analyzed and discussed with different techniques of LED nonlinearity alleviation. The simulation results show that compared to the original DCO-OFDM VLC system, the system with the proposed scheme can achieve about 4.8 dB improvement of PAPR reduction and 7 dB improvement of bit error rate (BER) performance. The reason is that the signals acquiring the desired shape in LED linear region can be recovered correctly without distortion induced by LED nonlinearity. It is demonstrated that the proposed SLM-RC technique effectively reduces not only PAPR but also the impacts of LED nonlinearity without BER deterioration.

  16. Box-constrained Total-variation Image Restoration with Automatic Parameter Estimation

    Institute of Scientific and Technical Information of China (English)

    HE Chuan; HU Chang-Hua; ZHANG Wei; SHI Biao

    2014-01-01

    The box constraints in image restoration have been arousing great attention, since the pixels of a digital image can attain only a finite number of values in a given dynamic range. This paper studies the box-constrained total-variation (TV) image restoration problem with automatic regularization parameter estimation. By adopting the variable splitting technique and introducing some auxiliary variables, the box-constrained TV minimization problem is decomposed into a sequence of subproblems which are easier to solve. Then the alternating direction method (ADM) is adopted to solve the related subproblems. By means of Morozov0s discrepancy principle, the regularization parameter can be updated adaptively in a closed form in each iteration. Image restoration experiments indicate that with our strategies, more accurate solutions are achieved, especially for image with high percentage of pixel values lying on the boundary of the given dynamic range.

  17. NONLINEAR SPECTRAL IMAGING OF ELASTIC CARTILAGE IN RABBIT EARS

    Directory of Open Access Journals (Sweden)

    JING CHEN

    2013-07-01

    Full Text Available Elastic cartilage in the rabbit external ear is an important animal model with attractive potential value for researching the physiological and pathological states of cartilages especially during wound healing. In this work, nonlinear optical microscopy based on two-photon excited fluorescence and second harmonic generation were employed for imaging and quantifying the intact elastic cartilage. The morphology and distribution of main components in elastic cartilage including cartilage cells, collagen and elastic fibers were clearly observed from the high-resolution two-dimensional nonlinear optical images. The areas of cell nuclei, a parameter related to the pathological changes of normal or abnormal elastic cartilage, can be easily quantified. Moreover, the three-dimensional structure of chondrocytes and matrix were displayed by constructing three-dimensional image of cartilage tissue. At last, the emission spectra from cartilage were obtained and analyzed. We found that the different ratio of collagen over elastic fibers can be used to locate the observed position in the elastic cartilage. The redox ratio based on the ratio of nicotinamide adenine dinucleotide (NADH over flavin adenine dinucleotide (FAD fluorescence can also be calculated to analyze the metabolic state of chondrocytes in different regions. Our results demonstrated that this technique has the potential to provide more accurate and comprehensive information for the physiological states of elastic cartilage.

  18. Supervised restoration of degraded medical images using multiple-point geostatistics.

    Science.gov (United States)

    Pham, Tuan D

    2012-06-01

    Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing.

  19. Nonlinear filtering for character recognition in low quality document images

    Science.gov (United States)

    Diaz-Escobar, Julia; Kober, Vitaly

    2014-09-01

    Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.

  20. Point spread function modeling and images restoration for cone-beam CT

    CERN Document Server

    Zhang, Hua; Shi, Yikai; Xu, Zhe

    2014-01-01

    X-ray cone-beam computed tomography (CT) has the notable features such as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection images degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed firstly. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection images restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection images restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasib...

  1. Dark channel prior based blurred image restoration method using total variation and morphology

    Institute of Scientific and Technical Information of China (English)

    Yibing Li; Qiang Fu; Fang Ye; Hayaru Shouno

    2015-01-01

    The blurred image restoration method can dramatical y highlight the image details and enhance the global contrast, which is of benefit to improvement of the visual effect during practical ap-plications. This paper is based on the dark channel prior principle and aims at the prior information absent blurred image degradation situation. A lot of improvements have been made to estimate the transmission map of blurred images. Since the dark channel prior principle can effectively restore the blurred image at the cost of a large amount of computation, the total variation (TV) and image morphology transform (specifical y top-hat transform and bottom-hat transform) have been introduced into the improved method. Compared with original transmission map estimation methods, the proposed method features both simplicity and accuracy. The es-timated transmission map together with the element can restore the image. Simulation results show that this method could inhibit the il-posed problem during image restoration, meanwhile it can greatly improve the image quality and definition.

  2. Mixed Gaussian-Impulse Noise Image Restoration Via Total Variation

    Science.gov (United States)

    2012-05-01

    pp. 402–407. [12] L. Rudin , S. Osher, and E. Fatemi, “Nonlinear total vari- ation based noise removal algorithms.,” Physica D. Non- lin. Phenomena...variation regularization in positron emission tomography,” UCLA CAM Report 98-48, 1998, CAM Report 98-48, UCLA. [16] S. Osher, N. Paragios, L. Rudin , and P

  3. GPU-based parallel algorithm for blind image restoration using midfrequency-based methods

    Science.gov (United States)

    Xie, Lang; Luo, Yi-han; Bao, Qi-liang

    2013-08-01

    GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images.

  4. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2014-01-01

    other documentation. 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC...and Image Processing IX, 2001. [29] J.-F. Aujol, G. Aubert, L. Blanc- Fraud , and A. Chambolle, “Image decomposition application to SAR images,” in

  5. Particle Swarm Optimization Based Support Vector Regression for Blind Image Restoration

    Institute of Scientific and Technical Information of China (English)

    Ratnakar Dash; Pankaj Kumar Sa; Banshidhar Majhi

    2012-01-01

    This paper presents a swarm intelligence based parameter optimization of the support vector machine (SVM)for blind image restoration.In this work,SVM is used to solve a regression problem.Support vector regression (SVR)has been utilized to obtain a true mapping of images from the observed noisy blurred images.The parameters of SVR are optimized through particle swarm optimization (PSO) technique.The restoration error function has been utilized as the fitness function for PSO.The suggested scheme tries to adapt the SVM parameters depending on the type of blur and noise strength and the experimental results validate its effectiveness.The results show that the parameter optimization of the SVR model gives better performance than conventional SVR model as well as other competent schemes for blind image restoration.

  6. Imaging the anisotropic nonlinear Meissner effect in unconventional superconductors

    Energy Technology Data Exchange (ETDEWEB)

    Zhuravel, Alexander P. [B. Verkin Institute for Low Temperature Physics and Engineering, National Academy of Sciences of Ukraine, Kharkov (Ukraine); Ghamsari, Behnood G.; Kurter, Cihan; Abrahams, John [CNAM, Physics Department, University of Maryland, College Park, MD (United States); Jung, Philipp; Lukashenko, Alexander; Ustinov, Alexey V. [Physikalisches Institut and DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology, Karlsruhe (Germany); Remillard, Stephen [Physics Department, Hope College, Holland, MI (United States); Anlage, Steven M. [CNAM, Physics Department, University of Maryland, College Park, MD (United States); Physikalisches Institut and DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology, Karlsruhe (Germany)

    2013-07-01

    We present measurements on the anisotropic nonlinear Meissner effect (aNLME). Using a laser scanning microscope we have directly imaged this effect in a self-resonant spiral patterned from a thin film of the d{sub x{sup 2}-y{sup 2}} superconductor YBa{sub 2}Cu{sub 3}O{sub 7-δ}. The spiral is excited at one of its resonant frequencies while a focused laser spot is scanned across its surface. The local illumination by the laser gives rise to a detectable change in the resonant properties. At low temperatures, the aNLME causes a direction dependent contribution to the critical current density. This makes it possible to image the directions of nodes and anti-nodes of the superconducting order parameter and the contribution of Andreev bound states associated with them. These two contributions to the photoresponse can be distinguished by their temperature dependence, which is consistent with theoretical predictions.

  7. Bispectral methods of signal processing applications in radar, telecommunications and digital image restoration

    CERN Document Server

    Totsky, Alexander V; Kravchenko, Victor F

    2015-01-01

    By studying applications in radar, telecommunications and digital image restoration, this monograph discusses signal processing techniques based on bispectral methods. Improved robustness against different forms of noise as well as preservation of phase information render this method a valuable alternative to common power-spectrum analysis used in radar object recognition, digital wireless communications, and jitter removal in images.

  8. Enhancement of out-of-focus images using fusion-based PSF estimation and restoration

    Science.gov (United States)

    Yoon, Joonshik; Shin, Jeong-Ho; Paik, Joon-Ki

    2000-12-01

    In this paper, we propose an enhancement algorithm of out-of- focused images using fusion-based Point-spread-function (PSF) estimation and restoration. The proposed algorithm can make in-focused image by using only digital image processing techniques, and it requires neither infrared light/ultrasound nor focusing lens assembly operated by electrically powered movement of focusing lens. In order to increase accuracy in estimating the PSF of the defocus image, the proposed algorithm finds true and linear edges by using Canny edge detector, which is optimal edge detector and has good localization, estimates the step response across the edge for each pixel, computes the one-dimensional step response by averaging the step responses, estimates the two-dimensional PSF from the averaged step response, and then provides in- focused image by image restoration filter based on the estimated PSF. Finally, we execute fusion process, which can enhance the quality of the fused image by fusing restored images. There is a limit of the amount of out-of-focus, which can be recovered by the proposed algorithm. Moreover, the proposed algorithm is operating under assumption that an input image contains at least one piece-wise linear boundary between an object and background. In spite of above-mentioned limitations, the proposed algorithm can make acceptable quality of focused image by using only digital image processing.

  9. Learning nonlinear statistical regularities in natural images by modeling the outer product of image intensities.

    Science.gov (United States)

    Qi, Peng; Hu, Xiaolin

    2014-04-01

    It is well known that there exist nonlinear statistical regularities in natural images. Existing approaches for capturing such regularities always model the image intensities by assuming a parameterized distribution for the intensities and learn the parameters. In the letter, we propose to model the outer product of image intensities by assuming a gaussian distribution for it. A two-layer structure is presented, where the first layer is nonlinear and the second layer is linear. Trained on natural images, the first-layer bases resemble the receptive fields of simple cells in the primary visual cortex (V1), while the second-layer units exhibit some properties of the complex cells in V1, including phase invariance and masking effect. The model can be seen as an approximation of the covariance model proposed in Karklin and Lewicki (2009) but has more robust and efficient learning algorithms.

  10. Restoration of digital images with known space-variant blurs from conventional optical systems

    Science.gov (United States)

    Costello, Thomas P.; Mikhael, Wasfy B.

    1999-07-01

    Space-variant (SV) digital image restoration methods attempt to restore images degraded by blurs that vary over the image field. One specific source of SV blurs is that of geometrical optical aberrations, which divert light rays as they pass through the optical system away from an ideal focal point. For simple optical system, aberrations can become significant even at moderate field angles. Restoration methods have been developed for some space- variant aberrations when they are individually dominant, but such dominance is not typically characteristic of conventional optical systems. In this paper, an iterative method of restoration that is applicable to generalized, known space-variant blurs is applied to simulations of images generated with a spherical lines. The method is based on the Gauss-Seidel method of solution to systems of linear equations. The method is applied to sub-images having off- axis displacements of up to 453 pixels, and found to be superior in restoration effectiveness to Fourier methods in that range of field angles.

  11. Digital imaging for cultural heritage preservation analysis, restoration, and reconstruction of ancient artworks

    CERN Document Server

    Stanco, Filippo; Gallo, Giovanni

    2011-01-01

    Experiencing the Past: Computer Graphics in Archaeology, F. Stanco and D. TanasiThe Past and the Future: Archaeology and Computer ScienceFrom the Field to the Screen: 3D computer graphics and the Archaeological HeritageThe Archeomatica ProjectArchaeological 3D ModelingHaghia Triada, CretePolizzello Mountain, SicilyDigital RestorationDealing with Image Data in Archaeology: New PerspectivesUsing Digital 3D Models for Study and Restoration of Cultural Heritage Artifacts, M.

  12. Molecular probes for nonlinear optical imaging of biological membranes

    Science.gov (United States)

    Blanchard-Desce, Mireille H.; Ventelon, Lionel; Charier, Sandrine; Moreaux, Laurent; Mertz, Jerome

    2001-12-01

    Second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) are nonlinear optical (NLO) phenomena that scale with excitation intensity squared, and hence give rise to an intrinsic 3-dimensional resolution when used in microscopic imaging. TPEF microscopy has gained widespread popularity in the biology community whereas SHG microscopy promises to be a powerful tool because of its sensitivity to local asymmetry. We have implemented an approach toward the design of NLO-probes specifically adapted for SHG and/or TPEF imaging of biological membranes. Our strategy is based on the design of nanoscale amphiphilic NLO-phores. We have prepared symmetrical bolaamphiphilic fluorophores combining very high two-photon absorption (TPA) cross-sections in the visible red region and affinity for cellular membranes. Their incorporation and orientation in lipid membranes can be monitored via TPEF anisotropy. We have also prepared amphiphilic push-pull chromophores exhibiting both large TPA cross-sections and very large first hyperpolarizabilities in the near-IR region. These NLO-probes have proved to be particularly useful for imaging of biological membranes by simultaneous SHG and TPEF microscopy and offer attractive prospects for real-time imaging of fundamental biological processes such as adhesion, fusion or reporting of membrane potentials.

  13. Separated Component-Based Restoration of Speckled SAR Images

    Science.gov (United States)

    2013-01-01

    This new process is also valuable for many SAR image understanding tasks such as road detection, railway detection, ship wake detection, texture...Starck, and L. Boubchir, “Morphological diversity and sparse image denoising,” in Proc. IEEE Int. Conf. Acoust . Speech Signal Process., vol. 1. Apr

  14. DEVELOPMENT OF OPTIMAL FILTERS OBTAINED THROUGH CONVOLUTION METHODS, USED FOR FINGERPRINT IMAGE ENHANCEMENT AND RESTORATION

    OpenAIRE

    Cătălin LUPU

    2014-01-01

    This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter), non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting i...

  15. DEVELOPMENT OF OPTIMAL FILTERS OBTAINED THROUGH CONVOLUTION METHODS, USED FOR FINGERPRINT IMAGE ENHANCEMENT AND RESTORATION

    OpenAIRE

    Cătălin LUPU

    2014-01-01

    This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter), non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting i...

  16. Exploring infrared neural stimulation with multimodal nonlinear imaging (Conference Presentation)

    Science.gov (United States)

    Adams, Wilson R.; Mahadevan-Jansen, Anita

    2017-02-01

    Infrared neural stimulation (INS) provides optical control of neural excitability using near to mid-infrared (mid-IR) light, which allows for spatially selective, artifact-free excitation without the introduction of exogenous agents or genetic modification. Although neural excitability is mediated by a transient temperature increase due to water absorption of IR energy, the molecular nature of IR excitability in neural tissue remains unknown. Current research suggests that transient changes in local tissue temperature give rise to a myriad of cellular responses that have been individually attributed to IR mediated excitability. To further elucidate the underlying biophysical mechanisms, we have begun work towards employing a novel multimodal nonlinear imaging platform to probe the molecular underpinnings of INS. Our imaging system performs coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), two-photon excitation fluorescence (TPEF), second-harmonic generation (SHG) and thermal imaging into a single platform that allows for unprecedented co-registration of thermal and biochemical information in real-time. Here, we present our work leveraging CARS and SRS in acute thalamocortical brain slice preparations. We observe the evolution of lipid and protein-specific Raman bands during INS and electrically evoked activity in real-time. Combined with two-photon fluorescence and second harmonic generation, we offer insight to cellular metabolism and membrane dynamics during INS. Thermal imaging allows for the coregistration of acquired biochemical information with temperature information. Our work previews the versatility and capabilities of coherent Raman imaging combined with multiphoton imaging to observe biophysical phenomena for neuroscience applications.

  17. A NEW APPROACH FOR UNSUPERVISED RESTORING IMAGES BASED ON WAVELET-DOMAIN PROJECTION PURSUIT LEARNING NETWORK

    Institute of Scientific and Technical Information of China (English)

    Lin Wei; Tian Zheng; Wen Xianbin

    2003-01-01

    The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very difficult when little is known about apriori knowledge for multisource degraded factors. WDPPLN successfully resolves this problemby separately processing wavelet coefficients and scale coefficients. Parameters in WDPPLN,which are used to simulate degraded factors, are estimated via WDPPLN training, using scalecoefficients. Also, WDPPLN uses soft-threshold of wavelet shrinkage technique to suppress noisein three high frequency subbands. The new method is compared with the traditional methodsand the Projection Pursuit Learning Network (PPLN) method. Experimental results demonstratethat it is an effective method for unsupervised restoring degraded image.

  18. Robust low-dose dynamic cerebral perfusion CT image restoration via coupled dictionary learning scheme.

    Science.gov (United States)

    Tian, Xiumei; Zeng, Dong; Zhang, Shanli; Huang, Jing; Zhang, Hua; He, Ji; Lu, Lijun; Xi, Weiwen; Ma, Jianhua; Bian, Zhaoying

    2016-11-22

    Dynamic cerebral perfusion x-ray computed tomography (PCT) imaging has been advocated to quantitatively and qualitatively assess hemodynamic parameters in the diagnosis of acute stroke or chronic cerebrovascular diseases. However, the associated radiation dose is a significant concern to patients due to its dynamic scan protocol. To address this issue, in this paper we propose an image restoration method by utilizing coupled dictionary learning (CDL) scheme to yield clinically acceptable PCT images with low-dose data acquisition. Specifically, in the present CDL scheme, the 2D background information from the average of the baseline time frames of low-dose unenhanced CT images and the 3D enhancement information from normal-dose sequential cerebral PCT images are exploited to train the dictionary atoms respectively. After getting the two trained dictionaries, we couple them to represent the desired PCT images as spatio-temporal prior in objective function construction. Finally, the low-dose dynamic cerebral PCT images are restored by using a general DL image processing. To get a robust solution, the objective function is solved by using a modified dictionary learning based image restoration algorithm. The experimental results on clinical data show that the present method can yield more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps than the state-of-the-art methods.

  19. Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

    Science.gov (United States)

    Park, Chulhee; Kang, Moon Gi

    2016-05-18

    A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

  20. Restoration of images from the scanning-tunneling microscope

    Science.gov (United States)

    Kokaram, A. C.; Persad, N.; Lasenby, J.; Fitzgerald, W. J.; McKinnon, A.; Welland, M.

    1995-08-01

    During the acquisition of an image from any probe microscope instrument, various noise sources cause distortion in the observed image. It is often the case that impulsive disturbances cause bright groups of pixels to replace the actual image data in these locations. Furthermore, the images from a probe microscope show some amount of blurring caused both by the instrument function and the material properties. In almost all image-processing applications it is important to remove any impulsive distortion that may be present before deblurring can be attempted. We give a technique for detecting these impulses and reconstructing the image. This technique is superior to the standard global application of median filters for the case considered. The reconstruction is limited only to the affected regions and therefore results in a much sharper and more meaningful image. With the assumption of Gaussian blur it is then possible to propose several different deblurring methodologies. We present a novel Wiener-filter deblurring implementation and compare it to both maximum-entropy and Richardson-Lucy deblurring.

  1. A variational image restoration with spatially varying noise

    Science.gov (United States)

    Bao, Zheng; Bai, Hua; Liu, Ruihua; Shen, Chaomin

    2008-10-01

    The noise in natural images sometimes changes according to imaging mechanism or local image information. This is called spatially varying noise. It is obvious that classical variational denoising algorithms such as the Rudin-Osher-Fatemi model are not suitable for this kind of noise. We propose a variational method to remove this spatially varying noise based on the estimation of local variance for a given image, such that high noise regions are smoothed meanwhile the textures and certain details in low noise regions are preserved. Moreover, we give the proof of existence of the minimizer of our proposed functional. The experimental results show visual improvement and high signal-to-noise ratio over other variational denoising models.

  2. Restoration of polarimetric SAR images using simulated annealing

    DEFF Research Database (Denmark)

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented...... are obtained while at the same time preserving most of the structures in the image. The algorithm is evaluated using multilook polarimetric L-band data from the Danish airborne EMISAR system, and the impact of the algorithm on the unsupervised H-α classification is demonstrated......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  3. A preconditioned inexact newton method for nonlinear sparse electromagnetic imaging

    KAUST Repository

    Desmal, Abdulla

    2015-03-01

    A nonlinear inversion scheme for the electromagnetic microwave imaging of domains with sparse content is proposed. Scattering equations are constructed using a contrast-source (CS) formulation. The proposed method uses an inexact Newton (IN) scheme to tackle the nonlinearity of these equations. At every IN iteration, a system of equations, which involves the Frechet derivative (FD) matrix of the CS operator, is solved for the IN step. A sparsity constraint is enforced on the solution via thresholded Landweber iterations, and the convergence is significantly increased using a preconditioner that levels the FD matrix\\'s singular values associated with contrast and equivalent currents. To increase the accuracy, the weight of the regularization\\'s penalty term is reduced during the IN iterations consistently with the scheme\\'s quadratic convergence. At the end of each IN iteration, an additional thresholding, which removes small \\'ripples\\' that are produced by the IN step, is applied to maintain the solution\\'s sparsity. Numerical results demonstrate the applicability of the proposed method in recovering sparse and discontinuous dielectric profiles with high contrast values.

  4. Super-resolution image restoration algorithm based on orthogonal discrete wavelet transform

    Institute of Scientific and Technical Information of China (English)

    Yangyang Liu(刘扬阳); Weiqi Jin(金伟其); Binghua Su(苏秉华)

    2004-01-01

    By using orthogonal discrete wavelet transform(ODWT)and generalized cross validation(GCV),and combining with Luck-Richardson algorithm based on Poisson-Markovmodel (MPML),several new superresolution image restoration algorithms are proposed.According to simulation experiments for practical images,all the proposed algor ithms could retain image details better than MPML,and be more suitable to low signal-to-noise ratio(SNR)images.The single operation wavelet MPML(SW-MPML)algorithm and MPML algorithm based on single operation wavelet transform(MPML-SW)avoid the iterative operation of self-adaptive parameter in MPML particularly,and improve operating speed and precision.They are instantaneous to super-resolution image restoration process and have extensive application foreground.

  5. CARS and non-linear microscopy imaging of brain tumors

    Science.gov (United States)

    Galli, Roberta; Uckermann, Ortrud; Tamosaityte, Sandra; Geiger, Kathrin; Schackert, Gabriele; Steiner, Gerald; Koch, Edmund; Kirsch, Matthias

    2013-06-01

    Nonlinear optical microscopy offers a series of techniques that have the potential to be applied in vivo, for intraoperative identification of tumor border and in situ pathology. By addressing the different content of lipids that characterize the tumors with respect to the normal brain tissue, CARS microscopy enables to discern primary and secondary brain tumors from healthy tissue. A study performed in mouse models shows that the reduction of the CARS signal is a reliable quantity to identify brain tumors, irrespective from the tumor type. Moreover it enables to identify tumor borders and infiltrations at a cellular resolution. Integration of CARS with autogenous TPEF and SHG adds morphological and compositional details about the tissue. Examples of multimodal CARS imaging of different human tumor biopsies demonstrate the ability of the technique to retrieve information useful for histopathological diagnosis.

  6. Noninvasive nonlinear imaging through strongly-scattering turbid layers

    CERN Document Server

    Katz, Ori; Guan, Yefeng; Silberberg, Yaron

    2014-01-01

    Diffraction-limited imaging through complex scattering media is a long sought after goal with important applications in biomedical research. In recent years, high resolution wavefront-shaping has emerged as a powerful approach to generate a sharp focus through highly scattering, visually opaque samples. However, it requires a localized feedback signal from the target point of interest, which necessitates an invasive procedure in all-optical techniques. Here, we show that by exploiting optical nonlinearities, a diffraction-limited focus can be formed inside or through a complex sample, even when the feedback signal is not localized. We prove our approach theoretically and numerically, and experimentally demonstrate it with a two-photon fluorescence signal through highly scattering biological samples. We use the formed focus to perform two-photon microscopy through highly scattering, visually opaque layers.

  7. A sparse electromagnetic imaging scheme using nonlinear landweber iterations

    KAUST Repository

    Desmal, Abdulla

    2015-10-26

    Development and use of electromagnetic inverse scattering techniques for imagining sparse domains have been on the rise following the recent advancements in solving sparse optimization problems. Existing techniques rely on iteratively converting the nonlinear forward scattering operator into a sequence of linear ill-posed operations (for example using the Born iterative method) and applying sparsity constraints to the linear minimization problem of each iteration through the use of L0/L1-norm penalty term (A. Desmal and H. Bagci, IEEE Trans. Antennas Propag, 7, 3878–3884, 2014, and IEEE Trans. Geosci. Remote Sens., 3, 532–536, 2015). It has been shown that these techniques produce more accurate and sharper images than their counterparts which solve a minimization problem constrained with smoothness promoting L2-norm penalty term. But these existing techniques are only applicable to investigation domains involving weak scatterers because the linearization process breaks down for high values of dielectric permittivity.

  8. Envelope based nonlinear blind deconvolution approach for ultrasound imaging

    Directory of Open Access Journals (Sweden)

    L.T. Chira

    2012-06-01

    Full Text Available The resolution of ultrasound medical images is yet an important problem despite of the researchers efforts. In this paper we presents a nonlinear blind deconvolution to eliminate the blurring effect based on the measured radio-frequency signal envelope. This algorithm is executed in two steps. Firslty we make an estimation for Point Spread Function (PSF and, secondly we use the estimated PSF to remove, iteratively their effect. The proposed algorithm is a greedy algorithm, called also matching pursuit or CLEAN. The use of this algorithm is motivated beacause theorically it avoid the so called inverse problem, which usually needs regularization to obtain an optimal solution. The results are presented using 1D simulated signals in term of visual evaluation and nMSE in comparison with the two most kwown regularisation solution methods for least square problem, Thikonov regularization or l2-norm and Total Variation or l1 norm.

  9. Iterative Desensitisation of Image Restoration Filters under Wrong PSF and Noise Estimates

    Directory of Open Access Journals (Sweden)

    Bernués Emiliano

    2007-01-01

    Full Text Available The restoration achieved on the basis of a Wiener scheme is an optimum since the restoration filter is the outcome of a minimisation process. Moreover, the Wiener restoration approach requires the estimation of some parameters related to the original image and the noise, as well as knowledge about the PSF function. However, in a real restoration problem, we may not possess accurate values of these parameters, making results relatively far from the desired optimum. Indeed, a desensitisation process is required to decrease this dependency on the parameter errors of the restoration filter. In this paper, we present an iterative method to reduce the sensitivity of a general restoration scheme (but specified to the Wiener filter with regards to wrong estimates of the said parameters. Within the Fourier transform domain, a sensitivity analysis is tackled in depth with the purpose of defining a number of iterations for each frequency element, which leads to the aimed desensitisation regardless of the errors on estimates. Experimental computations using meaningful values of parameters are addressed. The proposed technique effectively achieves better results than those obtained when using the same wrong estimates in the Wiener approach, as well as verified on an SAR restoration.

  10. Image restoration using regularized inverse filtering and adaptive threshold wavelet denoising

    Directory of Open Access Journals (Sweden)

    Mr. Firas Ali

    2007-01-01

    Full Text Available Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .In this paper a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet denoising stage . The choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet sub band coefficients like standard deviation, arithmetic mean and geometrical mean . The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by this method .Experimental results on test image by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR. Here, to prove the efficiency of this method in image restoration , we have compared this with various restoration methods like Wiener filter alone and inverse filter.

  11. Sources of image degradation in fundamental and harmonic ultrasound imaging using nonlinear, full-wave simulations.

    Science.gov (United States)

    Pinton, Gianmarco F; Trahey, Gregg E; Dahl, Jeremy J

    2011-04-01

    A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-andsum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is reverberation from near-field structures. Reverberation clutter in the harmonic PSF is 26 dB higher than the fundamental PSF. An artificial medium with uniform velocity but unchanged impedance characteristics indicates that for the fundamental PSF, the primary source of degradation is phase aberration. An ultrasound image is created in silico using the same physical and algorithmic process used in an ultrasound scanner: a series of pulses are transmitted through heterogeneous scattering tissue and the received echoes are used in a delay-and-sum beamforming algorithm to generate images. These beamformed images are compared with images obtained from convolution of the PSF with a scatterer field to demonstrate that a very large portion of the PSF must be used to accurately represent the clutter observed in conventional imaging. © 2011 IEEE

  12. ℓ0TV: A new method for image restoration in the presence of impulse noise

    KAUST Repository

    Yuan, Ganzhao

    2015-06-02

    Total Variation (TV) is an effective and popular prior model in the field of regularization-based image processing. This paper focuses on TV for image restoration in the presence of impulse noise. This type of noise frequently arises in data acquisition and transmission due to many reasons, e.g. a faulty sensor or analog-to-digital converter errors. Removing this noise is an important task in image restoration. State-of-the-art methods such as Adaptive Outlier Pursuit(AOP), which is based on TV with L02-norm data fidelity, only give sub-optimal performance. In this paper, we propose a new method, called L0T V -PADMM, which solves the TV-based restoration problem with L0-norm data fidelity. To effectively deal with the resulting non-convex nonsmooth optimization problem, we first reformulate it as an equivalent MPEC (Mathematical Program with Equilibrium Constraints), and then solve it using a proximal Alternating Direction Method of Multipliers (PADMM). Our L0TV-PADMM method finds a desirable solution to the original L0-norm optimization problem and is proven to be convergent under mild conditions. We apply L0TV-PADMM to the problems of image denoising and deblurring in the presence of impulse noise. Our extensive experiments demonstrate that L0TV-PADMM outperforms state-of-the-art image restoration methods.

  13. Radiopacity of restorative composites by conventional radiography and digital images with different resolutions

    Energy Technology Data Exchange (ETDEWEB)

    Dantas, Raquel Venancio; Samento, Hugo Ramalho [Graduate Program in Dentistry, Federal University of Pelotas, Pelotas (Brazil); Duarte, Rosangela Marques; Raso, Sonia Saeger Meireles Monte; De Andrade Ana Karina Maciel; Anjos-Pontual Maria Luiza Dos [Dept. of Operative Dentistry, Federal University of Paraiba, Pelotas (Brazil)

    2013-09-15

    This study was performed to evaluate and compare the radiopacity of dentin, enamel, and 8 restorative composites on conventional radiograph and digital images with different resolutions. Specimens were fabricated from 8 materials and human molars were longitudinally sectioned 1.0 mm thick to include both enamel and dentin. The specimens and tooth sections were imaged by conventional radiograph using 4 sized intraoral film and digital images were taken in high speed and high resolution modes using a phosphor storage plate. Densitometric evaluation of the enamel, dentin, restorative materials, a lead sheet, and an aluminum step wedge was performed on the radiographic images. For the evaluation, the Al equivalent (mm) for each material was calculated. The data were analyzed using one-way ANOVA and Tukey's test (p<0.05), considering the material factor and then the radiographic method factor, individually. The high speed mode allowed the highest radiopacity, while the high resolution mode generated the lowest values. Furthermore, the high resolution mode was the most efficient method for radiographic differentiation between restorative composites and dentin. The conventional radiograph was the most effective in enabling differentiation between enamel and composites. The high speed mode was the least effective in enabling radiographic differentiation between the dental tissues and restorative composites. The high speed mode of digital imaging was not effective for differentiation between enamel and composites. This made it less effective than the high resolution mode and conventional radiographs. All of the composites evaluated showed radiopacity values that fit the ISO 4049 recommendations.

  14. Blurred image restoration using the type of blur and blur parameter identification on the neural network

    Science.gov (United States)

    Aizenberg, Igor N.; Butakoff, Constantine; Karnaukhov, Viktor N.; Merzlyakov, Nikolay S.; Milukova, Olga

    2002-05-01

    As a rule, blur is a form of bandwidth reduction of an ideal image owing to the imperfect image formation process. It can be caused by relative motion between the camera and the original scene, or by an optical system that is out of focus. Today there are different techniques available for solving of the restoration problem including Fourier domain techniques, regularization methods, recursive and iterative filters to name a few. But without knowing at least approximate parameters of the blur, these filters show poor results. If incorrect blur model is chosen then the image will be rather distorted much more than restored. The original solution of the blur and blur parameters identification problem is presented in this paper. A neural network based on multi-valued neurons is used for the blur and blur parameters identification. It is shown that using simple single-layered neural network it is possible to identify the type of the distorting operator. Four types of blur are considered: defocus, rectangular, motion and Gaussian ones. The parameters of the corresponding operator are identified using a similar neural network. After a type of blur and its parameters identification the image can be restored using several kinds of methods. Some fundamentals of image restoration are also considered.

  15. Virtual restoration of cracks in digitized image of paintings

    Energy Technology Data Exchange (ETDEWEB)

    Spagnolo, G Schirripa; Somma, F

    2010-11-01

    An integrated methodology for the detection and removal of cracks on digitized image is presented in this paper. Crack-like pattern detection have been a matter of high concern among researchers mostly for its useful contribution to a variety of applications. The results presented here regard the craquelure of old paintings, however, the same methodology can be used for a much wider set of application. Many images contain similar patterns: crack in protective coating for polymers and other surfaces; fatigue crack in MEMS/NEMS; crack in epoxies used for underfill and encapsulation microelectronics components; etc. In this paper the cracks are detected by thresholding the output of the morphological top-hat transform. Afterwards, the thin dark brush strokes which have been misidentified as cracks are removed using automatic procedure. Finally, crack filling using texture synthesis algorithms. The methodology has been shown to perform very well on digitized images suffering from cracks.

  16. Wavefront Control and Image Restoration with Less Computing

    Science.gov (United States)

    Lyon, Richard G.

    2010-01-01

    PseudoDiversity is a method of recovering the wavefront in a sparse- or segmented- aperture optical system typified by an interferometer or a telescope equipped with an adaptive primary mirror consisting of controllably slightly moveable segments. (PseudoDiversity should not be confused with a radio-antenna-arraying method called pseudodiversity.) As in the cases of other wavefront- recovery methods, the streams of wavefront data generated by means of PseudoDiversity are used as feedback signals for controlling electromechanical actuators of the various segments so as to correct wavefront errors and thereby, for example, obtain a clearer, steadier image of a distant object in the presence of atmospheric turbulence. There are numerous potential applications in astronomy, remote sensing from aircraft and spacecraft, targeting missiles, sighting military targets, and medical imaging (including microscopy) through such intervening media as cells or water. In comparison with prior wavefront-recovery methods used in adaptive optics, PseudoDiversity involves considerably simpler equipment and procedures and less computation. For PseudoDiversity, there is no need to install separate metrological equipment or to use any optomechanical components beyond those that are already parts of the optical system to which the method is applied. In Pseudo- Diversity, the actuators of a subset of the segments or subapertures are driven to make the segments dither in the piston, tilt, and tip degrees of freedom. Each aperture is dithered at a unique frequency at an amplitude of a half wavelength of light. During the dithering, images on the focal plane are detected and digitized at a rate of at least four samples per dither period. In the processing of the image samples, the use of different dither frequencies makes it possible to determine the separate effects of the various dithered segments or apertures. The digitized image-detector outputs are processed in the spatial

  17. Variational approach for restoring blurred images with cauchy noise

    DEFF Research Database (Denmark)

    Sciacchitano, Federica; Dong, Yiqiu; Zeng, Tieyong

    2015-01-01

    model, we add a quadratic penalty term, which guarantees the uniqueness of the solution. Due to the convexity of our model, the primal dual algorithm is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for simultaneously deblurring...... and denoising images corrupted by Cauchy noise. Comparison with other existing and well-known methods is provided as well....

  18. Super-resolution image restoration algorithms based on orthogonal discrete wavelet transform

    Science.gov (United States)

    Liu, Yang-yang; Jin, Wei-qi

    2005-02-01

    Several new super-resolution image restoration algorithms based on orthogonal discrete wavelet transform are proposed, by using orthogonal discrete wavelet transform and generalized cross validation ,and combining with Luck-Richardson super-resolution image restoration algorithm (LR) and Luck-Richardson algorithm based on Poisson-Markov model (MPML). Orthogonal discrete wavelet transform analyzed in both space and frequency domain has the capability of indicating local features of a signal, and concentrating the signal power to a few coefficients in wavelet transform domain. After an original image is "Symlets" orthogonal discrete wavelet transformed, an asymptotically optimal threshold is determined by minimizing generalized cross validation, and high frequency subbands in each decomposition level are denoised with soft threshold processes to converge respectively to those with maximum signal-noise-ratio, when the method is incorporated with existed super-resolution image algorithms, details of original image, especially of those with low signal-noise-ratio, could be well recovered. Single operation wavelet LR algorithm(SWLR),single operation wavelet MPML algorithm(SW-MPML) and MPML algorithm based on single operation and wavelet transform (MPML- SW) are some operative algorithms proposed based on the method. According to the processing results to simulating and practical images , because of the only one operation, under the guarantee of rapid and effective restoration processing, in comparison with LR and MPML, all the proposed algorithms could retain image details better, and be more suitable to low signal-noise-ratio images, They could also reduce operation time for up to hundreds times of iteratives, as well as, avoid the iterative operation of self-adaptive parameters in MPML, improve operating speed and precision. They are practical and instantaneous to some extent in the field of low signal-noise-ratio image restoration.

  19. Full-field optical coherence tomography image restoration based on Hilbert transformation

    Science.gov (United States)

    Na, Jihoon; Choi, Woo June; Choi, Eun Seo; Ryu, Seon Young; Lee, Byeong Ha

    2007-02-01

    We propose the envelope detection method that is based on Hilbert transform for image restoration in full-filed optical coherence tomography (FF-OCT). The FF-OCT system presenting a high-axial resolution of 0.9 μm was implemented with a Kohler illuminator based on Linnik interferometer configuration. A 250 W customized quartz tungsten halogen lamp was used as a broadband light source and a CCD camera was used as a 2-dimentional detector array. The proposed image restoration method for FF-OCT requires only single phase-shifting. By using both the original and the phase-shifted images, we could remove the offset and the background signals from the interference fringe images. The desired coherent envelope image was obtained by applying Hilbert transform. With the proposed image restoration method, we demonstrate en-face imaging performance of the implemented FF-OCT system by presenting a tilted mirror surface, an integrated circuit chip, and a piece of onion epithelium.

  20. Compressive Sensing Image Restoration Using Adaptive Curvelet Thresholding and Nonlocal Sparse Regularization.

    Science.gov (United States)

    Eslahi, Nasser; Aghagolzadeh, Ali

    2016-07-01

    Compressive sensing (CS) is a recently emerging technique and an extensively studied problem in signal and image processing, which suggests a new framework for the simultaneous sampling and compression of sparse or compressible signals at a rate significantly below the Nyquist rate. Maybe, designing an effective regularization term reflecting the image sparse prior information plays a critical role in CS image restoration. Recently, both local smoothness and nonlocal self-similarity have led to superior sparsity prior for CS image restoration. In this paper, first, an adaptive curvelet thresholding criterion is developed, trying to adaptively remove the perturbations appeared in recovered images during CS recovery process, imposing sparsity. Furthermore, a new sparsity measure called joint adaptive sparsity regularization (JASR) is established, which enforces both local sparsity and nonlocal 3-D sparsity in transform domain, simultaneously. Then, a novel technique for high-fidelity CS image recovery via JASR is proposed-CS-JASR. To efficiently solve the proposed corresponding optimization problem, we employ the split Bregman iterations. Extensive experimental results are reported to attest the adequacy and effectiveness of the proposed method comparing with the current state-of-the-art methods in CS image restoration.

  1. Nonlinear imaging (NIM) of flaws in a complex composite stiffened panel using a constructive nonlinear array (CNA) technique.

    Science.gov (United States)

    Malfense Fierro, Gian Piero; Meo, Michele

    2017-02-01

    Recently, there has been high interest in the capabilities of nonlinear ultrasound techniques for damage/defect detection as these techniques have been shown to be quite accurate in imaging some particular type of damage. This paper presents a Constructive Nonlinear Array (CNA) method, for the detection and imaging of material defects/damage in a complex composite stiffened panel. CNA requires the construction of an ultrasound array in a similar manner to standard phased arrays systems, which require multiple transmitting and receiving elements. The method constructively phase-match multiple captured signals at a particular position given multiple transmit positions, similar to the total focusing method (TFM) method. Unlike most of the ultrasonic linear techniques, a longer excitation signal was used to achieve a steady-state excitation at each capturing position, so that compressive and tensile stress at defect/crack locations increases the likelihood of the generation of nonlinear elastic waves. Moreover, the technique allows the reduction of instrumentation nonlinear wave generation by relying on signal attenuation to naturally filter these errors. Experimental tests were carried out on a stiffened panel with manufacturing defects. Standard industrial linear ultrasonic test were carried out for comparison. The proposed new method allows to image damages/defects in a reliable and reproducible manner and overcomes some of the main limitations of nonlinear ultrasound techniques. In particular, the effectiveness and robustness of CNA and the advantages over linear ultrasonic were clearly demonstrated allowing a better resolution and imaging of complex and realistic flaws.

  2. Nonlinear color-image decomposition for image processing of a digital color camera

    Science.gov (United States)

    Saito, Takahiro; Aizawa, Haruya; Yamada, Daisuke; Komatsu, Takashi

    2009-01-01

    This paper extends the BV (Bounded Variation) - G and/or the BV-L1 variational nonlinear image-decomposition approaches, which are considered to be useful for image processing of a digital color camera, to genuine color-image decomposition approaches. For utilizing inter-channel color cross-correlations, this paper first introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G and/or BV-L1 energy functionals, and then derives denoising-type decomposition-algorithms with an over-complete wavelet transform, through applying the Besov-norm approximation to the variational problems. Our methods decompose a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and they achieve desirable high-quality color-image decomposition, which is very robust against colored random noise.

  3. ASSESSMENT OF RESTORATION METHODS OF X-RAY IMAGES WITH EMPHASIS ON MEDICAL PHOTOGRAMMETRIC USAGE

    Directory of Open Access Journals (Sweden)

    S. Hosseinian

    2016-06-01

    Full Text Available Nowadays, various medical X-ray imaging methods such as digital radiography, computed tomography and fluoroscopy are used as important tools in diagnostic and operative processes especially in the computer and robotic assisted surgeries. The procedures of extracting information from these images require appropriate deblurring and denoising processes on the pre- and intra-operative images in order to obtain more accurate information. This issue becomes more considerable when the X-ray images are planned to be employed in the photogrammetric processes for 3D reconstruction from multi-view X-ray images since, accurate data should be extracted from images for 3D modelling and the quality of X-ray images affects directly on the results of the algorithms. For restoration of X-ray images, it is essential to consider the nature and characteristics of these kinds of images. X-ray images exhibit severe quantum noise due to limited X-ray photons involved. The assumptions of Gaussian modelling are not appropriate for photon-limited images such as X-ray images, because of the nature of signal-dependant quantum noise. These images are generally modelled by Poisson distribution which is the most common model for low-intensity imaging. In this paper, existing methods are evaluated. For this purpose, after demonstrating the properties of medical X-ray images, the more efficient and recommended methods for restoration of X-ray images would be described and assessed. After explaining these approaches, they are implemented on samples from different kinds of X-ray images. By considering the results, it is concluded that using PURE-LET, provides more effective and efficient denoising than other examined methods in this research.

  4. Assessment of Restoration Methods of X-Ray Images with Emphasis on Medical Photogrammetric Usage

    Science.gov (United States)

    Hosseinian, S.; Arefi, H.

    2016-06-01

    Nowadays, various medical X-ray imaging methods such as digital radiography, computed tomography and fluoroscopy are used as important tools in diagnostic and operative processes especially in the computer and robotic assisted surgeries. The procedures of extracting information from these images require appropriate deblurring and denoising processes on the pre- and intra-operative images in order to obtain more accurate information. This issue becomes more considerable when the X-ray images are planned to be employed in the photogrammetric processes for 3D reconstruction from multi-view X-ray images since, accurate data should be extracted from images for 3D modelling and the quality of X-ray images affects directly on the results of the algorithms. For restoration of X-ray images, it is essential to consider the nature and characteristics of these kinds of images. X-ray images exhibit severe quantum noise due to limited X-ray photons involved. The assumptions of Gaussian modelling are not appropriate for photon-limited images such as X-ray images, because of the nature of signal-dependant quantum noise. These images are generally modelled by Poisson distribution which is the most common model for low-intensity imaging. In this paper, existing methods are evaluated. For this purpose, after demonstrating the properties of medical X-ray images, the more efficient and recommended methods for restoration of X-ray images would be described and assessed. After explaining these approaches, they are implemented on samples from different kinds of X-ray images. By considering the results, it is concluded that using PURE-LET, provides more effective and efficient denoising than other examined methods in this research.

  5. Projection based image restoration, super-resolution and error correction codes

    Science.gov (United States)

    Bauer, Karl Gregory

    Super-resolution is the ability of a restoration algorithm to restore meaningful spatial frequency content beyond the diffraction limit of the imaging system. The Gerchberg-Papoulis (GP) algorithm is one of the most celebrated algorithms for super-resolution. The GP algorithm is conceptually simple and demonstrates the importance of using a priori information in the formation of the object estimate. In the first part of this dissertation the continuous GP algorithm is discussed in detail and shown to be a projection on convex sets algorithm. The discrete GP algorithm is shown to converge in the exactly-, over- and under-determined cases. A direct formula for the computation of the estimate at the kth iteration and at convergence is given. This analysis of the discrete GP algorithm sets the stage to connect super-resolution to error-correction codes. Reed-Solomon codes are used for error-correction in magnetic recording devices, compact disk players and by NASA for space communications. Reed-Solomon codes have a very simple description when analyzed with the Fourier transform. This signal processing approach to error- correction codes allows the error-correction problem to be compared with the super-resolution problem. The GP algorithm for super-resolution is shown to be equivalent to the correction of errors with a Reed-Solomon code over an erasure channel. The Restoration from Magnitude (RFM) problem seeks to recover a signal from the magnitude of the spectrum. This problem has applications to imaging through a turbulent atmosphere. The turbulent atmosphere causes localized changes in the index of refraction and introduces different phase delays in the data collected. Synthetic aperture radar (SAR) and hyperspectral imaging systems are capable of simultaneously recording multiple images of different polarizations or wavelengths. Each of these images will experience the same turbulent atmosphere and have a common phase distortion. A projection based restoration

  6. Computationally efficient image restoration and super-resolution algorithns for real-time implementation

    Science.gov (United States)

    Sundareshan, Malur K.

    2002-07-01

    Computational complexity is a major impediment to the real- time implementation of image restoration and super- resolution algorithms. Although powerful restoration algorithms have been developed within the last few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require enough number of iterations to be executed to achieve desired resolution gains in order to meaningfully perform detection and recognition tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture mega-pixel imagery data at video frame rates. A major challenge in the processing of these large format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and super- resolution algorithms is of significant practical interest and will be the primary focus of this paper. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate pre-processing and post-processing steps together with the super-resolution iterations in order to tailor optimized overall processing sequences for imagery data of specific formats. Three distinct methods for tailoring a pre-processing filter and integrating it with the super-resolution processing steps will be outlined in this paper. These methods consist of a Region-of-Interest (ROI) extraction scheme, a background- detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared to the super-resolution iterations. A

  7. Image preprocessing for improving computational efficiency in implementation of restoration and superresolution algorithms.

    Science.gov (United States)

    Sundareshan, Malur K; Bhattacharjee, Supratik; Inampudi, Radhika; Pang, Ho-Yuen

    2002-12-10

    Computational complexity is a major impediment to the real-time implementation of image restoration and superresolution algorithms in many applications. Although powerful restoration algorithms have been developed within the past few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require a sufficient number of iterations to be executed to achieve the desired resolution improvement that may be needed to meaningfully perform postprocessing image exploitation tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture megapixel imagery data at video frame rates. A major challenge in the processing of these large-format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and superresolution algorithms is of significant practical interest and is the primary focus of this study. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate preprocessing steps together with the superresolution iterations to tailor optimized overall processing sequences for imagery data of specific formats. For substantiating this assertion, three distinct methods for tailoring a preprocessing filter and integrating it with the superresolution processing steps are outlined. These methods consist of a region-of-interest extraction scheme, a background-detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared with the

  8. Image preprocessing for improving computational efficiency in implementation of restoration and superresolution algorithms

    Science.gov (United States)

    Sundareshan, Malur K.; Bhattacharjee, Supratik; Inampudi, Radhika; Pang, Ho-Yuen

    2002-12-01

    Computational complexity is a major impediment to the real-time implementation of image restoration and superresolution algorithms in many applications. Although powerful restoration algorithms have been developed within the past few years utilizing sophisticated mathematical machinery (based on statistical optimization and convex set theory), these algorithms are typically iterative in nature and require a sufficient number of iterations to be executed to achieve the desired resolution improvement that may be needed to meaningfully perform postprocessing image exploitation tasks in practice. Additionally, recent technological breakthroughs have facilitated novel sensor designs (focal plane arrays, for instance) that make it possible to capture megapixel imagery data at video frame rates. A major challenge in the processing of these large-format images is to complete the execution of the image processing steps within the frame capture times and to keep up with the output rate of the sensor so that all data captured by the sensor can be efficiently utilized. Consequently, development of novel methods that facilitate real-time implementation of image restoration and superresolution algorithms is of significant practical interest and is the primary focus of this study. The key to designing computationally efficient processing schemes lies in strategically introducing appropriate preprocessing steps together with the superresolution iterations to tailor optimized overall processing sequences for imagery data of specific formats. For substantiating this assertion, three distinct methods for tailoring a preprocessing filter and integrating it with the superresolution processing steps are outlined. These methods consist of a region-of-interest extraction scheme, a background-detail separation procedure, and a scene-derived information extraction step for implementing a set-theoretic restoration of the image that is less demanding in computation compared with the

  9. Adaptive contourlet-wavelet iterative shrinkage/thresholding for remote sensing image restoration

    Institute of Scientific and Technical Information of China (English)

    Nu WEN; Shi-zhi YANG; Cheng-jie ZHU; Sheng-cheng CUI

    2014-01-01

    In this paper, we present an adaptive two-step contourlet-wavelet iterative shrinkage/thresholding (TcwIST) algorithm for remote sensing image restoration. This algorithm can be used to deal with various linear inverse problems (LIPs), including image deconvolution and reconstruction. This algorithm is a new version of the famous two-step iterative shrinkage/thresholding (TwIST) algorithm. First, we use the split Bregman Rudin-Osher-Fatemi (ROF) model, based on a sparse dictionary, to decom-pose the image into cartoon and texture parts, which are represented by wavelet and contourlet, respectively. Second, we use an adaptive method to estimate the regularization parameter and the shrinkage threshold. Finally, we use a linear search method to find a step length and a fast method to accelerate convergence. Results show that our method can achieve a signal-to-noise ratio improvement (ISNR) for image restoration and high convergence speed.

  10. Multimodal nonlinear optical imaging of cartilage development in mouse model

    Science.gov (United States)

    He, Sicong; Xue, Wenqian; Sun, Qiqi; Li, Xuesong; Huang, Jiandong; Qu, Jianan Y.

    2017-02-01

    Kinesin-1 is a kind of motor protein responsible for intracellular transportation and has been studied in a variety of tissues. However, its roles in cartilage development are not clear. In this study, a kinesin-1 heavy chain (Kif5b) knockout mouse model is used to study the functions of kinesin-1 in the cartilage development. We developed a multimodal nonlinear optical (NLO) microscope system integrating stimulated Raman scattering (SRS), second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) to investigate the morphological and biomedical characteristics of fresh tibial cartilage from normal and mutant mice at different developmental stages. The combined forward and backward SHG imaging resolved the fine structure of collagen fibrils in the extracellular matrix of cartilage. Meanwhile, the chondrocyte morphology in different zones of cartilage was visualized by label-free SRS and TPEF images. The results show that the fibrillar collagen in the superficial zone of cartilage in postnatal day 10 and 15 (P10 and P15) knockout mice was significantly less than that of control mice. Moreover, we observed distorted morphology and disorganization of columnar arrangement of chondrocytes in the growth plate cartilage of mutant mice. This study reveals the significant roles of kinesin-1 in collagen formation and chondrocyte morphogenesis.

  11. Image restoration techniques based on fuzzy neural networks

    Institute of Scientific and Technical Information of China (English)

    刘普寅; 李洪兴

    2002-01-01

    By establishing some suitable partitions of input and output spaces, a novel fuzzy neuralnetwork (FNN) which is called selection type FNN is developed. Such a system is a multilayerfeedforward neural network, which can be a universal approximator with maximum norm. Based ona family of fuzzy inference rules that are of real senses, a simple and useful inference type FNN isconstructed. As a result, the fusion of selection type FNN and inference type FNN results in a novelfilter-FNN filter. It is simple in structure. And also it is convenient to design the learning algorithmfor structural parameters. Further, FNN filter can efficiently suppress impulse noise superimposed onimage and preserve fine image structure, simultaneously. Some examples are simulated to confirmthe advantages of FNN filter over other filters, such as median filter and adaptive weighted fuzzymean (AWFM) filter and so on, in suppression of noises and preservation of image structure.

  12. A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

    DEFF Research Database (Denmark)

    Dong, Yiqiu; Tieyong Zeng

    2013-01-01

    In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees...... to multiplicative noise. A comparison with other methods is provided as well....

  13. Robust Image Restoration for Ground-Based Space Surveillance

    Science.gov (United States)

    2013-09-01

    the Earth’s atmosphere requires careful mitigation of the turbulence-induced aberration in the observed wave fronts. This is typically achieved...BACKGROUND As we discuss in Jefferies et al. [3], high spatial frequency aberrations of the wave-front phase become increasingly damaging to image...large values of D/r0 where chromatic radial streaking of the PSF speckles is a large part of the PSF morphology. By including temporal and spectral

  14. The trustworthy digital camera: Restoring credibility to the photographic image

    Science.gov (United States)

    Friedman, Gary L.

    1994-02-01

    The increasing sophistication of computers has made digital manipulation of photographic images, as well as other digitally-recorded artifacts such as audio and video, incredibly easy to perform and increasingly difficult to detect. Today, every picture appearing in newspapers and magazines has been digitally altered to some degree, with the severity varying from the trivial (cleaning up 'noise' and removing distracting backgrounds) to the point of deception (articles of clothing removed, heads attached to other people's bodies, and the complete rearrangement of city skylines). As the power, flexibility, and ubiquity of image-altering computers continues to increase, the well-known adage that 'the photography doesn't lie' will continue to become an anachronism. A solution to this problem comes from a concept called digital signatures, which incorporates modern cryptographic techniques to authenticate electronic mail messages. 'Authenticate' in this case means one can be sure that the message has not been altered, and that the sender's identity has not been forged. The technique can serve not only to authenticate images, but also to help the photographer retain and enforce copyright protection when the concept of 'electronic original' is no longer meaningful.

  15. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  16. Image-restoration algorithms for a fully connected architecture.

    Science.gov (United States)

    Abbiss, J B; Brames, B J; Byrne, C L; Fiddy, M A

    1990-06-15

    We describe the implementation of a technique for achieving image superresolution using a fully connected network of simple processors operating in an iterative mode. We show that an updating scheme can be specified that ensures convergence for the serial (asynchronous) updating case. With the appropriate hardware, parallel (synchronous) updating becomes of particular interest because of the potential for accelerated convergence; it is this approach that we envisage implementing in optical hardware. For this case also, we present a convergent scheme that can be related to a regularized form of the Gerchberg-Papoulis algorithm.

  17. An edge-preserving algorithm of joint image restoration and volume reconstruction for rotation-scanning 4D echocardiographic images

    Institute of Scientific and Technical Information of China (English)

    GUO Qiang; YANG Xin

    2006-01-01

    A statistical algorithm for the reconstruction from time sequence echocardiographic images is proposed in this paper.The ability to jointly restore the images and reconstruct the 3D images without blurring the boundary is the main innovation of this algorithm. First, a Bayesian model based on MAP-MRF is used to reconstruct 3D volume, and extended to deal with the images acquired by rotation scanning method. Then, the spatiotemporal nature of ultrasound images is taken into account for the parameter of energy function, which makes this statistical model anisotropic. Hence not only can this method reconstruct 3D ultrasound images, but also remove the speckle noise anisotropically. Finally, we illustrate the experiments of our method on the synthetic and medical images and compare it with the isotropic reconstruction method.

  18. Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

    Science.gov (United States)

    Dong, Jian; Kudo, Hiroyuki

    2017-03-01

    Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

  19. An improved method for polarimetric image restoration in interferometry

    CERN Document Server

    Pratley, Luke

    2016-01-01

    Interferometric radio astronomy data require the effects of limited coverage in the Fourier plane to be accounted for via a deconvolution process. For the last 40 years this process, known as `cleaning', has been performed almost exclusively on all Stokes parameters individually as if they were independent scalar images. However, here we demonstrate for the case of the linear polarisation $\\mathcal{P}$, this approach fails to properly account for the complex vector nature resulting in a process which is dependant on the axis under which the deconvolution is performed. We present here an improved method, `Generalised Complex CLEAN', which properly accounts for the complex vector nature of polarised emission and is invariant under rotations of the deconvolution axis. We use two Australia Telescope Compact Array datasets to test standard and complex CLEAN versions of the H\\"{o}gbom and SDI CLEAN algorithms. We show that in general the Complex CLEAN version of each algorithm produces more accurate clean component...

  20. An improved method for polarimetric image restoration in interferometry

    Science.gov (United States)

    Pratley, Luke; Johnston-Hollitt, Melanie

    2016-11-01

    Interferometric radio astronomy data require the effects of limited coverage in the Fourier plane to be accounted for via a deconvolution process. For the last 40 years this process, known as `cleaning', has been performed almost exclusively on all Stokes parameters individually as if they were independent scalar images. However, here we demonstrate for the case of the linear polarization P, this approach fails to properly account for the complex vector nature resulting in a process which is dependent on the axes under which the deconvolution is performed. We present here an improved method, `Generalized Complex CLEAN', which properly accounts for the complex vector nature of polarized emission and is invariant under rotations of the deconvolution axes. We use two Australia Telescope Compact Array data sets to test standard and complex CLEAN versions of the Högbom and SDI (Steer-Dwedney-Ito) CLEAN algorithms. We show that in general the complex CLEAN version of each algorithm produces more accurate clean components with fewer spurious detections and lower computation cost due to reduced iterations than the current methods. In particular, we find that the complex SDI CLEAN produces the best results for diffuse polarized sources as compared with standard CLEAN algorithms and other complex CLEAN algorithms. Given the move to wide-field, high-resolution polarimetric imaging with future telescopes such as the Square Kilometre Array, we suggest that Generalized Complex CLEAN should be adopted as the deconvolution method for all future polarimetric surveys and in particular that the complex version of an SDI CLEAN should be used.

  1. Remotely sensed image restoration using partial differential equations and watershed transformation

    Science.gov (United States)

    Nazari, Avishan; Zehtabian, Amin; Gribaudo, Marco; Ghassemian, Hassan

    2015-02-01

    This paper proposes a novel approach for remotely sensed image restoration. The main goal of this study is to mitigate two most well-known types of noises from remote sensing images while their important details such as edges are preserved. To this end, a novel method based on partial differential equations is proposed. The parameters used in the proposed algorithm are adaptively set regarding the type of noise and the texture of noisy datasets. Moreover, we propose to apply a segmentation pre-processing step based on Watershed transformation to localize the denoising process. The performance of the restoration techniques is measured using PSNR criterion. For further assessment, we also feed the original/noisy/denoised images into SVM classifier and explore the results.

  2. Improving spatial resolution of confocal Raman microscopy by super-resolution image restoration.

    Science.gov (United States)

    Cui, Han; Zhao, Weiqian; Wang, Yun; Fan, Ying; Qiu, Lirong; Zhu, Ke

    2016-05-16

    A new super-resolution image restoration confocal Raman microscopy method (SRIR-RAMAN) is proposed for improving the spatial resolution of confocal Raman microscopy. This method can recover the lost high spatial frequency of the confocal Raman microscopy by using Poisson-MAP super-resolution imaging restoration, thereby improving the spatial resolution of confocal Raman microscopy and realizing its super-resolution imaging. Simulation analyses and experimental results indicate that the spatial resolution of SRIR-RAMAN can be improved by 65% to achieve 200 nm with the same confocal Raman microscopy system. This method can provide a new tool for high spatial resolution micro-probe structure detection in physical chemistry, materials science, biomedical science and other areas.

  3. A Comparison of Solar Image Restoration Techniques for SST/CRISP Data (Summary)

    Science.gov (United States)

    Löfdahl, M.

    2016-04-01

    Solar images from high-resolution, ground-based telescopes are corrected for the blurring effects of atmospheric turbulence by use of adaptive optics and post-facto image restoration. Two classes of image restoration methods are regularly used today, those based on Multi-Frame Blind Deconvolution (MFBD; Löfdahl 2002) and those based on Speckle Interferometry (SI; von der Luhe &Dunn 1987). In a recently started project, we will compare and evaluate such methods for use with spectropolarimetric data from the CRisp Imaging SpectroPolarimeter (CRISP; Scharmer et al. 2008) of the Swedish 1-meter Solar Telescope (SST; Scharmer et al. 2003). For SST/CRISP data we routinely use the Multi-Object MFBD (MOMFBD; van Noort et al. 2005) technique to jointly restore images collected from a wideband camera and from the narrowband cameras behind the CRISP FPI and polarimetry optics. This crucial step in the data reduction pipeline of CRISP (CRISPRED; de la Cruz Rodríguez et al. 2015) is carefully integrated with the application of various procedures that are designed to reduce effects of imperfections in the instruments. In order to make the comparison as fair as possible, we have extended CRISPRED so that the Kiepenheuer-Institut Speckle Interferometry Package (KISIP; Wöger & von der Lühe 2008), together with Speckle Deconvolution (SD; Keller & von der Luehe 1992; Mikurda et al. 2006), can serve as a drop in replacement for MOMFBD. The adaption of SI and SD to CRISPRED will allow us to make fair comparisons not only of the restored images, but also of derivative data like Stokes maps and further on to evaluate the consequences of remaining errors and artifacts for the interpretation of physical quantities inferred through atmospheric model inversions.

  4. Majorization-minimization algorithms for wavelet-based image restoration.

    Science.gov (United States)

    Figueiredo, Mário A T; Bioucas-Dias, José M; Nowak, Robert D

    2007-12-01

    Standard formulations of image/signal deconvolution under wavelet-based priors/regularizers lead to very high-dimensional optimization problems involving the following difficulties: the non-Gaussian (heavy-tailed) wavelet priors lead to objective functions which are nonquadratic, usually nondifferentiable, and sometimes even nonconvex; the presence of the convolution operator destroys the separability which underlies the simplicity of wavelet-based denoising. This paper presents a unified view of several recently proposed algorithms for handling this class of optimization problems, placing them in a common majorization-minimization (MM) framework. One of the classes of algorithms considered (when using quadratic bounds on nondifferentiable log-priors) shares the infamous "singularity issue" (SI) of "iteratively reweighted least squares" (IRLS) algorithms: the possibility of having to handle infinite weights, which may cause both numerical and convergence issues. In this paper, we prove several new results which strongly support the claim that the SI does not compromise the usefulness of this class of algorithms. Exploiting the unified MM perspective, we introduce a new algorithm, resulting from using l1 bounds for nonconvex regularizers; the experiments confirm the superior performance of this method, when compared to the one based on quadratic majorization. Finally, an experimental comparison of the several algorithms, reveals their relative merits for different standard types of scenarios.

  5. Imaging theory of nonlinear second harmonic and third harmonic generations in confocal microscopy

    Institute of Scientific and Technical Information of China (English)

    TANG; Zhilie; XING; Da; LIU; Songhao

    2004-01-01

    The imaging theory of nonlinear second harmonic generation (SHG) and third harmonic generation (THG) in confocal microscopy is presented in this paper. The nonlinear effect of SHG and THG on the imaging properties of confocal microscopy has been analyzed in detail by the imaging theory. It is proved that the imaging process of SHG and THG in confocal microscopy, which is different from conventional coherent imaging or incoherent imaging, can be divided into two different processes of coherent imaging. The three-dimensional point spread functions (3D-PSF) of SHG and THG confocal microscopy are derived based on the nonlinear principles of SHG and THG. The imaging properties of SHG and THG confocal microscopy are discussed in detail according to its 3D-PSF. It is shown that the resolution of SHG and THG confocal microscopy is higher than that of single-and two-photon confocal microscopy.

  6. VLSI implementation of a nonlinear neuronal model: a "neural prosthesis" to restore hippocampal trisynaptic dynamics.

    Science.gov (United States)

    Hsiao, Min-Chi; Chan, Chiu-Hsien; Srinivasan, Vijay; Ahuja, Ashish; Erinjippurath, Gopal; Zanos, Theodoros P; Gholmieh, Ghassan; Song, Dong; Wills, Jack D; LaCoss, Jeff; Courellis, Spiros; Tanguay, Armand R; Granacki, John J; Marmarelis, Vasilis Z; Berger, Theodore W

    2006-01-01

    We are developing a biomimetic electronic neural prosthesis to replace regions of the hippocampal brain area that have been damaged by disease or insult. We have used the hippocampal slice preparation as the first step in developing such a prosthesis. The major intrinsic circuitry of the hippocampus consists of an excitatory cascade involving the dentate gyrus (DG), CA3, and CA1 subregions; this trisynaptic circuit can be maintained in a transverse slice preparation. Our demonstration of a neural prosthesis for the hippocampal slice involves: (i) surgically removing CA3 function from the trisynaptic circuit by transecting CA3 axons, (ii) replacing biological CA3 function with a hardware VLSI (very large scale integration) model of the nonlinear dynamics of CA3, and (iii) through a specially designed multi-site electrode array, transmitting DG output to the hardware device, and routing the hardware device output to the synaptic inputs of the CA1 subregion, thus by-passing the damaged CA3. Field EPSPs were recorded from the CA1 dendritic zone in intact slices and "hybrid" DG-VLSI-CA1 slices. Results show excellent agreement between data from intact slices and transected slices with the hardware-substituted CA3: propagation of temporal patterns of activity from DG-->VLSI-->CA1 reproduces that observed experimentally in the biological DG-->CA3-->CA1 circuit.

  7. Restoration of solar and star images with phase diversity-based blind deconvolution

    Institute of Scientific and Technical Information of China (English)

    Qiang Li; Sheng Liao; Honggang Wei; Mangzuo Shen

    2007-01-01

    The images recorded by a ground-based telescope are often degraded by atmospheric turbulence and the aberration of the optical system. Phase diversity-based blind deconvolution is an effective post-processing method that can be used to overcome the turbulence-induced degradation. The method uses an ensemble of short-exposure images obtained imultaneously from multiple cameras to jointly estimate the object and the wavefront distribution on pupil. Based on signal estimation theory and optimization theory, we derive the cost function and solve the large-scale optimization problem using a limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method. We apply the method to the urbulence degraded images generated with computer, the solar images acquired with the swedish vacuum solar telescope (SVST, 0.475m) in La Paima and the star images collected with 1.2-m telescope in Yunnan Observatory. In order to avoid edge effect in the restoration of the solar images, a modified Hanning apodized window is adopted.The star image till can be estored when the defocus distance is measured inaccurately. The restored results demonstrate that the method is efficient for removing the effect of turbulence and reconstructing the point-like or extended objects.

  8. Accuracy assessment of blind and semi-blind restoration methods for hyperspectral images

    Science.gov (United States)

    Zhang, Mo; Vozel, Benoit; Chehdi, Kacem; Uss, Mykhail; Abramov, Sergey; Lukin, Vladimir

    2016-10-01

    Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. When no knowledge is available about the degradations present or the original image, blind restoration methods must be considered. Otherwise, when a partial information is needed, semi-blind restoration methods can be considered. Numerous semi-blind and quite advanced methods are available in the literature. So to get better insights and feedback on the applicability and potential efficiency of a representative set of four semi-blind methods recently proposed, we have performed a comparative study of these methods in objective terms of blur filter and original image error estimation accuracy. In particular, we have paid special attention to the accurate recovering in the spectral dimension of original spectral signatures. We have analyzed peculiarities and factors restricting the applicability of these methods. Our tests are performed on a synthetic hyperspectral image, degraded with various synthetic blurs (out-of-focus, gaussian, motion) and with signal independent noise of typical levels such as those encountered in real hyperspectral images. This synthetic image has been built from various samples from classified areas of a real-life hyperspectral image, in order to benefit from realistic reference spectral signatures to recover after synthetic degradation. Conclusions, practical recommendations and perspectives are drawn from the results experimentally obtained.

  9. A generalized accelerated proximal gradient approach for total-variation-based image restoration.

    Science.gov (United States)

    Zuo, Wangmeng; Lin, Zhouchen

    2011-10-01

    This paper proposes a generalized accelerated proximal gradient (GAPG) approach for solving total variation (TV)-based image restoration problems. The GAPG algorithm generalizes the original APG algorithm by replacing the Lipschitz constant with an appropriate positive-definite matrix, resulting in faster convergence. For TV-based image restoration problems, we further introduce two auxiliary variables that approximate the partial derivatives. Constraints on the variables can easily be imposed without modifying the algorithm much, and the TV regularization can be either isotropic or anisotropic. As compared with the recently developed APG-based methods for TV-based image restoration, i.e., monotone version of the two-step iterative shrinkage/thresholding algorithm (MTwIST) and monotone version of the fast IST algorithm (MFISTA), our GAPG is much simpler as it does not require to solve an image denoising subproblem. Moreover, the convergence rate of O(k(-2)) is maintained by our GAPG, where k is the number of iterations; the cost of each iteration in GAPG is also lower. As a result, in our experiments, our GAPG approach can be much faster than MTwIST and MFISTA. The experiments also verify that our GAPG converges faster than the original APG and MTwIST when they solve identical problems.

  10. Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations.

    Science.gov (United States)

    Li, Laquan; Wang, Jian; Lu, Wei; Tan, Shan

    2017-02-01

    Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L2 regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L2 regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin's lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial

  11. Non-linearly weighted fuzzy correlation for color-image retrieval

    Institute of Scientific and Technical Information of China (English)

    Guoguang Mu(母国光); Hongchen Zhai(翟宏琛); Siyuan Zhang(张思远)

    2003-01-01

    An algorithm with non-linear weight factors in the summation process for fuzzy correlation of color his-tograms is presented, in which non-linear weights are assigned to some characteristic colors of interest.Experimental results show that this can improve the retrieval of color images with partial aberrations orwith local color characters.

  12. Restoration of distorted colour microscopic images from transverse chromatic aberration of imperfect lenses.

    Science.gov (United States)

    Wu, H-S; Murray, J; Morgello, S; Fiel, M I; Schiano, T; Kalir, T; Deligdisch, L; Gil, J

    2011-02-01

    An algorithm is presented for restoration of colour microscopic images with distortions from imperfect microscope lenses having transverse chromatic aberrations, resulting in a magnification that slightly varies with wavelengths or colours. The differential of each colour component image is computed as the difference between the component image and its slightly magnified version. The absolute values in the differential component images are generally higher at the edges where greater discontinuities occur. The two cross-correlation functions of the absolute differentials between red and green colours and between red and blue colours are then computed. The maximum in the two cross-correlation functions were sought, respectively, and the cross-correlation delays were then calculated. The two cross-correlation delays were used to determine dispersions and to realign the three colour components. Results of real microscopic images are provided. The restored image and the original are compared both visually and quantitatively in terms of the estimated entropies measured for the degree of concentrations using vector distributions.

  13. EXISTENCE AND UNIQUENESS OF WEAK SOLUTIONS FOR A NONLINEAR PARABOLIC EQUATION RELATED TO IMAGE ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    Wang Lihe; Zhou Shulin

    2006-01-01

    In this paper we establish the existence and uniqueness of weak solutions for the initial-boundary value problem of a nonlinear parabolic partial differential equation, which is related to the Malik-Perona model in image analysis.

  14. Image restoration with surface-based fourth-order partial differential equation

    Science.gov (United States)

    Lu, Bibo; Liu, Qiang

    2010-07-01

    This paper presents an edge-preserving fourth order partial differential equation (PDE) for image restoration derived from a new surface-based energy functional. The corresponding fourth order PDE can preserve edges and avoid the staircase effect. The proposed model contains a function of gradient norm as an edge detector, which controls the diffusion speed according to the local structure of the image and preserves more details. Denoising results are given and we have also compared our method with some related PDE models.

  15. The Analytic Hierarchy Method-Based Algorithm for Restoring Broken Pixels on the Noisy Images

    Directory of Open Access Journals (Sweden)

    S. V. Belim

    2014-01-01

    Full Text Available This article presents an algorithm for restoring broken pixels, which can appear in graphic files with statistical gaps. The suggested algorithm is based on the method of hierarchical analysis of the decision support theory. The choice of the broken pixel color depends on the nearest neighbors and their next neighbors. Three parameters inherent in each nearest neighbor are analysed. Firstly, it is the number of neighbors, which have the same color as the given nearest neighbor. Secondly, it is a deviation of the given pixel from the average value of its neighbors. Thirdly, it is a difference between the pixels being on the opposite sides of the broken pixel. Based on these three criteria, for each nearest neighbor of the broken pixel, a weight coefficient is defined. A hierarchical two-level tree for making decision is constructed. As a color of the broken pixel, its neighbor color with the maximum weight is chosen.A computer experiment to determine the effectiveness of the proposed method is conducted. The effectiveness of the proposed method was determined by comparing the similarity degree of the broken and restored images to the source image. To compare images Minkowski metric was used. To conduct experiments photographic and artificial images were used. The paper investigates a dependence of the proposed algorithm efficiency on the broken image amount. It was found out that the proposed algorithm has the advantage over the known algorithms for restoring broken pixels near the sharp edges. An image restored by our method has more sharply defined edges as compared to what the smoothing filters provide. The proposed method can be iteratively applied. As the experiments have shown, the first five iterations provide image enhancement.The proposed method together with the algorithms for detecting the broken pixels can be used to design filters of noisy images. The method efficiency enhancement can be achieved in case of taking into account the

  16. Nonlocal image restoration with bilateral variance estimation: a low-rank approach.

    Science.gov (United States)

    Dong, Weisheng; Shi, Guangming; Li, Xin

    2013-02-01

    Simultaneous sparse coding (SSC) or nonlocal image representation has shown great potential in various low-level vision tasks, leading to several state-of-the-art image restoration techniques, including BM3D and LSSC. However, it still lacks a physically plausible explanation about why SSC is a better model than conventional sparse coding for the class of natural images. Meanwhile, the problem of sparsity optimization, especially when tangled with dictionary learning, is computationally difficult to solve. In this paper, we take a low-rank approach toward SSC and provide a conceptually simple interpretation from a bilateral variance estimation perspective, namely that singular-value decomposition of similar packed patches can be viewed as pooling both local and nonlocal information for estimating signal variances. Such perspective inspires us to develop a new class of image restoration algorithms called spatially adaptive iterative singular-value thresholding (SAIST). For noise data, SAIST generalizes the celebrated BayesShrink from local to nonlocal models; for incomplete data, SAIST extends previous deterministic annealing-based solution to sparsity optimization through incorporating the idea of dictionary learning. In addition to conceptual simplicity and computational efficiency, SAIST has achieved highly competent (often better) objective performance compared to several state-of-the-art methods in image denoising and completion experiments. Our subjective quality results compare favorably with those obtained by existing techniques, especially at high noise levels and with a large amount of missing data.

  17. Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm

    CERN Document Server

    Altmann, Yoann; Tourneret, Jean-Yves

    2013-01-01

    This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are post-nonlinear functions of unknown pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomials leading to a polynomial post-nonlinear mixing model. A Bayesian algorithm is proposed to estimate the parameters involved in the model yielding an unsupervised nonlinear unmixing algorithm. Due to the large number of parameters to be estimated, an efficient Hamiltonian Monte Carlo algorithm is investigated. The classical leapfrog steps of this algorithm are modified to handle the parameter constraints. The performance of the unmixing strategy, including convergence and parameter tuning, is first evaluated on synthetic data. Simulations conducted with real data finally show the accuracy of the proposed unmixing strategy for the analysis of hyperspectral images.

  18. Direct optical imaging of graphene in vitro by nonlinear femtosecond laser spectral reshaping.

    Science.gov (United States)

    Li, Baolei; Cheng, Yingwen; Liu, Jie; Yi, Congwen; Brown, April S; Yuan, Hsiangkuo; Vo-Dinh, Tuan; Fischer, Martin C; Warren, Warren S

    2012-11-14

    Nonlinear optical microscopy, based on femtosecond laser spectral reshaping, characterized and imaged graphene samples made from different methods, both on slides and in a biological environment. This technique clearly discriminates between graphene flakes with different numbers of layers and reveals the distinct nonlinear optical properties of reduced graphene oxide as compared to mechanically exfoliated or chemical vapor deposition grown graphene. The nonlinearity makes it applicable to scattering samples (such as tissue) as opposed to previous methods, such as transmission. This was demonstrated by high-resolution imaging of breast cancer cells incubated with graphene flakes.

  19. AIG Based Nonlinear Anisotropic Smoothing Strategy for Vector-Valued Images

    Institute of Scientific and Technical Information of China (English)

    ZHANG Xiang-fen; TIAN Wei-feng; CHEN Wu-fan; YE Hong

    2009-01-01

    The effects of the Rician noise on the calculated tensors are analyzed and an affine invariant gradient (AIG) based nonlinear anisotropic smoothing strategy is presented. The AIG based smoothing strategy is a development of the affine invariant nonlinear anisotropic diffusion (AINAD) restoration model, introduced by Guillermo Sapiro, and adopted to restore vector-valued data. To evaluate the efficiency of the presented AINAD model in accounting for the Rician noise introduced into the vector-valued data, the peak-to-peak signal-to-noise ratio (PSNR), signal-to-mean squared error ratio (SMSE) and Beta(parameter that stands for edge preservation) metrics are used. The experiment results acquired from the synthetic and real data prove the good performance of the presented filter.

  20. Image quality assessment method based on nonlinear feature extraction in kernel space

    Institute of Scientific and Technical Information of China (English)

    Yong DING‡; Nan LI; Yang ZHAO; Kai HUANG

    2016-01-01

    To match human perception, extracting perceptual features effectively plays an important role in image quality assessment. In contrast to most existing methods that use linear transformations or models to represent images, we employ a complex mathematical expression of high dimensionality to reveal the statistical characteristics of the images. Furthermore, by introducing kernel methods to transform the linear problem into a nonlinear one, a full-reference image quality assessment method is proposed based on high-dimensional nonlinear feature extraction. Experiments on the LIVE, TID2008, and CSIQ databases demonstrate that nonlinear features offer competitive performance for image inherent quality representation and the proposed method achieves a promising performance that is consistent with human subjective evaluation.

  1. Combined statistical regularization and experiment-design-theory-based nonlinear techniques for extended objects imaging from remotely sensed data

    Science.gov (United States)

    Kostenko, Yuri T.; Shkvarko, Yuri V.

    1994-06-01

    The aim of this presentation is to address a new theoretic approach to the problem of the development of remote sensing imaging (RSI) nonlinear techniques that exploit the idea of fusion the experiment design and statistical regularization theory-based methods for inverse problems solution optimal/suboptimal in the mixed Bayesian-regularization setting. The basic purpose of such the information fusion-based methodology is twofold, namely, to design the appropriate system- oriented finite-dimensional model of the RSI experiment in the terms of projection schemes for wavefield inversion problems, and to derive the two-stage estimation techniques that provide the optimal/suboptimal restoration of the power distribution in the environment from the limited number of the wavefield measurements. We also discuss issues concerning the available control of some additional degrees of freedom while such an RSI experiment is conducted.

  2. Wide-area image restoration using a new iterative registration method

    Science.gov (United States)

    Fraser, Donald; Lambert, Andrew J.

    2000-11-01

    Over a wide field of view (e.g., 100 arcsec in optical astronomy) the point spread function due to atmospheric effects is found to be far form position invariant, and appears as a combination of local warping and local blurring. Recently, we discussed a method in which the first step in restoration is to register all points in every frame of a movie sequence to the corresponding points in a prototype image. After registration, each frame is de- warped and summed to form an average, motion-blur corrected result. Previously, we applied a hierarchical, windowed cross correlation process to obtain local x and y registration information, similar to common methods in stereo cartography. We discuss a new approach to image registration for this purpose. Suppose two images to be registered differ mainly in varying random, but spatially coherent warping (such as occurs as one effect of a slowly varying wavefront tip-tilt over a wide field of vies). Imagine that one image, the reference image, is represented by a solid surface corresponding to its intensity distribution. Imagine that the second image is also represented by a surface, but in the form of a flexible, rubber mold. If the two images are identical, then the mold fits the solid like a glove. If one image includes local warping relative to the other, then the mold or glove must be forced to fit though local distortions.

  3. Automated, non-linear registration between 3-dimensional brain map and medical head image

    Energy Technology Data Exchange (ETDEWEB)

    Mizuta, Shinobu; Urayama, Shin-ichi; Zoroofi, R.A.; Uyama, Chikao [National Cardiovascular Center, Suita, Osaka (Japan)

    1998-05-01

    In this paper, we propose an automated, non-linear registration method between 3-dimensional medical head image and brain map in order to efficiently extract the regions of interest. In our method, input 3-dimensional image is registered into a reference image extracted from a brain map. The problems to be solved are automated, non-linear image matching procedure, and cost function which represents the similarity between two images. Non-linear matching is carried out by dividing the input image into connected partial regions, transforming the partial regions preserving connectivity among the adjacent images, evaluating the image similarity between the transformed regions of the input image and the correspondent regions of the reference image, and iteratively searching the optimal transformation of the partial regions. In order to measure the voxelwise similarity of multi-modal images, a cost function is introduced, which is based on the mutual information. Some experiments using MR images presented the effectiveness of the proposed method. (author)

  4. Coupled nonlinear-diffusion color image sharpening based on the chromaticity-brightness model

    Science.gov (United States)

    Saito, Takahiro; Nosaka, Reina; Komatsu, Takashi

    2006-01-01

    Previously we have presented a selective image sharpening method based on the coupled nonlinear diffusion process composed of a nonlinear diffusion term, a fidelity term and an isotropic peaking term, and it can sharpen only blurred edges without increasing the noise visibility. Our previously presented prototypal color-image sharpening methods based on the coupled nonlinear-diffusion process have been formulated on the linear color models, namely, the channel-bychannel model and the 3D vectorial model. Our prototypal methods can sharpen blurred color step edges, but they do not necessarily enhance contrasts of signal variations in complex texture image regions so well as in simple step-edge regions. To remedy the drawback, this paper extends our coupled nonlinear-diffusion color-image sharpening method to the nonlinear non-flat color model, namely, the chromaticity-brightness model, which is known to be closely relating to human color perception. We modify our time-evolution PDE's for the non-flat space of the chromaticity vector and present its digital implementations. Through experimental simulations, we compare our new color-image sharpening method based on the chromaticity-brightness model with our prototypal color-image sharpening methods based on the linear color models.

  5. Optimal selection of regularization parameter for l1-based image restoration based on SURE

    Science.gov (United States)

    Xue, Feng; Liu, Xin; Liu, Hongyan; Liu, Jiaqi

    2016-10-01

    To exploit the sparsity in transform domain (e.g. wavelets), the image deconvolution can be typically formulated as a l1-penalized minimization problem, which, however, generally requires proper selection of regularization parameter for desired reconstruction quality. The key contribution of this paper is to develop a novel data-driven scheme to optimize regularization parameter, such that the resultant restored image achieves minimum prediction error (p-error). First, we develop Stein's unbiased risk estimate (SURE), an unbiased estimate of p-error, for image degradation model. Then, we propose a recursive evaluation of SURE for the basic iterative shrinkage/thresholding (IST), which enables us to find the optimal value of regularization parameter by exhaustive search. The numerical experiments show that the proposed SURE-based optimization leads to nearly optimal deconvolution performance in terms of peak signal-to-noise ratio (PSNR).

  6. Missing pixels restoration for remote sensing images using adaptive search window and linear regression

    Science.gov (United States)

    Tai, Shen-Chuan; Chen, Peng-Yu; Chao, Chian-Yen

    2016-07-01

    The Consultative Committee for Space Data Systems proposed an efficient image compression standard that can do lossless compression (CCSDS-ICS). CCSDS-ICS is the most widely utilized standard for satellite communications. However, the original CCSDS-ICS is weak in terms of error resilience with even a single incorrect bit possibly causing numerous missing pixels. A restoration algorithm based on the neighborhood similar pixel interpolator is proposed to fill in missing pixels. The linear regression model is used to generate the reference image from other panchromatic or multispectral images. Furthermore, an adaptive search window is utilized to sieve out similar pixels from the pixels in the search region defined in the neighborhood similar pixel interpolator. The experimental results show that the proposed methods are capable of reconstructing missing regions with good visual quality.

  7. Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets

    KAUST Repository

    Lenzen, F.

    2014-01-01

    © 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied both theoretical and numerical issues. While we were able to show the existence of solutions for a relatively broad class of problems, we encountered difficulties concerning uniqueness of the solution as well as convergence of existing algorithms for solving QVIs. In particular, it seemed that with increasing image size the growing condition number of the involved differential operator posed severe problems. In the present paper we prove uniqueness for a larger class of problems, particularly independent of the image size. Moreover, we provide a numerical algorithm with proved convergence. Experimental results support our theoretical findings.

  8. Metal Artifact Reduction from Computed Tomography (CT Images using Directional Restoration Filter

    Directory of Open Access Journals (Sweden)

    Mithun Kumar PK

    2014-05-01

    Full Text Available Computed tomography angiography (CTA is a stabilized tool for vessel imaging in the medical image processing field. High-intense structures in the contrast image can seriously hamper luminal visualization. Metal artifacts are an extensive problem in computed tomography (CT images. We proposed directional restoration filtering process with Fuzzy logic in order to reduce metal artifact from CT images. We create two sets by iteration process and these sets will be sorted in ascending order. After sorting we take two elements from two data sets and the tracking both elements will be selected from the second position of those sorting arrays. Intersection Fuzzy logic will be executed between two selected elements and Gaussian convolution operation will be performed in the entire images because of enhancement the artifact affected CT images. In this paper, we investigated a fully automated intensity-based filter and it depends on the gray level variation rating. This results in a better visualization of the vessel lumen, also of the smaller vessels, allowing a faster and more accurate inspection of the whole vascular structures.

  9. Classifying content-based Images using Self Organizing Map Neural Networks Based on Nonlinear Features

    Directory of Open Access Journals (Sweden)

    Ebrahim Parcham

    2014-07-01

    Full Text Available Classifying similar images is one of the most interesting and essential image processing operations. Presented methods have some disadvantages like: low accuracy in analysis step and low speed in feature extraction process. In this paper, a new method for image classification is proposed in which similarity weight is revised by means of information in related and unrelated images. Based on researchers’ idea, most of real world similarity measurement systems are nonlinear. Thus, traditional linear methods are not capable of recognizing nonlinear relationship and correlation in such systems. Undoubtedly, Self Organizing Map neural networks are strongest networks for data mining and nonlinear analysis of sophisticated spaces purposes. In our proposed method, we obtain images with the most similarity measure by extracting features of our target image and comparing them with the features of other images. We took advantage of NLPCA algorithm for feature extraction which is a nonlinear algorithm that has the ability to recognize the smallest variations even in noisy images. Finally, we compare the run time and efficiency of our proposed method with previous proposed methods.

  10. Constructive role of sensors nonlinearities in the acquisition of partially polarized speckle images

    Energy Technology Data Exchange (ETDEWEB)

    Delahaies, Agnes; Rousseau, David; Chapeau-Blondeau, Francois [Laboratoire d' Ingenierie des Systemes Automatises (LISA), Universite d' Angers, 62 avenue Notre Dame du Lac, 49000 Angers (France); Gindre, Denis, E-mail: david.rousseau@univ-angers.f [Laboratoire des Proprietes Optiques des Materiaux et Applications (POMA), Universite d' Angers, 2 boulevard Lavoisier, 49000 Angers (France)

    2010-02-01

    We study the impact of the level of the speckle noise on data acquisition in a partially polarized coherent imaging system with the presence of a nonlinearity in the imaging sensor characteristic. In perfectly linear acquisition conditions, due to the essentially multiplicative action of the speckle, the image contrast is unchanged as the speckle noise level increases, and so it has no impact on the quality of the acquired images. On the contrary, in nonlinear conditions the acquisition is affected by the speckle noise level. However, this effect of the speckle is not always detrimental. We show that, in definite nonlinear conditions, there is usually an optimal level of the speckle noise that leads to a maximum quality of the acquired images. We theoretically analyze such nonlinear regimes with partially polarized speckled images. We specifically exhibit the existence of an optimal speckle noise level in the interesting case of images realized only by a depolarization contrast. Illustrations are given with a simple 1-bit hard limiter and binary images. Then, we propose and discuss as perspectives an experimental optical setup to confront theory and experiment.

  11. Improvement of nonlinear diffusion equation using relaxed geometric mean filter for low PSNR images

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan

    2013-01-01

    A new method to improve the performance of low PSNR image denoising is presented. The proposed scheme estimates edge gradient from an image that is regularised with a relaxed geometric mean filter. The proposed method consists of two stages; the first stage consists of a second order nonlinear...... anisotropic diffusion equation with new neighboring structure and the second is a relaxed geometric mean filter, which processes the output of nonlinear anisotropic diffusion equation. The proposed algorithm enjoys the benefit of both nonlinear PDE and relaxed geometric mean filter. In addition, the algorithm...... will not introduce any artefacts, and preserves image details, sharp corners, curved structures and thin lines. Comparison of the results obtained by the proposed method, with those of other methods, shows that a noticeable improvement in the quality of the denoised images, that were evaluated subjectively...

  12. Research of nonlinear simulation on sweep voltage of streak tube imaging lidar

    Science.gov (United States)

    Zhai, Qian; Han, Shao-kun; Zhai, Yu; Lei, Jie-yu; Yao, Jian-feng

    2016-10-01

    In order to study the influence of nonlinear sweep voltage on the range accuracy of streak tube imaging lidar, a nonlinear distance model of streak tube is proposed. The model of the parallel-plate deflection system is studied, and the mathematical relation between the sweep voltage and the position of the image point on the screen is obtained based on the movement rule of phoelectron. And the mathematical model of the sweep voltage is established on the basis of its principle. The simulation of streak image is carried out for the selected staircase target, the range image of the target can be reconstructed by extremum method. Comparing reconstruction result and actual target, the range accuracy caused by the nonlinear sweep voltage is obtained. The curve of the errors varying with target ranges is also obtained. And the range accuracy of the system is analyzed by the means of changing the parameter relate to sweep time.

  13. Optical coherence tomography based imaging of dental demineralisation and cavity restoration in 840 nm and 1310 nm wavelength regions

    Science.gov (United States)

    Damodaran, Vani; Rao, Suresh Ranga; Vasa, Nilesh J.

    2016-08-01

    In this paper, a study of in-house built optical coherence tomography (OCT) system with a wavelength of 840 nm for imaging of dental caries, progress in demineralisation and cavity restoration is presented. The caries when imaged with the 840 nm OCT system showed minute demineralisation in the order of 5 μm. The OCT system was also proposed to study the growth of lesion and this was demonstrated by artificially inducing caries with a demineralisation solution of pH 4.8. The progress of carious lesion to a depth of about 50-60 μm after 60 hours of demineralisation was clearly observed with the 840 nm OCT system. The tooth samples were subjected to accelerated demineralisation condition at pH of approximately 2.3 to study the adverse effects and the onset of cavity formation was clearly observed. The restoration of cavity was also studied by employing different restorative materials (filled and unfilled). In the case of restoration without filler material (unfilled), the restoration boundaries were clearly observed. Overall, results were comparable with that of the widely used 1310 nm OCT system. In the case of restoration with filler material, the 1310 nm OCT imaging displayed better imaging capacity due to lower scattering than 840 nm imaging.

  14. Determining Optimal Fluorescent Agent Concentrations in Dental Adhesive Resins for Imaging the Tooth/Restoration Interface.

    Science.gov (United States)

    Bim Júnior, Odair; Cebim, Marco A; Atta, Maria T; Machado, Camila M; Francisconi-Dos-Rios, Luciana F; Wang, Linda

    2017-02-01

    Fluorescent dyes like Rhodamine B (RB) have been used to identify the spatial distribution of adhesive restorative materials in the tooth/restoration interface. Potential effects of the addition of RB to dental adhesives were addressed in the past, but no further information is available on how to determine suitable concentrations of RB in these bonding agents for imaging in the confocal laser scanning microscope. This study provides systematical strategies for adding RB to viscous dental adhesive resins, focusing on the determination of the lowest range of dye concentrations necessary to achieve an acceptable image of the dentin/adhesive interface. It was demonstrated that optimized images of the resin distribution in dentin can be produced with 0.1-0.02 mg/mL of RB in the (tested) adhesives. Our approaches took into account aspects related to the dye concentration, photophysical parameters in different host media, specimen composition and morphology to develop a rational use of the fluorescent agent with the resin-based materials. Information gained from this work can help optimize labeling methods using dispersions of low-molecular-weight dyes in different monomer blend systems.

  15. The optical synthetic aperture image restoration based on the improved maximum-likelihood algorithm

    Science.gov (United States)

    Geng, Zexun; Xu, Qing; Zhang, Baoming; Gong, Zhihui

    2012-09-01

    Optical synthetic aperture imaging (OSAI) can be envisaged in the future for improving the image resolution from high altitude orbits. Several future projects are based on optical synthetic aperture for science or earth observation. Comparing with equivalent monolithic telescopes, however, the partly filled aperture of OSAI induces the attenuation of the modulation transfer function of the system. Consequently, images acquired by OSAI instrument have to be post-processed to restore ones equivalent in resolution to that of a single filled aperture. The maximum-likelihood (ML) algorithm proposed by Benvenuto performed better than traditional Wiener filter did, but it didn't work stably and the point spread function (PSF), was assumed to be known and unchanged in iterative restoration. In fact, the PSF is unknown in most cases, and its estimation was expected to be updated alternatively in optimization. Facing these limitations of this method, an improved ML (IML) reconstruction algorithm was proposed in this paper, which incorporated PSF estimation by means of parameter identification into ML, and updated the PSF successively during iteration. Accordingly, the IML algorithm converged stably and reached better results. Experiment results showed that the proposed algorithm performed much better than ML did in peak signal to noise ratio, mean square error and the average contrast evaluation indexes.

  16. Convex half-quadratic criteria and interacting auxiliary variables for image restoration.

    Science.gov (United States)

    Idier, J

    2001-01-01

    This paper deals with convex half-quadratic criteria and associated minimization algorithms for the purpose of image restoration. It brings a number of original elements within a unified mathematical presentation based on convex duality. Firstly, the Geman and Yang's and Geman and Reynolds's constructions are revisited, with a view to establishing the convexity properties of the resulting half-quadratic augmented criteria, when the original nonquadratic criterion is already convex. Secondly, a family of convex Gibbsian energies that incorporate interacting auxiliary variables is revealed as a potentially fruitful extension of the Geman and Reynolds's construction.

  17. Enhanced nonlinear imaging through scattering media using transmission matrix based wavefront shaping

    CERN Document Server

    de Aguiar, Hilton B; Brasselet, Sophie

    2016-01-01

    Despite the tremendous progresses in wavefront control through or inside complex scattering media, several limitations prevent reaching practical feasibility for nonlinear imaging in biological tissues. While the optimization of nonlinear signals might suffer from low signal to noise conditions and from possible artifacts at large penetration depths, it has nevertheless been largely used in the multiple scattering regime since it provides a guide star mechanism as well as an intrinsic compensation for spatiotemporal distortions. Here, we demonstrate the benefit of Transmission Matrix (TM) based approaches under broadband illumination conditions, to perform nonlinear imaging. Using ultrashort pulse illumination with spectral bandwidth comparable but still lower than the spectral width of the scattering medium, we show strong nonlinear enhancements of several orders of magnitude, through thicknesses of a few transport mean free paths, which corresponds to millimeters in biological tissues. Linear TM refocusing ...

  18. Restoration and enhancement of textural properties in SAR images using second-order statistics

    Science.gov (United States)

    Nezry, Edmond; Kohl, Hans-Guenther; De Groof, Hugo

    1994-12-01

    Local second order properties, describing spatial relations between pixels are introduced into the single-point speckle adaptive filtering processes, in order to account for the effects of speckle spatial correlation and to enhance scene textural properties in the restored image. To this end, texture measures originating, first from local grey level co-occurrence matrices (GLCM), and second from the local autocorrelation functions (ACF) are used. Results obtained on 3-look processed ERS-1 FDC and PRI spaceborne images illustrate the performance allowed by the introduction of these texture measures in the structure retaining speckle adaptive filters. The observable texture in remote sensing images is related to the physical spatial resolution of the sensor. For this reason, other spatial speckle decorrelation methods, more simple and easier to implement, for example post-filtering and linear image resampling, are also presented in this paper. In the particular case of spaceborne SAR imagery, all these methods lead to visually similar results. They produce filtered (radar reflectivity) images visually comparable to optical images.

  19. Semi-Huber Quadratic Function and Comparative Study of Some MRFs for Bayesian Image Restoration

    Science.gov (United States)

    De la Rosa, J. I.; Villa-Hernández, J.; González-Ramírez, E.; De la Rosa, M. E.; Gutiérrez, O.; Olvera-Olvera, C.; Castañeda-Miranda, R.; Fleury, G.

    2013-10-01

    The present work introduces an alternative method to deal with digital image restoration into a Bayesian framework, particularly, the use of a new half-quadratic function is proposed which performance is satisfactory compared with respect to some other functions in existing literature. The bayesian methodology is based on the prior knowledge of some information that allows an efficient modelling of the image acquisition process. The edge preservation of objects into the image while smoothing noise is necessary in an adequate model. Thus, we use a convexity criteria given by a semi-Huber function to obtain adequate weighting of the cost functions (half-quadratic) to be minimized. The principal objective when using Bayesian methods based on the Markov Random Fields (MRF) in the context of image processing is to eliminate those effects caused by the excessive smoothness on the reconstruction process of image which are rich in contours or edges. A comparison between the new introduced scheme and other three existing schemes, for the cases of noise filtering and image deblurring, is presented. This collection of implemented methods is inspired of course on the use of MRFs such as the semi-Huber, the generalized Gaussian, the Welch, and Tukey potential functions with granularity control. The obtained results showed a satisfactory performance and the effectiveness of the proposed estimator with respect to other three estimators.

  20. DEVELOPMENT OF OPTIMAL FILTERS OBTAINED THROUGH CONVOLUTION METHODS, USED FOR FINGERPRINT IMAGE ENHANCEMENT AND RESTORATION

    Directory of Open Access Journals (Sweden)

    Cătălin LUPU

    2014-12-01

    Full Text Available This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter, non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting image after applying Canny filter is not ideal. It is possible that the result will be an image with very fragmented edges and many pores in ridge. For the resulting image, a bank of convolution filters are applied one after another (Kirsch, Laplace, Roberts, Prewitt, Sobel, Frei-Chen, averaging convolution filter, circular convolution filter, lapacian convolution filter, gaussian convolution filter, LoG convolution filter, DoG, inverted filters, Wiener, the filter of ”equalization of the power spectrum” (intermediary filter between the Wiener filter and the inverted filter, the geometrical average filter , etc. with different features.

  1. Mammography image restoration based on a radiographic scattering model from a single projection: Experimental study

    Science.gov (United States)

    Kim, Kyuseok; Park, Soyoung; Kim, Guna; Cho, Hyosung; Je, Uikyu; Park, Chulkyu; Lim, Hyunwoo; Lee, Dongyeon; Lee, Hunwoo; Kang, Seokyoon

    2017-03-01

    In conventional mammography, contrast sensitivity remains limited due to the superimposition of breast tissue and scattered X-rays, which induces low visibility of lesions in the breast and, thus, an excessive number of false-positive findings. Several methods, including digital breast tomosynthesis as a multiplanar imaging modality, air-gap and slot techniques for the reduction of scatters, phase-contrast imaging as another image-contrast modality, etc., have been investigated in attempt to overcome these difficulties. However, those techniques typically require a higher imaging dose or special equipment. In this work, as an alternative, we propose a new image restoration method based on a radiographic scattering model in which the intensity of scattered X-rays and the direct transmission function of a given medium are estimated from a single projection by using the dark-channel prior. We implemented the proposed algorithm and performed an experiment to demonstrate its viability. Our results indicate that most of the structures in the examined breast were very discernable even with no adjustment in the display-window level, thus preserving superior image features and edge sharpening.

  2. Adaptive Subspace-based Inverse Projections via Division into Multiple Sub-problems for Missing Image Data Restoration.

    Science.gov (United States)

    Ogawa, Takahiro; Haseyama, Miki

    2016-10-10

    This paper presents adaptive subspace-based inverse projections via division into multiple sub-problems (ASIP-DIMS) for missing image data restoration. In the proposed method, a target problem for estimating missing image data is divided into multiple sub-problems, and each sub-problem is iteratively solved with constraints of other known image data. By projection into a subspace model of image patches, the solution of each subproblem is calculated, where we call this procedure "subspacebased inverse projection" for simplicity. The proposed method can use higher-dimensional subspaces for finding unique solutions in each sub-problem, and successful restoration becomes feasible since a high level of image representation performance can be preserved. This is the biggest contribution of this paper. Furthermore, the proposed method generates several subspaces from known training examples and enables derivation of a new criterion in the above framework to adaptively select the optimal subspace for each target patch. In this way, the proposed method realizes missing image data restoration using ASIP-DIMS. Since our method can estimate any kind of missing image data, its potential in two image restoration tasks, image inpainting and super-resolution, based on several methods for multivariate analysis is also shown in this paper.

  3. Characterization of Periodically Poled Nonlinear Materials Using Digital Image Processing

    Science.gov (United States)

    2008-04-01

    minimize noise. A wiener image filter is a low-pass adaptive filter that using statistics from the underlying image to estimate the noise in the image, in...t = t parameter function y = Gaussian(x,y,t) y = 1/(2.*pi.*t).*exp(-(x.^2+y.^2)/(2.*t)); Listing 2.2: GaussFilter.m % Applies Gaussian image ... filter % I = image % m = Size of filter on a side divided by 2 % t = t parameter % % Creates the specified Gaussian filter and then % applies

  4. Sources of Image Degradation in Fundamental and Harmonic Ultrasound Imaging: A Nonlinear, Full-Wave, Simulation Study

    Science.gov (United States)

    Pinton, Gianmarco F.; Trahey, Gregg E.; Dahl, Jeremy J.

    2011-01-01

    A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-and-sum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is due to reverberation from near-field structures. Compared to fundamental imaging, reverberation clutter in harmonic imaging is 27.1 dB lower. Simulated tissue with uniform velocity but unchanged impedance characteristics indicates that for fundamental imaging, the primary source of degradation is phase aberration. PMID:21507753

  5. Erratum: Sources of Image Degradation in Fundamental and Harmonic Ultrasound Imaging: A Nonlinear, Full-Wave, Simulation Study

    Science.gov (United States)

    Pinton, Gianmarco F.; Trahey, Gregg E.; Dahl, Jeremy J.

    2015-01-01

    A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain. This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-and-sum beamforming is used to generate point spread functions (PSFs) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is due to reverberation from near-field structures. Compared with fundamental imaging, reverberation clutter in harmonic imaging is 27.1 dB lower. Simulated tissue with uniform velocity but unchanged impedance characteristics indicates that for harmonic imaging, the primary source of degradation is phase aberration. PMID:21693410

  6. Optical multiple-image encryption in diffractive-imaging-based scheme using spectral fusion and nonlinear operation.

    Science.gov (United States)

    Qin, Yi; Gong, Qiong; Wang, Zhipeng; Wang, Hongjuan

    2016-11-14

    We report a new method for multiple-image encryption in diffractive-imaging-based encryption (DIBE) scheme. The discrete cosine transformation (DCT) spectra of the primary images are extracted, compacted and then nonlinear-transformed before being sent to the DIBE, where they are encoded into a single intensity pattern. With the help of a suggested phase retrieval algorithm, the original images can be recovered with high quality. Furthermore, due to the introduction of the nonlinear operation, the proposal is demonstrated to be robust to the currently available cryptographic attacks. The proposal probes a new way for multiple-image encryption in DIBE, and its effectiveness and feasibility have been supported by numerical simulations.

  7. Evaluating the Effects of Shadow Detection on QuickBird Image Classification and Spectroradiometric Restoration

    Directory of Open Access Journals (Sweden)

    Marvin E. Bauer

    2013-09-01

    Full Text Available Shadows in high resolution imagery create significant problems for urban land cover classification and environmental application. We first investigated whether shadows were intrinsically different and hypothetically possible to separate from each other with ground spectral measurements. Both pixel-based and object-oriented methods were used to evaluate the effects of shadow detection on QuickBird image classification and spectroradiometric restoration. In each method, shadows were detected and separated either with or without histogram thresholding, and subsequently corrected with a k-nearest neighbor algorithm and a linear correlation correction. The results showed that shadows had distinct spectroradiometric characteristics, thus, could be detected with an optimal brightness threshold and further differentiated with a scene-based near infrared ratio. The pixel-based methods generally recognized more shadow areas and with statistically higher accuracy than the object-oriented methods. The effects of the prior shadow thresholding were not statistically significant. The accuracy of the final land cover classification, after accounting for the shadow detection and separation, was significantly higher for the pixel-based methods than for the object-oriented methods, although both achieved similar accuracy for the non-shadow classes. Both radiometric restoration algorithms significantly reduced shadow areas in the original satellite images.

  8. Multiscale Tikhonov-Total Variation Image Restoration Using Spatially Varying Edge Coherence Exponent.

    Science.gov (United States)

    Prasath, V B Surya; Vorotnikov, Dmitry; Pelapur, Rengarajan; Jose, Shani; Seetharaman, Guna; Palaniappan, Kannappan

    2015-12-01

    Edge preserving regularization using partial differential equation (PDE)-based methods although extensively studied and widely used for image restoration, still have limitations in adapting to local structures. We propose a spatially adaptive multiscale variable exponent-based anisotropic variational PDE method that overcomes current shortcomings, such as over smoothing and staircasing artifacts, while still retaining and enhancing edge structures across scale. Our innovative model automatically balances between Tikhonov and total variation (TV) regularization effects using scene content information by incorporating a spatially varying edge coherence exponent map constructed using the eigenvalues of the filtered structure tensor. The multiscale exponent model we develop leads to a novel restoration method that preserves edges better and provides selective denoising without generating artifacts for both additive and multiplicative noise models. Mathematical analysis of our proposed method in variable exponent space establishes the existence of a minimizer and its properties. The discretization method we use satisfies the maximum-minimum principle which guarantees that artificial edge regions are not created. Extensive experimental results using synthetic, and natural images indicate that the proposed multiscale Tikhonov-TV (MTTV) and dynamical MTTV methods perform better than many contemporary denoising algorithms in terms of several metrics, including signal-to-noise ratio improvement and structure preservation. Promising extensions to handle multiplicative noise models and multichannel imagery are also discussed.

  9. Texture Image Segmentation Based on Nonlinear Diffusion%基于非线性扩散的纹理分割

    Institute of Scientific and Technical Information of China (English)

    张煜

    2008-01-01

    A texture image segmentation based on nonlinear diffusion is presented. The scale of texture can be measured during the process of nonlinear diffusion. A smooth 5-channel vector image with edge preserved, which is composed of inten- sity, scale and orientation of texture image, can be achieved by coupled nonlinear diffusion. A multi-channel statistical region active contour is employed to segment this vector image. The method can be seen as a kind of unsupervised segmentation because parameters are not sensitive to different texture images. Experimental results show its high efficiency in the semi- automatic extraction of texture image.

  10. 大气湍流模糊图像的高分辨力复原算法%High resolution restoration algorithm of atmospheric turbulence blurred image

    Institute of Scientific and Technical Information of China (English)

    李思雯; 徐超; 刘广荣; 金伟其

    2013-01-01

    大气湍流是大气中的一种重要运动形式,它的存在使大气中的动量、热量、水气和污染物的垂直和水平交换作用明显增强,这种干扰作用极大地影响了光电成像系统对于目标的分辨能力。由于湍流影响而退化的图像中同时存在着“幸运区域”,用适当的算法可以获得高分辨力复原图像。为了获取包含“幸运区域”的大气湍流模糊图像,在实验室使用人造湍流,并结合短曝光技术拍摄了大气湍流干扰的序列图像。文中应用矩形交叠分块方法,改进了基于偏微分方程(PDE′s)的序列图像复原算法,对获取的序列短曝光图像进行处理。结果表明,经该算法处理得到的合成图像质量有明显的提升,该算法对大气湍流造成的图像质量退化有较好的复原作用。%Atmospheric turbulence is an important form of movement in the atmosphere, which makes the vertical and horizontal′s exchange interaction of momentum, heat, water vapor and pollutants significantly enhanced, and this interference has a great impact on the target resolution of optical imaging system. There also have "lucky regions" in the degraded images because of turbulence, so the appropriate algorithm can obtain high resolution restored image. To obtain the atmospheric turbulence blurred images which contains "lucky regions", the artificial turbulence was used in the laboratory and combined with the short-exposure technique to take a serial of atmospheric turbulence blurred images. The rectangle overlapped partition method was used and the image restoration algorithm was improved based on nonlinear partial-derivative equations (PDE′s), to process the obtained short exposure serial images. The results show that, the image quality of the composite image is improved obviously, this algorithm has great restoration effect on images′ quality degradation caused by atmospheric turbulence.

  11. Underwater Image Processing: State of the Art of Restoration and Image Enhancement Methods

    Directory of Open Access Journals (Sweden)

    Silvia Corchs

    2010-01-01

    Full Text Available The underwater image processing area has received considerable attention within the last decades, showing important achievements. In this paper we review some of the most recent methods that have been specifically developed for the underwater environment. These techniques are capable of extending the range of underwater imaging, improving image contrast and resolution. After considering the basic physics of the light propagation in the water medium, we focus on the different algorithms available in the literature. The conditions for which each of them have been originally developed are highlighted as well as the quality assessment methods used to evaluate their performance.

  12. In vivo nonlinear spectral imaging in mouse skin

    NARCIS (Netherlands)

    J.A. Palero (Jonathan); H.S. de Bruijn (Riette); A. van der Ploeg-van den Heuvel (Angélique); H.J.C.M. Sterenborg (Dick); H.C. Gerritsen (Hans)

    2006-01-01

    textabstractWe report on two-photon autofluorescence and second harmonic spectral imaging of live mouse tissues. The use of a high sensitivity detector and ultraviolet optics allowed us to record razor-sharp deep-tissue spectral images of weak autofluorescence and short-wavelength second harmonic

  13. Supervised local error estimation for nonlinear image registration using convolutional neural networks

    Science.gov (United States)

    Eppenhof, Koen A. J.; Pluim, Josien P. W.

    2017-02-01

    Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

  14. [Radiation dose reduction using a non-linear image filter in MDCT].

    Science.gov (United States)

    Nakashima, Junya; Takahashi, Toshiyuki; Takahashi, Yoshimasa; Imai, Yasuhiro; Ishihara, Yotaro; Kato, Kyoichi; Nakazawa, Yasuo

    2010-05-20

    The development of MDCT enabled various high-quality 3D imaging and optimized scan timing with contrast injection in a multi-phase dynamic study. Since radiation dose tends to increase to yield such high-quality images, we have to make an effort to reduce radiation dose. A non-linear image filter (Neuro 3D filter: N3D filter) has been developed in order to improve image noise. The purpose of this study was to evaluate the physical performance and effectiveness of this non-linear image filter using phantoms, and show how we can reduce radiation dose in clinical use of this filter. This N3D filter reduced radiation dose by about 50%, with minimum deterioration of spatial reduction in phantom and clinical studies. This filter shows great potential for clinical application.

  15. Sparse PDF maps for non-linear multi-resolution image operations

    KAUST Repository

    Hadwiger, Markus

    2012-11-01

    We introduce a new type of multi-resolution image pyramid for high-resolution images called sparse pdf maps (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations directly in any pyramid level with proper pre-filtering for anti-aliasing, without accessing higher or lower resolutions. The sparsity of sPDF-maps makes them feasible for gigapixel images, while enabling direct evaluation of a variety of non-linear operators from the same representation. We illustrate this versatility for antialiased color mapping, O(n) local Laplacian filters, smoothed local histogram filters (e.g., median or mode filters), and bilateral filters. © 2012 ACM.

  16. A nonlinear fuzzy assisted image reconstruction algorithm for electrical capacitance tomography.

    Science.gov (United States)

    Deabes, W A; Abdelrahman, M A

    2010-01-01

    A nonlinear method based on a Fuzzy Inference System (FIS) to improve the images obtained from Electrical Capacitance Tomography (ECT) is proposed. Estimation of the molten metal characteristic in the Lost Foam Casting (LFC) process is a novel application in the area of the tomography process. The convergence rate of iterative image reconstruction techniques is dependent on the accuracy of the first image. The possibility of the existence of metal in the first image is computed by the proposed fuzzy system. This first image is passed to an iterative image reconstruction technique to get more precise images and to speed up the convergence rate. The proposed technique is able to detect the position of the metal on the periphery of the imaging area by using just eight capacitive sensors. The final results demonstrate the advantage of using the FIS compared to the performance of the iterative back projection image reconstruction technique.

  17. Pre-determining the location of electromigrated gaps by nonlinear optical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Mennemanteuil, M.-M.; Dellinger, J.; Buret, M.; Colas des Francs, G.; Bouhelier, A., E-mail: alexandre.bouhelier@u-bourgogne.fr [Laboratoire Interdisciplinaire Carnot de Bourgogne CNRS-UMR 6303, Université de Bourgogne, 21078 Dijon (France)

    2014-07-14

    In this paper we describe a nonlinear imaging method employed to spatially map the occurrence of constrictions occurring on an electrically stressed gold nanowire. The approach consists at measuring the influence of a tightly focused ultrafast pulsed laser on the electronic transport in the nanowire. We found that structural defects distributed along the nanowire are efficient nonlinear optical sources of radiation and that the differential conductance is significantly decreased when the laser is incident on such electrically induced morphological changes. This imaging technique is applied to pre-determine the location of the electrical failure before it occurs.

  18. 2-D nonlinear IIR-filters for image processing - An exploratory analysis

    Science.gov (United States)

    Bauer, P. H.; Sartori, M.

    1991-01-01

    A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.

  19. 2-D nonlinear IIR-filters for image processing - An exploratory analysis

    Science.gov (United States)

    Bauer, P. H.; Sartori, M.

    1991-01-01

    A new nonlinear IIR filter structure is introduced and its deterministic properties are analyzed. It is shown to be better suited for image processing applications than its linear shift-invariant counterpart. The new structure is obtained from causality inversion of a 2D quarterplane causal linear filter with respect to the two directions of propagation. It is demonstrated, that by using this design, a nonlinear 2D lowpass filter can be constructed, which is capable of effectively suppressing Gaussian or impulse noise without destroying important image information.

  20. Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

    Science.gov (United States)

    Itoh, Kazuyoshi

    2015-12-01

    Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

  1. The use of amalgam powder and calcium hydroxide to recreate a radiopaque image of a lost dental restoration.

    Science.gov (United States)

    Shiroma, Calvin Y

    2002-05-01

    Radiographs of dental restorations are highly reliable when used to identify postmortem dental remains. A problem exists if key dental restorations are missing or defective, which results in the loss of a comparative radiographic image. This article describes a simple method allowing the odontologist to quickly recreate a temporary radiopaque restoration. This article presents a method of using amalgam powder (radiopaque material) and calcium hydroxide (radiopaque material and transport medium for the amalgam powder) to recreate a radiopaque image on a tooth that has lost a dental restoration. Amalgam powder and calcium hydroxide is easily obtained (in any dental office), fairly clean, easy to manipulate, inexpensive, inert, stable, and able to be removed without damaging the dental remains. The amalgam powder/calcium hydroxide mixture can easily be re-shaped or modified to reflect the radiopaque image of the original restoration. Radiographic comparison of the "restored" dental remains to the antemortem radiographs is now possible. The use of this technique is presented in a case report.

  2. State-space blur model for high-speed forward-moving imaging system and its recursive restoration

    Science.gov (United States)

    Cao, Fengmei; Chen, Xichun; Jin, Weiqi

    2007-01-01

    When an imaging system is approaching the object at a high speed, because of the existence of integration time, the images obtained are always blurred radially. Since the degradation process is space variant, this kind of blur is difficult to handle, traditional frequency domain techniques can't be applied here. Obviously, the radially blurred image obtained is rotation symmetrical, so the usual uniformly sampled image can be resampled with fan-shaped grids, and the gray level of these new sampling points build up a new image matrix. The new image matrix's columns and rows are never the edges of the image, but the image's radius and angle. So, the original two-dimensional problem is simplified. Even after the resampling, the blur is still space variant, and the PSF (point spread function) will change along the radius direction. So the authors come up with a state-space method, a state-space blur model is constructed, which handles the problem recursively. To restore the degraded image simply means to find the inverse of the degradation system and computer simulation result shows the restoration algorithm restored the radially blurred image approvingly.

  3. Combination of nonlinear ultrasonics and guided wave tomography for imaging the micro-defects.

    Science.gov (United States)

    Li, Weibin; Cho, Younho

    2016-02-01

    The use of guided wave tomography has become an attractive alternative to convert ultrasonic wave raw data to visualized results for quantitative signal interpretation. For more accurate life prediction and efficient management strategies for critical structural components, there is a demand of imaging micro-damages in early stage. However, there is rarely investigation on guided wave tomographic imaging of micro-defects. One of the reasons for this might be that it becomes challenging to monitor tiny signal difference coefficient in a reliable manner for wave propagation in the specimens with micro-damages. Nonlinear acoustic signal whose frequency differs from that of the input signal can be found in the specimens with micro-damages. Therefore, the combination of guided wave tomography and nonlinear acoustic response induced by micro-damages could be a feasibility study for imaging micro-damages. In this paper, the nonlinear Rayleigh surface wave tomographic method is investigated to locate and size micro-corrosive defect region in an isotropic solid media. The variations of acoustic nonlinear responses of ultrasonic waves in the specimens with and without defects are used in guided wave tomographic algorithm to construct the images. The comparisons between images obtained by experimental signals and real defect region induced by hydrogen corrosion are presented in this paper. Results show that the images of defect regions with different shape, size and location are successfully obtained by this novel technique, while there is no visualized result constructed by conventional linear ultrasonic tomographic one. The present approach shows a potential for inspecting, locating and imaging micro-defects by nonlinear Rayleigh surface wave tomography. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Introduction to the Restoration of Astrophysical Images by Multiscale Transforms and Bayesian Methods

    Science.gov (United States)

    Bijaoui, A.

    2013-03-01

    The image restoration is today an important part of the astrophysical data analysis. The denoising and the deblurring can be efficiently performed using multiscale transforms. The multiresolution analysis constitutes the fundamental pillar for these transforms. The discrete wavelet transform is introduced from the theory of the approximation by translated functions. The continuous wavelet transform carries out a generalization of multiscale representations from translated and dilated wavelets. The à trous algorithm furnishes its discrete redundant transform. The image denoising is first considered without any hypothesis on the signal distribution, on the basis of the a contrario detection. Different softening functions are introduced. The introduction of a regularization constraint may improve the results. The application of Bayesian methods leads to an automated adaptation of the softening function to the signal distribution. The MAP principle leads to the basis pursuit, a sparse decomposition on redundant dictionaries. Nevertheless the posterior expectation minimizes, scale per scale, the quadratic error. The proposed deconvolution algorithm is based on a coupling of the wavelet denoising with an iterative inversion algorithm. The different methods are illustrated by numerical experiments on a simulated image similar to images of the deep sky. A white Gaussian stationary noise was added with three levels. In the conclusion different important connected problems are tackled.

  5. Nonlinear optical microscopy and ultrasound imaging of human cervical structure

    Science.gov (United States)

    Reusch, Lisa M.; Feltovich, Helen; Carlson, Lindsey C.; Hall, Gunnsteinn; Campagnola, Paul J.; Eliceiri, Kevin W.; Hall, Timothy J.

    2013-03-01

    The cervix softens and shortens as its collagen microstructure rearranges in preparation for birth, but premature change may lead to premature birth. The global preterm birth rate has not decreased despite decades of research, likely because cervical microstructure is poorly understood. Our group has developed a multilevel approach to evaluating the human cervix. We are developing quantitative ultrasound (QUS) techniques for noninvasive interrogation of cervical microstructure and corroborating those results with high-resolution images of microstructure from second harmonic generation imaging (SHG) microscopy. We obtain ultrasound measurements from hysterectomy specimens, prepare the tissue for SHG, and stitch together several hundred images to create a comprehensive view of large areas of cervix. The images are analyzed for collagen orientation and alignment with curvelet transform, and registered with QUS data, facilitating multiscale analysis in which the micron-scale SHG images and millimeter-scale ultrasound data interpretation inform each other. This novel combination of modalities allows comprehensive characterization of cervical microstructure in high resolution. Through a detailed comparative study, we demonstrate that SHG imaging both corroborates the quantitative ultrasound measurements and provides further insight. Ultimately, a comprehensive understanding of specific microstructural cervical change in pregnancy should lead to novel approaches to the prevention of preterm birth.

  6. Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique

    Directory of Open Access Journals (Sweden)

    Izhal Abdul Halin

    2009-11-01

    Full Text Available The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region.

  7. Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique

    Science.gov (United States)

    Shafie, Suhaidi; Kawahito, Shoji; Halin, Izhal Abdul; Hasan, Wan Zuha Wan

    2009-01-01

    The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region. PMID:22303133

  8. Three dimensional full-wave nonlinear acoustic simulations: Applications to ultrasound imaging

    Energy Technology Data Exchange (ETDEWEB)

    Pinton, Gianmarco [Joint Department of Biomedical Engineering, University of North Carolina - North Carolina State University, 348 Taylor Hall, Chapel Hill, NC 27599, USA gfp@unc.edu (United States)

    2015-10-28

    Characterization of acoustic waves that propagate nonlinearly in an inhomogeneous medium has significant applications to diagnostic and therapeutic ultrasound. The generation of an ultrasound image of human tissue is based on the complex physics of acoustic wave propagation: diffraction, reflection, scattering, frequency dependent attenuation, and nonlinearity. The nonlinearity of wave propagation is used to the advantage of diagnostic scanners that use the harmonic components of the ultrasonic signal to improve the resolution and penetration of clinical scanners. One approach to simulating ultrasound images is to make approximations that can reduce the physics to systems that have a low computational cost. Here a maximalist approach is taken and the full three dimensional wave physics is simulated with finite differences. This paper demonstrates how finite difference simulations for the nonlinear acoustic wave equation can be used to generate physically realistic two and three dimensional ultrasound images anywhere in the body. A specific intercostal liver imaging scenario for two cases: with the ribs in place, and with the ribs removed. This configuration provides an imaging scenario that cannot be performed in vivo but that can test the influence of the ribs on image quality. Several imaging properties are studied, in particular the beamplots, the spatial coherence at the transducer surface, the distributed phase aberration, and the lesion detectability for imaging at the fundamental and harmonic frequencies. The results indicate, counterintuitively, that at the fundamental frequency the beamplot improves due to the apodization effect of the ribs but at the same time there is more degradation from reverberation clutter. At the harmonic frequency there is significantly less improvement in the beamplot and also significantly less degradation from reverberation. It is shown that even though simulating the full propagation physics is computationally challenging it

  9. Restoration of Medical Images with Different Types of Noise; Restauracion de Imagenes Medicas con Diferentes Tipos de Ruido

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, M. G.; Vidal, V.; Verdu, G.; Mayo, P.; Rodenas, F.

    2013-07-01

    In this paper, a method is proposed to reduce the Gaussian, speckle and impulsive noise. This filter, named PGMFDNL filter combines a nonlinear diffusion and fuzzy peer group. The proposed filter can effectively reduce image noise without any information about the noise present in the image. As a result, the proposed method obtains good performance in different types of noise.

  10. Nonlinear optical molecular imaging enables metabolic redox sensing in tissue-engineered constructs

    Science.gov (United States)

    Chen, Leng-Chun; Lloyd, William R.; Wilson, Robert H.; Kuo, Shiuhyang; Marcelo, Cynthia L.; Feinberg, Stephen E.; Mycek, Mary-Ann

    2011-07-01

    Tissue-engineered constructs require noninvasive monitoring of cellular viability prior to implantation. In a preclinical study on human Ex Vivo Produced Oral Mucosa Equivalent (EVPOME) constructs, nonlinear optical molecular imaging was employed to extract morphological and functional information from intact constructs. Multiphoton excitation fluorescence images were acquired using endogenous fluorescence from cellular nicotinamide adenine dinucleotide phosphate [NAD(P)H] and flavin adenine dinucleotide (FAD). The images were analyzed to report quantitatively on tissue structure and metabolism (redox ratio). Both thickness variations over time and cell distribution variations with depth were identified, while changes in redox were quantified. Our results show that nonlinear optical molecular imaging has the potential to visualize and quantitatively monitor the growth and viability of a tissue-engineered construct over time.

  11. Edge detection of remote sensing image based on nonlinear intensity of curved surface

    Institute of Scientific and Technical Information of China (English)

    张连蓬; 刘国林; 江涛

    2003-01-01

    A new edge detector based on the nonlinear intensity of curved surface was proposed. The edge detector describes the largest curvature and the smallest curvature of curved surface, therefore it can reflect the real largest direction of image edge jump. By the new edge detector, it is convenient to calculate the curvature in any direction of the curved surface and the curvature can be used in the identification of edge direction and the feature extraction of objects on remote sensing image.

  12. Monitoring the metabolic state of fungal hyphae and the presence of melanin by nonlinear spectral imaging

    NARCIS (Netherlands)

    Knaus, H.; Blab, G.; Agronskaia, A.V.; van den Heuvel, D.J.; Gerritsen, H.C.; Wösten, H.A.B.

    2013-01-01

    Label-free nonlinear spectral imaging microscopy (NLSM) records two-photon-excited fluorescence emission spectra of endogenous fluorophores within the specimen. Here, NLSM is introduced as a novel, minimally invasive method to analyze the metabolic state of fungal hyphae by monitoring the autofluore

  13. AM Multipurpose High-Resolution Imaging Topological Radar (ITR): reverse engineering and artworks monitoring and restoration

    Science.gov (United States)

    Guarneri, Massimiliano; Bartolini, Luciano; Fornetti, Giorgio; Ferri De Collibus, Mario; De Dominicis, Luigi; Paglia, Emiliano; Poggi, Claudio; Ricci, Roberto

    2005-08-01

    A high resolution Amplitude Modulated Imaging Laser Radar (AM-LR) sensor has recently been developed, aimed to accurately reconstructing 3D digital models of real targets - either single objects or large amplitude complex scenes. The system sounding beam can be swept linearly across the object or circularly around it, by placing the object on a controlled rotating platform. Both intensity and phase shift of the back-scattered light are then collected and processed, providing respectively a shade-free photographic-like picture and accurate range data in the form of a range or depth image, with accuracy depending mainly on the laser modulation frequency. The development of software, suitable for simultaneous 3D rendering of the intensity and absolute distance data collected by the ITR, constitutes one of the main objectives of the research activity, whatever is the application pursued. In fact, high resolution AM-LR systems have a great interest for their potentials in accurate 3D imaging of valuable objects which must be preserved in digital archives. Examples range from artwork monitoring, cataloguing and restoration from sparse fragments, to medicine for non-hazardous diagnostics and fast design of bio-compatible prostheses, to microtechnology in the miniaturization of macro-components (plastic prototypes, quality control). Several meaningful results of measurements executed in various important European archaeological sites, in particular Santa Maria Antiqua church situated in Fori Imperiali area in Rome and Costanza (Romania), involving 3D color mapped representation are also presented.

  14. 2D Iterative MAP Detection: Principles and Applications in Image Restoration

    Directory of Open Access Journals (Sweden)

    D. Kekrt

    2014-06-01

    Full Text Available The paper provides a theoretical framework for the two-dimensional iterative maximum a posteriori detection. This generalization is based on the concept of detection algorithms BCJR and SOVA, i.e., the classical (one-dimensional iterative detectors used in telecommunication applications. We generalize the one-dimensional detection problem considering the spatial ISI kernel as a two-dimensional finite state machine (2D FSM representing a network of the spatially concatenated elements. The cellular structure topology defines the design of the 2D Iterative decoding network, where each cell is a general combination-marginalization statistical element (SISO module exchanging discrete probability density functions (information metrics with neighboring cells. In this paper, we statistically analyse the performance of various topologies with respect to their application in the field of image restoration. The iterative detection algorithm was applied on the task of binarization of images taken from a CCD camera. The reconstruction includes suppression of the defocus caused by the lens, CCD sensor noise suppression and interpolation (demosaicing. The simulations prove that the algorithm provides satisfactory results even in the case of an input image that is under-sampled due to the Bayer mask.

  15. Sub-diffraction imaging on standard microscopes through photobleaching microscopy with non-linear processing.

    Science.gov (United States)

    Munck, Sebastian; Miskiewicz, Katarzyna; Sannerud, Ragna; Menchon, Silvia A; Jose, Liya; Heintzmann, Rainer; Verstreken, Patrik; Annaert, Wim

    2012-05-01

    Visualization of organelles and molecules at nanometer resolution is revolutionizing the biological sciences. However, such technology is still limited for many cell biologists. We present here a novel approach using photobleaching microscopy with non-linear processing (PiMP) for sub-diffraction imaging. Bleaching of fluorophores both within the single-molecule regime and beyond allows visualization of stochastic representations of sub-populations of fluorophores by imaging the same region over time. Our method is based on enhancing the probable positions of the fluorophores underlying the images. The random nature of the bleached fluorophores is assessed by calculating the deviation of the local actual bleached fluorescence intensity to the average bleach expectation as given by the overall decay of intensity. Subtracting measured from estimated decay images yields differential images. Non-linear enhancement of maxima in these diffraction-limited differential images approximates the positions of the underlying structure. Summing many such processed differential images yields a super-resolution PiMP image. PiMP allows multi-color, three-dimensional sub-diffraction imaging of cells and tissues using common fluorophores and can be implemented on standard wide-field or confocal systems.

  16. An ICPSO-RBFNN nonlinear inversion for electrical resistivity imaging

    Institute of Scientific and Technical Information of China (English)

    江沸菠; 戴前伟; 董莉

    2016-01-01

    To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network (RBFNN) based on information criterion (IC) and particle swarm optimization (PSO) is presented. In the proposed method, IC is applied to obtain the hidden layer structure by calculating the optimal IC value automatically and PSO algorithm is used to optimize the centers and widths of the radial basis functions in the hidden layer. Meanwhile, impacts of different information criteria to the inversion results are compared, and an implementation of the proposed ICPSO algorithm is given. The optimized neural network has one hidden layer with 261 nodes selected by AKAIKE’s information criterion (AIC) and it is trained on 32 data sets and tested on another 8 synthetic data sets. Two complex synthetic examples are used to verify the feasibility and effectiveness of the proposed method with two learning stages. The results show that the proposed method has better performance and higher imaging quality than three-layer and four-layer back propagation neural networks (BPNNs) and traditional least square(LS) inversion.

  17. Restoring Charlemagne’s chapel: historical consciousness, material culture, and transforming images of Aachen in the 1840s

    Directory of Open Access Journals (Sweden)

    Jenny H. Shaffer

    2012-12-01

    Full Text Available The 1840s offer crystallizing images of Charlemagne’s chapel at Aachen that continue to resonate. In this decade, the Carolingian building, restored in words and images by scholars, made an auspicious debut within the coalescing discipline of art history. Simultaneously, the well-known restoration of the extant medieval chapel, which began in the 1850s, found sure footing as the chapel’s columnar screen, which Napoleon had removed, was reinserted. While these co-existing, interrelated restoration movements – focused on the chapel’s dilapidated state and notions of its importance as an imperial, Christian, and German work – diverged in methods and results after mid-century, they remain central to understanding both the chapel in scholarship and the extraordinary monument in the town centre of Aachen today.

  18. Application of color image processing and low-coherent optical computer tomography in evaluation of adhesive interfaces of dental restorations

    Science.gov (United States)

    Bessudnova, Nadezda O.; Shlyapnikova, Olga A.; Venig, Sergey B.; Genina, Elina A.; Sadovnikov, Alexandr V.

    2015-03-01

    Durability of bonded interfaces between dentin and a polymer material in resin-based composite restorations remains a clinical dentistry challenge. In the present study the evolution of bonded interfaces in biological active environment is estimated in vivo. A novel in vivo method of visual diagnostics that involves digital processing of color images of composite restorations and allows the evaluation of adhesive interface quality over time, has been developed and tested on a group of volunteers. However, the application of the method is limited to the analysis of superficial adhesive interfaces. Low-coherent optical computer tomography (OCT) has been tested as a powerful non-invasive tool for in vivo, in situ clinical diagnostics of adhesive interfaces over time. In the long-term perspective adhesive interface monitoring using standard methods of clinical diagnostics along with colour image analysis and OCT could make it possible to objectivise and prognosticate the clinical longevity of composite resin-based restorations with adhesive interfaces.

  19. Observation of spectral self-imaging by nonlinear parabolic cross-phase modulation.

    Science.gov (United States)

    Lei, Lei; Huh, Jeonghyun; Cortés, Luis Romero; Maram, Reza; Wetzel, Benjamin; Duchesne, David; Morandotti, Roberto; Azaña, José

    2015-11-15

    We report an experimental demonstration of spectral self-imaging on a periodic frequency comb induced by a nonlinear all-optical process, i.e., parabolic cross-phase modulation in a highly nonlinear fiber. The comb free spectral range is reconfigured by simply tuning the temporal period of the pump parabolic pulse train. In particular, undistorted FSR divisions by factors of 2 and 3 are successfully performed on a 10 GHz frequency comb, realizing new frequency combs with an FSR of 5 and 3.3 GHz, respectively. The pump power requirement associated to the SSI phenomena is also shown to be significantly relaxed by the use of dark parabolic pulses.

  20. A 3-D nonlinear recursive digital filter for video image processing

    Science.gov (United States)

    Bauer, P. H.; Qian, W.

    1991-01-01

    This paper introduces a recursive 3-D nonlinear digital filter, which is capable of performing noise suppression without degrading important image information such as edges in space or time. It also has the property of unnoticeable bandwidth reduction immediately after a scene change, which makes the filter an attractive preprocessor to many interframe compression algorithms. The filter consists of a nonlinear 2-D spatial subfilter and a 1-D temporal filter. In order to achieve the required computational speed and increase the flexibility of the filter, all of the linear shift-variant filter modules are of the IIR type.

  1. A Nonlinear Entropic Variational Model for Image Filtering

    Directory of Open Access Journals (Sweden)

    Krim Hamid

    2004-01-01

    Full Text Available We propose an information-theoretic variational filter for image denoising. It is a result of minimizing a functional subject to some noise constraints, and takes a hybrid form of a negentropy variational integral for small gradient magnitudes and a total variational integral for large gradient magnitudes. The core idea behind this approach is to use geometric insight in helping to construct regularizing functionals and avoiding a subjective choice of a prior in maximum a posteriori estimation. Illustrative experimental results demonstrate a much improved performance of the approach in the presence of Gaussian and heavy-tailed noise.

  2. A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid imaging.

    Science.gov (United States)

    Bilgel, Murat; Prince, Jerry L; Wong, Dean F; Resnick, Susan M; Jedynak, Bruno M

    2016-07-01

    It is important to characterize the temporal trajectories of disease-related biomarkers in order to monitor progression and identify potential points of intervention. These are especially important for neurodegenerative diseases, as therapeutic intervention is most likely to be effective in the preclinical disease stages prior to significant neuronal damage. Neuroimaging allows for the measurement of structural, functional, and metabolic integrity of the brain at the level of voxels, whose volumes are on the order of mm(3). These voxelwise measurements provide a rich collection of disease indicators. Longitudinal neuroimaging studies enable the analysis of changes in these voxelwise measures. However, commonly used longitudinal analysis approaches, such as linear mixed effects models, do not account for the fact that individuals enter a study at various disease stages and progress at different rates, and generally consider each voxelwise measure independently. We propose a multivariate nonlinear mixed effects model for estimating the trajectories of voxelwise neuroimaging biomarkers from longitudinal data that accounts for such differences across individuals. The method involves the prediction of a progression score for each visit based on a collective analysis of voxelwise biomarker data within an expectation-maximization framework that efficiently handles large amounts of measurements and variable number of visits per individual, and accounts for spatial correlations among voxels. This score allows individuals with similar progressions to be aligned and analyzed together, which enables the construction of a trajectory of brain changes as a function of an underlying progression or disease stage. We apply our method to studying cortical β-amyloid deposition, a hallmark of preclinical Alzheimer's disease, as measured using positron emission tomography. Results on 104 individuals with a total of 300 visits suggest that precuneus is the earliest cortical region to

  3. Region-confined restoration method for motion-blurred star image of the star sensor under dynamic conditions.

    Science.gov (United States)

    Ma, Liheng; Bernelli-Zazzera, Franco; Jiang, Guangwen; Wang, Xingshu; Huang, Zongsheng; Qin, Shiqiao

    2016-06-10

    Under dynamic conditions, the centroiding accuracy of the motion-blurred star image decreases and the number of identified stars reduces, which leads to the degradation of the attitude accuracy of the star sensor. To improve the attitude accuracy, a region-confined restoration method, which concentrates on the noise removal and signal to noise ratio (SNR) improvement of the motion-blurred star images, is proposed for the star sensor under dynamic conditions. A multi-seed-region growing technique with the kinematic recursive model for star image motion is given to find the star image regions and to remove the noise. Subsequently, a restoration strategy is employed in the extracted regions, taking the time consumption and SNR improvement into consideration simultaneously. Simulation results indicate that the region-confined restoration method is effective in removing noise and improving the centroiding accuracy. The identification rate and the average number of identified stars in the experiments verify the advantages of the region-confined restoration method.

  4. Multifunction nonlinear signal processor - Deconvolution and correlation

    Science.gov (United States)

    Javidi, Bahram; Horner, Joseph L.

    1989-08-01

    A multifuncional nonlinear optical signal processor is described that allows different types of operations, such as image deconvolution and nonlinear correlation. In this technique, the joint power spectrum of the input signal is thresholded with varying nonlinearity to produce different specific operations. In image deconvolution, the joint power spectrum is modified and hard-clip thresholded to remove the amplitude distortion effects and to restore the correct phase of the original image. In optical correlation, the Fourier transform interference intensity is thresholded to provide higher correlation peak intensity and a better-defined correlation spot. Various types of correlation signals can be produced simply by varying the severity of the nonlinearity, without the need for synthesis of specific matched filter. An analysis of the nonlinear processor for image deconvolution is presented.

  5. Nonlinear optical imaging of defects in cubic silicon carbide epilayers.

    Science.gov (United States)

    Hristu, Radu; Stanciu, Stefan G; Tranca, Denis E; Matei, Alecs; Stanciu, George A

    2014-06-11

    Silicon carbide is one of the most promising materials for power electronic devices capable of operating at extreme conditions. The widespread application of silicon carbide power devices is however limited by the presence of structural defects in silicon carbide epilayers. Our experiment demonstrates that optical second harmonic generation imaging represents a viable solution for characterizing structural defects such as stacking faults, dislocations and double positioning boundaries in cubic silicon carbide layers. X-ray diffraction and optical second harmonic rotational anisotropy were used to confirm the growth of the cubic polytype, atomic force microscopy was used to support the identification of silicon carbide defects based on their distinct shape, while second harmonic generation microscopy revealed the detailed structure of the defects. Our results show that this fast and noninvasive investigation method can identify defects which appear during the crystal growth and can be used to certify areas within the silicon carbide epilayer that have optimal quality.

  6. Null space imaging: nonlinear magnetic encoding fields designed complementary to receiver coil sensitivities for improved acceleration in parallel imaging.

    Science.gov (United States)

    Tam, Leo K; Stockmann, Jason P; Galiana, Gigi; Constable, R Todd

    2012-10-01

    To increase image acquisition efficiency, we develop alternative gradient encoding strategies designed to provide spatial encoding complementary to the spatial encoding provided by the multiple receiver coil elements in parallel image acquisitions. Intuitively, complementary encoding is achieved when the magnetic field encoding gradients are designed to encode spatial information where receiver spatial encoding is ambiguous, for example, along sensitivity isocontours. Specifically, the method generates a basis set for the null space of the coil sensitivities with the singular value decomposition and calculates encoding fields from the null space vectors. A set of nonlinear gradients is used as projection imaging readout magnetic fields, replacing the conventional linear readout field and phase encoding. Multiple encoding fields are used as projections to capture the null space information, hence the term null space imaging. The method is compared to conventional Cartesian SENSitivity Encoding as evaluated by mean squared error and robustness to noise. Strategies for developments in the area of nonlinear encoding schemes are discussed. The null space imaging approach yields a parallel imaging method that provides high acceleration factors with a limited number of receiver coil array elements through increased time efficiency in spatial encoding.

  7. A neural learning approach for adaptive image restoration using a fuzzy model-based network architecture.

    Science.gov (United States)

    Wong, H S; Guan, L

    2001-01-01

    We address the problem of adaptive regularization in image restoration by adopting a neural-network learning approach. Instead of explicitly specifying the local regularization parameter values, they are regarded as network weights which are then modified through the supply of appropriate training examples. The desired response of the network is in the form of a gray level value estimate of the current pixel using weighted order statistic (WOS) filter. However, instead of replacing the previous value with this estimate, this is used to modify the network weights, or equivalently, the regularization parameters such that the restored gray level value produced by the network is closer to this desired response. In this way, the single WOS estimation scheme can allow appropriate parameter values to emerge under different noise conditions, rather than requiring their explicit selection in each occasion. In addition, we also consider the separate regularization of edges and textures due to their different noise masking capabilities. This in turn requires discriminating between these two feature types. Due to the inability of conventional local variance measures to distinguish these two high variance features, we propose the new edge-texture characterization (ETC) measure which performs this discrimination based on a scalar value only. This is then incorporated into a fuzzified form of the previous neural network which determines the degree of membership of each high variance pixel in two fuzzy sets, the EDGE and TEXTURE fuzzy sets, from the local ETC value, and then evaluates the appropriate regularization parameter by appropriately combining these two membership function values.

  8. A Comparison of PDE-based Non-Linear Anisotropic Diffusion Techniques for Image Denoising

    Energy Technology Data Exchange (ETDEWEB)

    Weeratunga, S K; Kamath, C

    2003-01-06

    PDE-based, non-linear diffusion techniques are an effective way to denoise images. In a previous study, we investigated the effects of different parameters in the implementation of isotropic, non-linear diffusion. Using synthetic and real images, we showed that for images corrupted with additive Gaussian noise, such methods are quite effective, leading to lower mean-squared-error values in comparison with spatial filters and wavelet-based approaches. In this paper, we extend this work to include anisotropic diffusion, where the diffusivity is a tensor valued function which can be adapted to local edge orientation. This allows smoothing along the edges, but not perpendicular to it. We consider several anisotropic diffusivity functions as well as approaches for discretizing the diffusion operator that minimize the mesh orientation effects. We investigate how these tensor-valued diffusivity functions compare in image quality, ease of use, and computational costs relative to simple spatial filters, the more complex bilateral filters, wavelet-based methods, and isotropic non-linear diffusion based techniques.

  9. Comparison of PDE-based non-linear anistropic diffusion techniques for image denoising

    Science.gov (United States)

    Weeratunga, Sisira K.; Kamath, Chandrika

    2003-05-01

    PDE-based, non-linear diffusion techniques are an effective way to denoise images.In a previous study, we investigated the effects of different parameters in the implementation of isotropic, non-linear diffusion. Using synthetic and real images, we showed that for images corrupted with additive Gaussian noise, such methods are quite effective, leading to lower mean-squared-error values in comparison with spatial filters and wavelet-based approaches. In this paper, we extend this work to include anisotropic diffusion, where the diffusivity is a tensor valued function which can be adapted to local edge orientation. This allows smoothing along the edges, but not perpendicular to it. We consider several anisotropic diffusivity functions as well as approaches for discretizing the diffusion operator that minimize the mesh orientation effects. We investigate how these tensor-valued diffusivity functions compare in image quality, ease of use, and computational costs relative to simple spatial filters, the more complex bilateral filters, wavelet-based methods, and isotropic non-linear diffusion based techniques.

  10. Compact ultrafast semiconductor disk laser for nonlinear imaging in living organisms

    Science.gov (United States)

    Aviles-Espinosa, Rodrigo; Filippidis, G.; Hamilton, Craig; Malcolm, Graeme; Weingarten, Kurt J.; Südmeyer, Thomas; Barbarin, Yohan; Keller, Ursula; Artigas, David; Loza-Alvarez, Pablo

    2011-03-01

    Ultrashort pulsed laser systems (such as Ti:sapphire) have been used in nonlinear microscopy during the last years. However, its implementation is not straight forward as they are maintenance-intensive, bulky and expensive. These limitations have prevented their wide-spread use for nonlinear imaging, especially in "real-life" biomedical applications. In this work we present the suitability of a compact ultrafast semiconductor disk laser source, with a footprint of 140x240x70 mm, to be used for nonlinear microscopy. The modelocking mechanism of the laser is based on a quantumdot semiconductor saturable absorber mirror (SESAM). The laser delivers an average output power of 287 mW with 1.5 ps pulses at 500 MHz, corresponding to a peak power of 0.4 kW. Its center wavelength is 965 nm which is ideally suited for two-photon excitation of the widely used Green Fluorescent Protein (GFP) marker as it virtually matches its twophoton action cross section. We reveal that it is possible to obtain two photon excited fluorescence images of GFP labeled neurons and secondharmonic generation images of pharynx and body wall muscles in living C. elegans nematodes. Our results demonstrate that this compact laser is well suited for long-term time-lapse imaging of living samples as very low powers provide a bright signal. Importantly this non expensive, turn-key, compact laser system could be used as a platform to develop portable nonlinear bio-imaging devices, facilitating its wide-spread adoption in "real-life" applications.

  11. New layer-based imaging and rapid prototyping techniques for computer-aided design and manufacture of custom dental restoration.

    Science.gov (United States)

    Lee, M-Y; Chang, C-C; Ku, Y C

    2008-01-01

    Fixed dental restoration by conventional methods greatly relies on the skill and experience of the dental technician. The quality and accuracy of the final product depends mostly on the technician's subjective judgment. In addition, the traditional manual operation involves many complex procedures, and is a time-consuming and labour-intensive job. Most importantly, no quantitative design and manufacturing information is preserved for future retrieval. In this paper, a new device for scanning the dental profile and reconstructing 3D digital information of a dental model based on a layer-based imaging technique, called abrasive computer tomography (ACT) was designed in-house and proposed for the design of custom dental restoration. The fixed partial dental restoration was then produced by rapid prototyping (RP) and computer numerical control (CNC) machining methods based on the ACT scanned digital information. A force feedback sculptor (FreeForm system, Sensible Technologies, Inc., Cambridge MA, USA), which comprises 3D Touch technology, was applied to modify the morphology and design of the fixed dental restoration. In addition, a comparison of conventional manual operation and digital manufacture using both RP and CNC machining technologies for fixed dental restoration production is presented. Finally, a digital custom fixed restoration manufacturing protocol integrating proposed layer-based dental profile scanning, computer-aided design, 3D force feedback feature modification and advanced fixed restoration manufacturing techniques is illustrated. The proposed method provides solid evidence that computer-aided design and manufacturing technologies may become a new avenue for custom-made fixed restoration design, analysis, and production in the 21st century.

  12. Image segmentation combining non-linear diffusion and the Nystrom extension

    Science.gov (United States)

    Izquierdo, Ebroul

    2005-07-01

    An approach for image segmentation is presented. Images are first preprocessed using multiscale simplification by nonlinear diffusion. Subsequently image segmentation of the resulting smoothed images is carried out. The actual segmentation step is based on the estimation of the Eigenvectors and Eigenvalues of a matrix derived from both the total dissimilarity and the total similarity between different groups of pixels in the image. This algorithm belong to the class of spectral methods, specifically, the Nystron extension introduced by Fowlkes et al in [1]. Stability analysis of the approximation of the underlying spectral partitioning is presented. Modifications of Fowlkes technique are proposed to improve the stability of the algorithm. The proposed modifications include a criterion for the selection of the initial sample and numerically stable estimations of ill-posed inverse matrices for the solution of the underlying mathematical problem. Results of selected computer experiments are reported to validate the superiority of the proposed approach when compared with the technique proposed in [1].

  13. Nonlinear PET parametric image reconstruction with MRI information using kernel method

    Science.gov (United States)

    Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

    2017-03-01

    Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

  14. 盲复原高斯模糊图像%The blind restoration of Gaussian blurred images

    Institute of Scientific and Technical Information of China (English)

    丁左红; 郭汉明; 高秀敏; 蓝景恒; 翁晓羽; 满忠胜; 庄松林

    2011-01-01

    经典的图像恢复算法设点扩展函数(PSF)是已知的,然而在许多情况下PSF难以确定,不得不在只知道成像系统部分信息甚至没有任何信息的情况下估计真实图像和PSF,这一过程称为图像盲复原.对于高斯模糊图像,它的PSF是很难被检测出来的,因此高斯模糊图像的盲复原一直是个棘手的问题.利用高斯点扩展函数的特性,初始估计PSF并对加噪后的模糊图像进行维纳滤波,后经过中值滤波获得恢复图像.恢复的图像主观视觉效果较好,具有良好的抗噪性,复原效果明显.该方法对于提高图像质量有一定的参考价值.%Classical image restoration algorithm is based on point spread function (PSF) is known. However, it is difficult to determine PSF in many cases, we have to estimate the true image and PSF in the case of only knowing some of the information or no information of imaging systems, this process is called blind image restoration. For the Gaussian blurred image, it is very difficult to detect PSF, so blind restoration of the Gaussian blurred image has been a troublesome issue. In this paper, we suppose the initial PSF using the characteristics of Gaussian PSF, and do Wiener filtering based on Gaussian blurred image with noise, then gain the restoration image through the median filtering. Experiment shows that, restored image is better in subjective visual effect, and remarkable in recovery effect with good noise immunity. This method has some reference value to improve the image quality.

  15. Subharmonic, non-linear fundamental and ultraharmonic imaging of microbubble contrast at high frequencies.

    Science.gov (United States)

    Daeichin, Verya; Bosch, Johan G; Needles, Andrew; Foster, F Stuart; van der Steen, Antonius; de Jong, Nico

    2015-02-01

    There is increasing use of ultrasound contrast agent in high-frequency ultrasound imaging. However, conventional contrast detection methods perform poorly at high frequencies. We performed systematic in vitro comparisons of subharmonic, non-linear fundamental and ultraharmonic imaging for different depths and ultrasound contrast agent concentrations (Vevo 2100 system with MS250 probe and MicroMarker ultrasound contrast agent, VisualSonics, Toronto, ON, Canada). We investigated 4-, 6- and 10-cycle bursts at three power levels with the following pulse sequences: B-mode, amplitude modulation, pulse inversion and combined pulse inversion/amplitude modulation. The contrast-to-tissue (CTR) and contrast-to-artifact (CAR) ratios were calculated. At a depth of 8 mm, subharmonic pulse-inversion imaging performed the best (CTR = 26 dB, CAR = 18 dB) and at 16 mm, non-linear amplitude modulation imaging was the best contrast imaging method (CTR = 10 dB). Ultraharmonic imaging did not result in acceptable CTRs and CARs. The best candidates from the in vitro study were tested in vivo in chicken embryo and mouse models, and the results were in a good agreement with the in vitro findings.

  16. A framework for simulating ultrasound imaging based on first order nonlinear pressure–velocity relations

    DEFF Research Database (Denmark)

    Du, Yigang; Fan, Rui; Li, Yong

    2016-01-01

    An ultrasound imaging framework modeled with the first order nonlinear pressure–velocity relations (NPVR) based simulation and implemented by a half-time staggered solution and pseudospectral method is presented in this paper. The framework is capable of simulating linear and nonlinear ultrasound...... propagation and reflections in a heterogeneous medium with different sound speeds and densities. It can be initialized with arbitrary focus, excitation and apodization for multiple individual channels in both 2D and 3D spatial fields. The simulated channel data can be generated using this framework......, and ultrasound image can be obtained by beamforming the simulated channel data. Various results simulated by different algorithms are illustrated for comparisons. The root mean square (RMS) errors for each compared pulses are calculated. The linear propagation is validated by an angular spectrum approach (ASA...

  17. Far-field optical imaging with subdiffraction resolution enabled by nonlinear saturation absorption

    Science.gov (United States)

    Ding, Chenliang; Wei, Jingsong

    2016-01-01

    The resolution of far-field optical imaging is required to improve beyond the Abbe limit to the subdiffraction or even the nanoscale. In this work, inspired by scanning electronic microscopy (SEM) imaging, in which carbon (or Au) thin films are usually required to be coated on the sample surface before imaging to remove the charging effect while imaging by electrons. We propose a saturation-absorption-induced far-field super-resolution optical imaging method (SAI-SRIM). In the SAI-SRIM, the carbon (or Au) layers in SEM imaging are replaced by nonlinear-saturation-absorption (NSA) thin films, which are directly coated onto the sample surfaces using advanced thin film deposition techniques. The surface fluctuant morphologies are replicated to the NSA thin films, accordingly. The coated sample surfaces are then imaged using conventional laser scanning microscopy. Consequently, the imaging resolution is greatly improved, and subdiffraction-resolved optical images are obtained theoretically and experimentally. The SAI-SRIM provides an effective and easy way to achieve far-field super-resolution optical imaging for sample surfaces with geometric fluctuant morphology characteristics.

  18. 3-D zebrafish embryo image filtering by nonlinear partial differential equations.

    Science.gov (United States)

    Rizzi, Barbara; Campana, Matteo; Zanella, Cecilia; Melani, Camilo; Cunderlik, Robert; Krivá, Zuzana; Bourgine, Paul; Mikula, Karol; Peyriéras, Nadine; Sarti, Alessandro

    2007-01-01

    We discuss application of nonlinear PDE based methods to filtering of 3-D confocal images of embryogenesis. We focus on the mean curvature driven and the regularized Perona-Malik equations, where standard as well as newly suggested edge detectors are used. After presenting the related mathematical models, the practical results are given and discussed by visual inspection and quantitatively using the mean Hausdorff distance.

  19. Radiopacity of restorative materials using digital images Radiopacidade de materiais restauradores utilizando imagens digitais

    Directory of Open Access Journals (Sweden)

    Leda Maria Pescinini Salzedas

    2006-04-01

    Full Text Available The radiopacity of esthetic restorative materials has been established as an important requirement, improving the radiographic diagnosis. The aim of this study was to evaluate the radiopacity of six restorative materials using a direct digital image system, comparing them to the dental tissues (enamel-dentin, expressed as equivalent thickness of aluminum (millimeters of aluminum. Five specimens of each material were made. Three 2-mm thick longitudinal sections were cut from an intact extracted permanent molar tooth (including enamel and dentin. An aluminum step wedge with 9 steps was used. The samples of different materials were placed on a phosphor plate together with a tooth section, aluminum step wedge and metal code letter, and were exposed using a dental x-ray unit. Five measurements of radiographic density were obtained from each image of each item assessed (restorative material, enamel, dentin, each step of the aluminum step wedge and the mean of these values was calculated. Radiopacity values were subsequently calculated as equivalents of aluminum thickness. Analysis of variance (ANOVA indicated significant differences in radiopacity values among the materials (PA radiopacidade dos materiais tem sido valorizada como importante requisito, incrementando o diagnóstico radiográfico. O objetivo deste estudo foi avaliar, no sistema digital Digora, as densidades radiográficas de 06 materiais restauradores comparando-os aos tecidos dentais (esmalte e dentina, expressos em milímetros de alumínio (mm Al. Foram confeccionadas 05 amostras de cada material e três cortes de um molar extraído hígido (incluindo esmalte e dentina, com 2 mm de espessura, e um penetrômetro de alumínio com 09 degraus. Sobre cada placa óptica foram colocados amostras dos diferentes materiais, um corte do dente humano, o penetrômetro e a identificação, e feita a exposição utilizando um aparelho de raios X. Foram obtidas 05 medidas de densidade radiográfica de

  20. ADI splitting schemes for a fourth-order nonlinear partial differential equation from image processing

    KAUST Repository

    Calatroni, Luca

    2013-08-01

    We present directional operator splitting schemes for the numerical solution of a fourth-order, nonlinear partial differential evolution equation which arises in image processing. This equation constitutes the H -1-gradient flow of the total variation and represents a prototype of higher-order equations of similar type which are popular in imaging for denoising, deblurring and inpainting problems. The efficient numerical solution of this equation is very challenging due to the stiffness of most numerical schemes. We show that the combination of directional splitting schemes with implicit time-stepping provides a stable and computationally cheap numerical realisation of the equation.

  1. Imaging arterial cells, atherosclerosis, and restenosis by multimodal nonlinear optical microscopy

    Science.gov (United States)

    Wang, Han-Wei; Simianu, Vlad; Locker, Matthew J.; Sturek, Michael; Cheng, Ji-Xin

    2008-02-01

    By integrating sum-frequency generation (SFG), and two-photon excitation fluorescence (TPEF) on a coherent anti-Stokes Raman scattering (CARS) microscope platform, multimodal nonlinear optical (NLO) imaging of arteries and atherosclerotic lesions was demonstrated. CARS signals arising from CH II-rich membranes allowed visualization of endothelial cells and smooth muscle cells in a carotid artery. Additionally, CARS microscopy allowed vibrational imaging of elastin and collagen fibrils which are rich in CH II bonds in their cross-linking residues. The extracellular matrix organization was further confirmed by TPEF signals arising from elastin's autofluorescence and SFG signals arising from collagen fibrils' non-centrosymmetric structure. The system is capable of identifying different atherosclerotic lesion stages with sub-cellular resolution. The stages of atherosclerosis, such as macrophage infiltration, lipid-laden foam cell accumulation, extracellular lipid distribution, fibrous tissue deposition, plaque establishment, and formation of other complicated lesions could be viewed by our multimodal CARS microscope. Collagen percentages in the region adjacent to coronary artery stents were resolved. High correlation between NLO and histology imaging evidenced the validity of the NLO imaging. The capability of imaging significant components of an arterial wall and distinctive stages of atherosclerosis in a label-free manner suggests the potential application of multimodal nonlinear optical microscopy to monitor the onset and progression of arterial diseases.

  2. Image Encryption Using Stream Cipher Based on Nonlinear Combination Generator with Enhanced Security

    Directory of Open Access Journals (Sweden)

    Belmeguenaï Aîssa

    2013-03-01

    Full Text Available The images are very largely used in our daily life; the security of their transfer became necessary. In this work a novel image encryption scheme using stream cipher algorithm based on nonlinear combination generator is developed. The main contribution of this work is to enhance the security of encrypted image. The proposed scheme is based on the use the several linear feedback shifts registers whose feedback polynomials are primitive and of degrees are all pairwise coprimes combined by resilient function whose resiliency order, algebraic degree and nonlinearity attain Siegenthaler’s and Sarkar, al.’s bounds. This proposed scheme is simple and highly efficient. In order to evaluate performance, the proposed algorithm was measured through a series of tests. These tests included visual test and histogram analysis, key space analysis, correlation coefficient analysis, image entropy, key sensitivity analysis, noise analysis, Berlekamp-Massey attack, correlation attack and algebraic attack. Experimental results demonstrate the proposed system is highly key sensitive, highly resistance to the noises and shows a good resistance against brute-force, statistical attacks, Berlekamp-Massey attack, correlation attack, algebraic attack and a robust system which makes it a potential candidate for encryption of image.

  3. Application of image restoration and three-dimensional visualization techniques to frog microvessels in-situ loaded with fluorescent indicators

    Science.gov (United States)

    Pagakis, Stamatis N.; Curry, Fitz-Roy E.; Lenz, Joyce F.

    1993-07-01

    In situ experiments on microvessels require image sensors of wide dynamic range due to large variations of the intensity in the scene, and 3D visualization due to the thickness of the preparation. The images require restoration because of the inherent tissue movement, out-of- focus-light contamination, and blur. To resolve the above problems, we developed an imaging system for quantitative imaging based on a 12 bits/pixel cooled CCD camera and a PC based digital imaging system. We applied the optical sectioning technique with image restoration using a modified nearest neighbor algorithm and iterative constrained deconvolution on each of the 2D optical sections. For the 3D visualization of the data, a volume rendering software was used. The data provided 3D images of the distribution of fluorescent indicators in intact microvessels. Optical cross sections were also compared with cross sections of the same microvessels examined in the electron microscope after their luminal surfaces were labeled with a tracer which was both electron dense and fluorescent. This procedure enabled precise identification of the endothelial cells in the microvessel wall as the principal site of accumulation of the fluorescent calcium indicator, fura-2, during microperfusion experiments.

  4. Blind restoration for nonuniform aerial images using nonlocal Retinex model and shearlet-based higher-order regularization

    Science.gov (United States)

    Chen, Rui; Jia, Huizhu; Xie, Xiaodong; Gao, Wen

    2017-05-01

    Aerial images are often degraded by space-varying motion blurs and simultaneous uneven illumination. To recover a high-quality aerial image from its nonuniform version, we propose a patchwise restoration approach based on a key observation that the degree of blurring is inevitably affected by the illumination conditions. A nonlocal Retinex model is developed to accurately estimate the reflectance component from the degraded aerial image. Thereafter, the uneven illumination is corrected well. Then nonuniform coupled blurring in the enhanced reflectance image is alleviated and transformed toward uniform distribution, which will facilitate the subsequent deblurring. For constructing the multiscale sparsified regularization, the discrete shearlet transform is improved to better represent anisotropic image features in terms of directional sensitivity and selectivity. In addition, a new adaptive variant of total generalized variation is proposed to act as the structure-preserving regularizer. These complementary regularizers are elegantly integrated into an objective function. The final deblurred image with uniform illumination can be obtained by applying a fast alternating direction scheme to solve the derived function. The experimental results demonstrate that our algorithm can not only effectively remove both the space-varying illumination and motion blurs in aerial images, but also recover the abundant details of aerial scenes with top-level objective and subjective quality, and outperforms other state-of-the-art restoration methods.

  5. Image formation by linear and nonlinear digital scanned light-sheet fluorescence microscopy with Gaussian and Bessel beam profiles

    Science.gov (United States)

    Olarte, Omar E.; Licea-Rodriguez, Jacob; Palero, Jonathan A.; Gualda, Emilio J.; Artigas, David; Mayer, Jürgen; Swoger, Jim; Sharpe, James; Rocha-Mendoza, Israel; Rangel-Rojo, Raul; Loza-Alvarez, Pablo

    2012-01-01

    We present the implementation of a combined digital scanned light-sheet microscope (DSLM) able to work in the linear and nonlinear regimes under either Gaussian or Bessel beam excitation schemes. A complete characterization of the setup is performed and a comparison of the performance of each DSLM imaging modality is presented using in vivo Caenorhabditis elegans samples. We found that the use of Bessel beam nonlinear excitation results in better image contrast over a wider field of view. PMID:22808423

  6. Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

    Science.gov (United States)

    Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

    2017-01-01

    The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

  7. Fast wavelet packet transform-based algorithm for numerical solution of image restoration problems in a parallel environment

    Science.gov (United States)

    Carracciuolo, Luisa; D'Amore, Luisa; Murli, Almerico

    1998-10-01

    We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for Image Restoration problems. We propose a parallel implementation for MIMD distributed memory environments. The key insight of our approach is the use of distributed versions of Level 3 Basic Linear Algebra Subprograms as computational building blocks and the use of Basic Linear Algebra Communication Subprograms as communication building blocks for advanced architecture computers. The use of these low-level mathematical software libraries guarantees the development of efficient, portable and scalable high-level algorithms and hides many details of the parallelism from the user's point of view. Numerical experiments on a simulated image restoration applications are shown. The parallel software has been tested on a 12 nodes IBM SP2 available at the Center for Research on Parallel Computing and Supercomputers in Naples, Italy).

  8. Rationally encapsulated gold nanorods improving both linear and nonlinear photoacoustic imaging contrast in vivo.

    Science.gov (United States)

    Gao, Fei; Bai, Linyi; Liu, Siyu; Zhang, Ruochong; Zhang, Jingtao; Feng, Xiaohua; Zheng, Yuanjin; Zhao, Yanli

    2017-01-07

    Photoacoustic tomography has emerged as a promising non-invasive imaging technique that integrates the merits of high optical contrast with high ultrasound resolution in deep scattering medium. Unfortunately, the blood background in vivo seriously impedes the quality of imaging due to its comparable optical absorption with contrast agents, especially in conventional linear photoacoustic imaging modality. In this study, we demonstrated that two hybrids consisting of gold nanorods (Au NRs) and zinc tetra(4-pyridyl)porphyrin (ZnTPP) exhibited a synergetic effect in improving optical absorption, conversion efficiency from light to heat, and thermoelastic expansion, leading to a notable enhancement in both linear (four times greater) and nonlinear (more than six times) photoacoustic signals as compared with conventional Au NRs. Subsequently, we carefully investigated the interesting factors that may influence photoacoustic signal amplification, suggesting that the coating of ZnTPP on Au NRs could result in the reduction of gold interfacial thermal conductance with a solvent, so that the heat is more confined within the nanoparticle clusters for a significant enhancement of local temperature. Hence, both the linear and nonlinear photoacoustic signals are enhanced on account of better thermal confinement. The present work not only shows that ZnTPP coated Au NRs could serve as excellent photoacoustic nanoamplifiers, but also brings a perspective for photoacoustic image-guided therapy.

  9. Near Infrared (NIR) Imaging Techniques Using Lasers and Nonlinear Crystal Optical Parametric Oscillator/Amplifier (OPO/OPA) Imaging and Transferred Electron (TE) Photocathode Image Intensifiers

    Energy Technology Data Exchange (ETDEWEB)

    YATES,GEORGE J.; MCDONALD,THOMAS E. JR.; BLISS,DAVID E.; CAMERON,STEWART M.; GREIVES,KENNETH H.; ZUTAVERN,FRED J.

    2000-12-20

    Laboratory experiments utilizing different near-infrared (NIR) sensitive imaging techniques for LADAR range gated imaging at eye-safe wavelengths are presented. An OPO/OPA configuration incorporating a nonlinear crystal for wavelength conversion of 1.56 micron probe or broadcast laser light to 807 nm light by utilizing a second pump laser at 532 nm for gating and gain, was evaluated for sensitivity, resolution, and general image quality. These data are presented with similar test results obtained from an image intensifier based upon a transferred electron (TE) photocathode with high quantum efficiency (QE) in the 1-2 micron range, with a P-20 phosphor output screen. Data presented include range-gated imaging performance in a cloud chamber with varying optical attenuation of laser reflectance images.

  10. High-resolution laser radar for 3D imaging in artwork cataloging, reproduction, and restoration

    Science.gov (United States)

    Ricci, Roberto; Fantoni, Roberta; Ferri de Collibus, Mario; Fornetti, Giorgio G.; Guarneri, Massimiliano; Poggi, Claudio

    2003-10-01

    A high resolution Amplitude Modulated Laser Radar (AM-LR) sensor has recently been developed, aimed at accurately reconstructing 3D digital models of real targets, either single objects or complex scenes. The sensor sounding beam can be swept linearly across the object or circularly around it, by placing the object on a controlled rotating platform, enabling to obtain respectively linear and cylindrical range maps. Both amplitude and phase shift of the modulating wave of back-scattered light are collected and processed, providing respectively a shade-free, high resolution, photographic-like picture and accurate range data in the form of a range image. The resolution of range measurements depends mainly on the laser modulation frequency, provided that the power of the backscattered light reaching the detector is at least a few nW (current best performances are ~100 μm). The complete object surface can be reconstructed from the sampled points by using specifically developed software tools. The system has been successfully applied to scan different types of real surfaces (stone, wood, alloys, bones), with relevant applications in different fields, ranging from industrial machining to medical diagnostics, to vision in hostile environments. Examples of artwork reconstructed models (pottery, marble statues) are presented and the relevance of this technology for reverse engineering applied to cultural heritage conservation and restoration are discussed. Final 3D models can be passed to numeric control machines for rapid-prototyping, exported in standard formats for CAD/CAM purposes and made available on the Internet by adopting a virtual museum paradigm, thus possibly enabling specialists to perform remote inspections on high resolution digital reproductions of hardly accessible masterpieces.

  11. Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification

    Science.gov (United States)

    Wen, Zaidao; Hou, Biao; Jiao, Licheng

    2017-07-01

    Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

  12. Fresnel domain nonlinear optical image encryption scheme based on Gerchberg-Saxton phase-retrieval algorithm.

    Science.gov (United States)

    Rajput, Sudheesh K; Nishchal, Naveen K

    2014-01-20

    We propose a novel nonlinear image-encryption scheme based on a Gerchberg-Saxton (G-S) phase-retrieval algorithm in the Fresnel transform domain. The decryption process can be performed using conventional double random phase encoding (DRPE) architecture. The encryption is realized by applying G-S phase-retrieval algorithm twice, which generates two asymmetric keys from intermediate phases. The asymmetric keys are generated in such a way that decryption is possible optically with a conventional DRPE method. Due to the asymmetric nature of the keys, the proposed encryption process is nonlinear and offers enhanced security. The cryptanalysis has been carried out, which proves the robustness of proposed scheme against known-plaintext, chosen-plaintext, and special attacks. A simple optical setup for decryption has also been suggested. Results of computer simulation support the idea of the proposed cryptosystem.

  13. Combined perfusion and doppler imaging using plane-wave nonlinear detection and microbubble contrast agents.

    Science.gov (United States)

    Tremblay-Darveau, Charles; Williams, Ross; Milot, Laurent; Bruce, Matthew; Burns, Peter N

    2014-12-01

    Plane-wave imaging offers image acquisition rates at the pulse repetition frequency, effectively increasing the imaging frame rates by up to two orders of magnitude over conventional line-by-line imaging. This form of acquisition can be used to achieve very long ensemble lengths in nonlinear modes such as pulse inversion Doppler, which enables new imaging trade-offs that were previously unattainable. We first demonstrate in this paper that the coherence of microbubble signals under repeated exposure to acoustic pulses of low mechanical index can be as high as 204 ± 5 pulses, which is long enough to allow an accurate power Doppler measurement. We then show that external factors, such as tissue acceleration, restrict the detection of perfusion at the capillary level with linear Doppler, even if long Doppler ensembles are considered. Hence, perfusion at the capillary level can only be detected with ultrasound through combined microbubbles and Doppler imaging. Finally, plane-wave contrast-enhanced power and color Doppler are performed on a rabbit kidney in vivo as a proof of principle. We establish that long pulse-inversion Doppler sequences and conventional wall-filters can create an image that simultaneously resolves both the vascular morphology of veins and arteries, and perfusion at the capillary level with frame rates above 100 Hz.

  14. A non-linear iterative method for multi-layer DOT sub-surface imaging system.

    Science.gov (United States)

    Hou, Hsiang-Wen; Wu, Shih-Yang; Sun, Hao-Jan; Fang, Wai-Chi

    2014-01-01

    Diffuse Optical Tomography (DOT) has become an emerging non-invasive technology, and has been widely used in clinical diagnosis. Functional near-infrared (FNIR) is one of the important applications of DOT. However, FNIR is used to reconstruct two-dimensional (2D) images for the sake of good spatial and temporal resolution. In this paper we propose a multiple-input and multiple-output (MIMO) based data extraction algorithm method in order to increase the spatial and temporal resolution. The non-linear iterative method is used to reconstruct better resolution images layer by layer. In terms of theory, the simulation results and original images are nearly identical. The proposed reconstruction method performs good spatial resolution, and has a depth resolutions capacity of three layers.

  15. Landmark Optimization Using Local Curvature for Point-Based Nonlinear Rodent Brain Image Registration

    Directory of Open Access Journals (Sweden)

    Yutong Liu

    2012-01-01

    Full Text Available Purpose. To develop a technique to automate landmark selection for point-based interpolating transformations for nonlinear medical image registration. Materials and Methods. Interpolating transformations were calculated from homologous point landmarks on the source (image to be transformed and target (reference image. Point landmarks are placed at regular intervals on contours of anatomical features, and their positions are optimized along the contour surface by a function composed of curvature similarity and displacements of the homologous landmarks. The method was evaluated in two cases (=5 each. In one, MRI was registered to histological sections; in the second, geometric distortions in EPI MRI were corrected. Normalized mutual information and target registration error were calculated to compare the registration accuracy of the automatically and manually generated landmarks. Results. Statistical analyses demonstrated significant improvement (<0.05 in registration accuracy by landmark optimization in most data sets and trends towards improvement (<0.1 in others as compared to manual landmark selection.

  16. CUDA-based acceleration and BPN-assisted automation of bilateral filtering for brain MR image restoration.

    Science.gov (United States)

    Chang, Herng-Hua; Chang, Yu-Ning

    2017-04-01

    Bilateral filters have been substantially exploited in numerous magnetic resonance (MR) image restoration applications for decades. Due to the deficiency of theoretical basis on the filter parameter setting, empirical manipulation with fixed values and noise variance-related adjustments has generally been employed. The outcome of these strategies is usually sensitive to the variation of the brain structures and not all the three parameter values are optimal. This article is in an attempt to investigate the optimal setting of the bilateral filter, from which an accelerated and automated restoration framework is developed. To reduce the computational burden of the bilateral filter, parallel computing with the graphics processing unit (GPU) architecture is first introduced. The NVIDIA Tesla K40c GPU with the compute unified device architecture (CUDA) functionality is specifically utilized to emphasize thread usages and memory resources. To correlate the filter parameters with image characteristics for automation, optimal image texture features are subsequently acquired based on the sequential forward floating selection (SFFS) scheme. Subsequently, the selected features are introduced into the back propagation network (BPN) model for filter parameter estimation. Finally, the k-fold cross validation method is adopted to evaluate the accuracy of the proposed filter parameter prediction framework. A wide variety of T1-weighted brain MR images with various scenarios of noise levels and anatomic structures were utilized to train and validate this new parameter decision system with CUDA-based bilateral filtering. For a common brain MR image volume of 256 × 256 × 256 pixels, the speed-up gain reached 284. Six optimal texture features were acquired and associated with the BPN to establish a "high accuracy" parameter prediction system, which achieved a mean absolute percentage error (MAPE) of 5.6%. Automatic restoration results on 2460 brain MR images received an average

  17. 3D early embryogenesis image filtering by nonlinear partial differential equations.

    Science.gov (United States)

    Krivá, Z; Mikula, K; Peyriéras, N; Rizzi, B; Sarti, A; Stasová, O

    2010-08-01

    We present nonlinear diffusion equations, numerical schemes to solve them and their application for filtering 3D images obtained from laser scanning microscopy (LSM) of living zebrafish embryos, with a goal to identify the optimal filtering method and its parameters. In the large scale applications dealing with analysis of 3D+time embryogenesis images, an important objective is a correct detection of the number and position of cell nuclei yielding the spatio-temporal cell lineage tree of embryogenesis. The filtering is the first and necessary step of the image analysis chain and must lead to correct results, removing the noise, sharpening the nuclei edges and correcting the acquisition errors related to spuriously connected subregions. In this paper we study such properties for the regularized Perona-Malik model and for the generalized mean curvature flow equations in the level-set formulation. A comparison with other nonlinear diffusion filters, like tensor anisotropic diffusion and Beltrami flow, is also included. All numerical schemes are based on the same discretization principles, i.e. finite volume method in space and semi-implicit scheme in time, for solving nonlinear partial differential equations. These numerical schemes are unconditionally stable, fast and naturally parallelizable. The filtering results are evaluated and compared first using the Mean Hausdorff distance between a gold standard and different isosurfaces of original and filtered data. Then, the number of isosurface connected components in a region of interest (ROI) detected in original and after the filtering is compared with the corresponding correct number of nuclei in the gold standard. Such analysis proves the robustness and reliability of the edge preserving nonlinear diffusion filtering for this type of data and lead to finding the optimal filtering parameters for the studied models and numerical schemes. Further comparisons consist in ability of splitting the very close objects which

  18. Nonlinear Imaging of Microbubble Contrast Agent Using the Volterra Filter: In Vivo Results.

    Science.gov (United States)

    Du, Juan; Liu, Dalong; Ebbini, Emad S

    2016-12-01

    A nonlinear filtering approach to imaging the dynamics of microbubble ultrasound contrast agents (UCAs) in microvessels is presented. The approach is based on the adaptive third-order Volterra filter (TVF), which separates the linear, quadratic, and cubic components from beamformed pulse-echo ultrasound data. The TVF captures polynomial nonlinearities utilizing the full spectral components of the echo data and not from prespecified bands, e.g., second or third harmonics. This allows for imaging using broadband pulse transmission to preserve the axial resolution and the SNR. In this paper, we present the results from imaging the UCA activity in a 200- [Formula: see text] cellulose tube embedded in a tissue-mimicking phantom using a linear array diagnostic probe. The contrast enhancement was quantified by computing the contrast-to-tissue ratio (CTR) for the different imaging components, i.e., B-mode, pulse inversion (PI), and the TVF components. The temporal mean and standard deviation of the CTR values were computed for all frames in a given data set. Quadratic and cubic images, referred to as QB-mode and CB-mode, produced higher mean CTR values than B-mode, which showed improved sensitivity. Compared with PI, they produced similar or higher mean CTR values with greater spatial specificity. We also report in vivo results from imaging UCA activity in an implanted LNCaP tumor with heterogeneous perfusion. The temporal means and standard deviations of the echogenicity were evaluated in small regions with different perfusion levels in the presence and absence of UCA. The in vivo measurements behaved consistently with the corresponding calculations obtained under microflow conditions in vitro. Specifically, the nonlinear VF components produced larger increases in the temporal mean and standard deviation values compared with B-mode in regions with low to relatively high perfusion. These results showed that polynomial filters such as the TVF can provide an important tool

  19. Dental non-linear image registration and collection method with 3D reconstruction and change detection

    Science.gov (United States)

    Rahmes, Mark; Fagan, Dean; Lemieux, George

    2017-03-01

    The capability of a software algorithm to automatically align same-patient dental bitewing and panoramic x-rays over time is complicated by differences in collection perspectives. We successfully used image correlation with an affine transform for each pixel to discover common image borders, followed by a non-linear homography perspective adjustment to closely align the images. However, significant improvements in image registration could be realized if images were collected from the same perspective, thus facilitating change analysis. The perspective differences due to current dental image collection devices are so significant that straightforward change analysis is not possible. To address this, a new custom dental tray could be used to provide the standard reference needed for consistent positioning of a patient's mouth. Similar to sports mouth guards, the dental tray could be fabricated in standard sizes from plastic and use integrated electronics that have been miniaturized. In addition, the x-ray source needs to be consistently positioned in order to collect images with similar angles and scales. Solving this pose correction is similar to solving for collection angle in aerial imagery for change detection. A standard collection system would provide a method for consistent source positioning using real-time sensor position feedback from a digital x-ray image reference. Automated, robotic sensor positioning could replace manual adjustments. Given an image set from a standard collection, a disparity map between images can be created using parallax from overlapping viewpoints to enable change detection. This perspective data can be rectified and used to create a three-dimensional dental model reconstruction.

  20. Multimodal nonlinear imaging of atherosclerotic plaques differentiation of triglyceride and cholesterol deposits

    Directory of Open Access Journals (Sweden)

    Christian Matthäus

    2014-09-01

    Full Text Available Cardiovascular diseases in general and atherothrombosis as the most common of its individual disease entities is the leading cause of death in the developed countries. Therefore, visualization and characterization of inner arterial plaque composition is of vital diagnostic interest, especially for the early recognition of vulnerable plaques. Established clinical techniques provide valuable morphological information but cannot deliver information about the chemical composition of individual plaques. Therefore, spectroscopic imaging techniques have recently drawn considerable attention. Based on the spectroscopic properties of the individual plaque components, as for instance different types of lipids, the composition of atherosclerotic plaques can be analyzed qualitatively as well as quantitatively. Here, we compare the feasibility of multimodal nonlinear imaging combining two-photon fluorescence (TPF, coherent anti-Stokes Raman scattering (CARS and second-harmonic generation (SHG microscopy to contrast composition and morphology of lipid deposits against the surrounding matrix of connective tissue with diffraction limited spatial resolution. In this contribution, the spatial distribution of major constituents of the arterial wall and atherosclerotic plaques like elastin, collagen, triglycerides and cholesterol can be simultaneously visualized by a combination of nonlinear imaging methods, providing a powerful label-free complement to standard histopathological methods with great potential for in vivo application.

  1. A Modern Image Quality Measurement Method for Blind Image Restoration%基于变分的盲图像复原质量评价指标

    Institute of Scientific and Technical Information of China (English)

    成孝刚; 安明伟; 阮雅端; 陈启美

    2013-01-01

    盲图像复原过程中,图像质量评价至关重要.通过分析重构图像质量与其总变分值之间的关系,提出了用于图像复原的一种基于总变分(Total bounded variation,TBV)的图像质量评估方法,并构建关系模型,证明了原始清晰图像的总变分值在所有模糊图像中具有极大值,且在所有重构图像的变分值中具有极小值.通过分析,得出结论:当总变分取极值时,基于所提度量方法,可以获得更好的盲图像重构效果.最后,比较了原始清晰图像、模糊图像和重构图像之间的变分值,计算机仿真验证了该方法的有效性和准确性.%In the process of blind image restoration, image quality assessment is of paramount importance. In this paper, A novel image quality assessment method is presented by analyzing the relation between reconstructed image quality and its total bounded variation (TBV), on this basis, the relationship model is constructed, that is, the original clear image's TBV is maximum in all the blurring image, and it is minimal in all the reconstructed image. Further, based on the metric method proposed, the better blind image reconstruction effect is obtained when the TBV is extremal. Finally, the TBV of original clear image, blurred images and blind restored images are compared, the simulation results shows the validation and veracity of the method proposed.

  2. NESP: Nonlinear enhancement and selection of plane for optimal segmentation and recognition of scene word images

    Science.gov (United States)

    Kumar, Deepak; Anil Prasad, M. N.; Ramakrishnan, A. G.

    2013-01-01

    In this paper, we report a breakthrough result on the difficult task of segmentation and recognition of coloured text from the word image dataset of ICDAR robust reading competition challenge 2: reading text in scene images. We split the word image into individual colour, gray and lightness planes and enhance the contrast of each of these planes independently by a power-law transform. The discrimination factor of each plane is computed as the maximum between-class variance used in Otsu thresholding. The plane that has maximum discrimination factor is selected for segmentation. The trial version of Omnipage OCR is then used on the binarized words for recognition. Our recognition results on ICDAR 2011 and ICDAR 2003 word datasets are compared with those reported in the literature. As baseline, the images binarized by simple global and local thresholding techniques were also recognized. The word recognition rate obtained by our non-linear enhancement and selection of plance method is 72.8% and 66.2% for ICDAR 2011 and 2003 word datasets, respectively. We have created ground-truth for each image at the pixel level to benchmark these datasets using a toolkit developed by us. The recognition rate of benchmarked images is 86.7% and 83.9% for ICDAR 2011 and 2003 datasets, respectively.

  3. Cubic generalized B-splines for interpolation and nonlinear filtering of images

    Science.gov (United States)

    Tshughuryan, Heghine

    1997-04-01

    This paper presents the introduction and using of the generalized or parametric B-splines, namely the cubic generalized B-splines, in various signal processing applications. The theory of generalized B-splines is briefly reviewed and also some important properties of generalized B-splines are investigated. In this paper it is shown the use of generalized B-splines as a tool to solve the quasioptimal algorithm problem for nonlinear filtering. Finally, the experimental results are presented for oscillatory and other signals and images.

  4. Nonlinear chemical imaging microscopy: near-field third harmonic generation imaging of human red blood cells.

    Science.gov (United States)

    Schaller, R D; Johnson, J C; Saykally, R J

    2000-11-01

    Third harmonic generation (THG) imaging using a near-field scanning optical microscope (NSOM) is demonstrated for the first time. A femtosecond, tunable near-infrared laser was used to generate both nonresonant and resonantly enhanced third harmonic radiation in human red blood cells. We show that resonantly enhanced THG is a chemically specific bulk probe in NSOM imaging by tuning the excitation source onto and off of resonance with the Soret transition of oxyhemoglobin. Additionally, we provide evidence that tightly focused, nonresonant, far-field THG imaging experiments do not produce contrast that is truly surface specific.

  5. Linear and Non-Linear Optical Imaging of Cancer Cells with Silicon Nanoparticles

    Science.gov (United States)

    Tolstik, Elen; Osminkina, Liubov A.; Akimov, Denis; Gongalsky, Maksim B.; Kudryavtsev, Andrew A.; Timoshenko, Victor Yu.; Heintzmann, Rainer; Sivakov, Vladimir; Popp, Jürgen

    2016-01-01

    New approaches for visualisation of silicon nanoparticles (SiNPs) in cancer cells are realised by means of the linear and nonlinear optics in vitro. Aqueous colloidal solutions of SiNPs with sizes of about 10–40 nm obtained by ultrasound grinding of silicon nanowires were introduced into breast cancer cells (MCF-7 cell line). Further, the time-varying nanoparticles enclosed in cell structures were visualised by high-resolution structured illumination microscopy (HR-SIM) and micro-Raman spectroscopy. Additionally, the nonlinear optical methods of two-photon excited fluorescence (TPEF) and coherent anti-Stokes Raman scattering (CARS) with infrared laser excitation were applied to study the localisation of SiNPs in cells. Advantages of the nonlinear methods, such as rapid imaging, which prevents cells from overheating and larger penetration depth compared to the single-photon excited HR-SIM, are discussed. The obtained results reveal new perspectives of the multimodal visualisation and precise detection of the uptake of biodegradable non-toxic SiNPs by cancer cells and they are discussed in view of future applications for the optical diagnostics of cancer tumours. PMID:27626408

  6. PDE-based nonlinear diffusion techniques for denoising scientific and industrial images: an empirical study

    Science.gov (United States)

    Weeratunga, Sisira K.; Kamath, Chandrika

    2002-05-01

    Removing noise from data is often the first step in data analysis. Denoising techniques should not only reduce the noise, but do so without blurring or changing the location of the edges. Many approaches have been proposed to accomplish this; in this paper, we focus on one such approach, namely the use of non-linear diffusion operators. This approach has been studied extensively from a theoretical viewpoint ever since the 1987 work of Perona and Malik showed that non-linear filters outperformed the more traditional linear Canny edge detector. We complement this theoretical work by investigating the performance of several isotropic diffusion operators on test images from scientific domains. We explore the effects of various parameters such as the choice of diffusivity function, explicit and implicit methods for the discretization of the PDE, and approaches for the spatial discretization of the non-linear operator etc. We also compare these schemes with simple spatial filters and the more complex wavelet-based shrinkage techniques. Our empirical results show that, with an appropriate choice of parameters, diffusion-based schemes can be as effective as competitive techniques.

  7. Linear and Non-Linear Optical Imaging of Cancer Cells with Silicon Nanoparticles.

    Science.gov (United States)

    Tolstik, Elen; Osminkina, Liubov A; Akimov, Denis; Gongalsky, Maksim B; Kudryavtsev, Andrew A; Timoshenko, Victor Yu; Heintzmann, Rainer; Sivakov, Vladimir; Popp, Jürgen

    2016-09-12

    New approaches for visualisation of silicon nanoparticles (SiNPs) in cancer cells are realised by means of the linear and nonlinear optics in vitro. Aqueous colloidal solutions of SiNPs with sizes of about 10-40 nm obtained by ultrasound grinding of silicon nanowires were introduced into breast cancer cells (MCF-7 cell line). Further, the time-varying nanoparticles enclosed in cell structures were visualised by high-resolution structured illumination microscopy (HR-SIM) and micro-Raman spectroscopy. Additionally, the nonlinear optical methods of two-photon excited fluorescence (TPEF) and coherent anti-Stokes Raman scattering (CARS) with infrared laser excitation were applied to study the localisation of SiNPs in cells. Advantages of the nonlinear methods, such as rapid imaging, which prevents cells from overheating and larger penetration depth compared to the single-photon excited HR-SIM, are discussed. The obtained results reveal new perspectives of the multimodal visualisation and precise detection of the uptake of biodegradable non-toxic SiNPs by cancer cells and they are discussed in view of future applications for the optical diagnostics of cancer tumours.

  8. Experimental investigation on the influence of instrument settings on pixel size and nonlinearity in SEM image formation

    DEFF Research Database (Denmark)

    Carli, Lorenzo; Genta, Gianfranco; Cantatore, Angela

    2010-01-01

    The work deals with an experimental investigation on the influence of three Scanning Electron Microscope (SEM) instrument settings, accelerating voltage, spot size and magnification, on the image formation process. Pixel size and nonlinearity were chosen as output parameters related to image qual...

  9. In vivo monitoring of protein-bound and free NADH during ischemia by nonlinear spectral imaging microscopy

    NARCIS (Netherlands)

    J.A. Palero (Jonathan); A.N. Bader (Arjen); H.S. de Bruijn (Riette); A.V.D.P. van den Heuvel (Angélique); H.J.C.M. Sterenborg (Dick); H.C. Gerritsen (Hans)

    2011-01-01

    textabstractNonlinear spectral imaging microscopy (NSIM) allows simultaneous morphological and spectroscopic investigation of intercellular events within living animals. In this study we used NSIM for in vivo timelapse in-depth spectral imaging and monitoring of protein-bound and free reduced nicoti

  10. In vivo monitoring of protein-bound and free NADH during ischemia by nonlinear spectral imaging microscopy

    NARCIS (Netherlands)

    Palero, J.A.; Bader, A.N.; de Bruijn, H.S.; van der Ploeg van den Heuvel, A.; Sterenborg, H.J.C.M.; Gerritsen, H.C.

    2011-01-01

    Nonlinear spectral imaging microscopy (NSIM) allows simultaneous morphological and spectroscopic investigation of intercellular events within living animals. In this study we used NSIM for in vivo time-lapse in-depth spectral imaging and monitoring of protein-bound and free reduced nicotinamide aden

  11. Parallel implementation of linear and nonlinear spectral unmixing of remotely sensed hyperspectral images

    Science.gov (United States)

    Plaza, Antonio; Plaza, Javier

    2011-11-01

    Hyperspectral unmixing is a very important task for remotely sensed hyperspectral data exploitation. It addresses the (possibly) mixed nature of pixels collected by instruments for Earth observation, which are due to several phenomena including limited spatial resolution, presence of mixing effects at different scales, etc. Spectral unmixing involves the separation of a mixed pixel spectrum into its pure component spectra (called endmembers) and the estimation of the proportion (abundance) of endmember in the pixel. Two models have been widely used in the literature in order to address the mixture problem in hyperspectral data. The linear model assumes that the endmember substances are sitting side-by-side within the field of view of the imaging instrument. On the other hand, the nonlinear mixture model assumes nonlinear interactions between endmember substances. Both techniques can be computationally expensive, in particular, for high-dimensional hyperspectral data sets. In this paper, we develop and compare parallel implementations of linear and nonlinear unmixing techniques for remotely sensed hyperspectral data. For the linear model, we adopt a parallel unsupervised processing chain made up of two steps: i) identification of pure spectral materials or endmembers, and ii) estimation of the abundance of each endmember in each pixel of the scene. For the nonlinear model, we adopt a supervised procedure based on the training of a parallel multi-layer perceptron neural network using intelligently selected training samples also derived in parallel fashion. The compared techniques are experimentally validated using hyperspectral data collected at different altitudes over a so-called Dehesa (semi-arid environment) in Extremadura, Spain, and evaluated in terms of computational performance using high performance computing systems such as commodity Beowulf clusters.

  12. Research on Nonlinear Characteristics of Image Measurement System for Instantaneous Concentration Field

    Directory of Open Access Journals (Sweden)

    Wu Jing

    2013-06-01

    Full Text Available Quantitative measurement on instantaneous concentration field not only can provide scientific methods for people measuring environment wind tunnel, but also can provide important data for solving convection--diffusion problem in practical project. The established large environment and wind engineering wind tunnel needs to develop the measurement system of instantaneous concentration field in order to study concentration field of environmental pollution diffusion. Based on collecting, analyzing and selecting a large number of literatures, the paper comprehensively studies the image measurement of instantaneous concentration field, and develops the complete software and hardware system. And the developed measurement system is used to measure the results, and the nonlinear characteristics of instable concentration field are studied. Combined with experimental fluid mechanics, information technology, optical scattering and imaging theory, the paper makes quantitative calculation on instability of concentration field from an experimental point of view, which provides an important experimental result for using numerical method to explore the instability of concentration field.

  13. Imaging immune and metabolic cells of visceral adipose tissues with multimodal nonlinear optical microscopy.

    Directory of Open Access Journals (Sweden)

    Yasuyo Urasaki

    Full Text Available Visceral adipose tissue (VAT inflammation is recognized as a mechanism by which obesity is associated with metabolic diseases. The communication between adipose tissue macrophages (ATMs and adipocytes is important to understanding the interaction between immunity and energy metabolism and its roles in obesity-induced diseases. Yet visualizing adipocytes and macrophages in complex tissues is challenging to standard imaging methods. Here, we describe the use of a multimodal nonlinear optical (NLO microscope to characterize the composition of VATs of lean and obese mice including adipocytes, macrophages, and collagen fibrils in a label-free manner. We show that lipid metabolism processes such as lipid droplet formation, lipid droplet microvesiculation, and free fatty acids trafficking can be dynamically monitored in macrophages and adipocytes. With its versatility, NLO microscopy should be a powerful imaging tool to complement molecular characterization of the immunity-metabolism interface.

  14. An improved exponential filter for fast nonlinear registration of brain magnetic resonance images

    Institute of Scientific and Technical Information of China (English)

    Zhiying Long; Li Yao; Kewei Chen; Danling Peng

    2009-01-01

    A linear elastic convolution filter was derived from the eigenfunctions of the Navier-Stokes differential operator by Bro-Nielsen in order to match images with large deformations. Due to the complexity of constructing the elastic convolution filter, the algorithm's effi-ciency reduces rapidly with the increase in the image's size. In our previous work, a simple two-sided exponential filter with high efficiency was proposed to approximate an elastic filter. However, its poor smoothness may degenerate the performance. In this paper, a new expo-nential filter was constructed by utilizing a modified nonlinear curve fitting method to approximate the elastic filter. The new filter's good smoothness makes its performance comparable to an elastic filter. Its simple and separable form makes the algorithm's speed faster than the elastic filter. Furthermore, our experiments demonstrated that the new filter was suitable for both the elastic and fluid models.

  15. Designing Non-linear Frequency Modulated Signals For Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2006-01-01

    is tested experimentally using the RASMUS ultrasound system with a 7 MHz linear array transducer. Synthetic transmit aperture ultrasound imaging is applied to acquire data. The proposed design method was compared to a linear FM signal. Due to more efficient spectral usage, a gain in SNR of 4.3plusmn1.2 d......In this paper a new method for designing non-linear frequency modulated (NLFM) waveforms for ultrasound imaging is proposed. The objective is to control the amplitude spectrum of the designed waveform and still keep a constant transmit amplitude, so that the transmitted energy is maximized...... in the transducer can be decreased. Secondly, by choosing an appropriate amplitude spectrum, no additional temporal tapering has to be applied to the matched filter to achieve sufficient range sidelobe suppression. Proper design results in waveforms with a range sidelobe level beyond -80 dB. The design method...

  16. A Hybrid Method of medical Image Restoration with Gaussian and Impulsive Noise; Un Metodo Hibrido de Restauracion de Images Medidas con Ruido Gausino e Impulsivo

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez, M. G.; Vidal, V.; Verdu, G.; Mayo, P.; Rodenas, F.

    2011-07-01

    The noise removal techniques to restore noisy images is currently an important issue, for example, medical images obtained by X-ray computed tomography in noise due to the use of a small number of projections present noise of different types. In this paper we analyze and evaluate two techniques that separately each behaves efficiently for the removal of Gaussian and impulsive noise respectively, and combined to form a hybrid approach obtains very good performance with respect to quality in most different types of noise.

  17. Multi-frequency harmonic arrays: initial experience with a novel transducer concept for nonlinear contrast imaging.

    Science.gov (United States)

    Forsberg, Flemming; Shi, William T; Jadidian, Bahram; Winder, Alan A

    2004-12-01

    Nonlinear contrast imaging modes such as second harmonic imaging (HI) and subharmonic imaging (SHI) are increasingly important for clinical applications. However, the performance of currently available transducers for HI and SHI is significantly constrained by their limited bandwidth. To bypass this constraint, a novel transducer concept termed multi-frequency harmonic transducer arrays (MFHA's) has been designed and a preliminary evaluation has been conducted. The MFHA may ultimately be used for broadband contrast enhanced HI and SHI with high dynamic range and consists of three multi-element piezo-composite sub-arrays (A-C) constructed so the center frequencies are 4f(A) = 2f(B) = f(C) (specifically 2.5/5.0/10.0 MHz and 1.75/3.5/7.0 MHz). In principle this enables SHI by transmitting on sub-array C receiving on B and, similarly, from B to A as well as HI by transmitting on A receiving on B and, likewise, from B to C. Initially transmit and receive pressure levels of the arrays were measured with the elements of each sub-array wired in parallel. Following contrast administration, preliminary in vitro HI and SHI signal-to-noise ratios of up to 40 dB were obtained. In conclusion, initial design and in vitro characterization of two MFHA's have been performed. They have an overall broad frequency bandwidth of at least two octaves. Due to the special design of the array assembly, the SNR for HI and SHI was comparable to that of regular B-mode and better than commercially available HI systems. However, further research on multi-element MFHA's is required before their potential for in vivo nonlinear contrast imaging can be assessed.

  18. Nonlinear microrheology and molecular imaging to map microscale deformations of entangled DNA networks

    Science.gov (United States)

    Wu, Tsai-Chin; Anderson, Rae

    We use active microrheology coupled to single-molecule fluorescence imaging to elucidate the microscale dynamics of entangled DNA. DNA naturally exists in a wide range of lengths and topologies, and is often confined in cell nucleui, forming highly concentrated and entangled biopolymer networks. Thus, DNA is the model polymer for understanding entangled polymer dynamics as well as the crowded environment of cells. These networks display complex viscoelastic properties that are not well understood, especially at the molecular-level and in response to nonlinear perturbations. Specifically, how microscopic stresses and strains propagate through entangled networks, and what molecular deformations lead to the network stress responses are unknown. To answer these important questions, we optically drive a microsphere through entangled DNA, perturbing the system far from equilibrium, while measuring the resistive force the DNA exerts on the bead during and after bead motion. We simultaneously image single fluorescent-labeled DNA molecules throughout the network to directly link the microscale stress response to molecular deformations. We characterize the deformation of the network from the molecular-level to the mesoscale, and map the stress propagation throughout the network. We further study the impact of DNA length (11 - 115 kbp) and topology (linear vs ring DNA) on deformation and propagation dynamics, exploring key nonlinear features such as tube dilation and power-law relaxation.

  19. Nonlinear temporal filtering of time-resolved digital particle image velocimetry data

    Energy Technology Data Exchange (ETDEWEB)

    Fore, L.B.; Tung, A.T.; Buchanan, J.R.; Welch, J.W. [Bechtel Bettis Inc., West Mifflin, PA (United States)

    2005-07-01

    Nonlinear filtering methods have been developed to identify and replace outlying data points in velocity time series obtained with time-resolved digital particle image velocimetry (PIV) of the flow around a surface-mounted cube at a Reynolds number of 20,000. Nuances associated with the spectral computation of the cross-correlation are highlighted, including the requirement of zero-padding an image interrogation area to eliminate the circular components of the cross-correlation. Three nonlinear filtering methods for the replacement of outliers are applied to the velocity time series sampled at 1,000 Hz: a median filter, a decision-based Hampel filter, and a PIV-specific Hampel filter. The particular benefit of the PIV-specific Hampel filter is that it allows the retention of actual measured data, sometimes derived from alternate peaks in the cross-correlation function, while still providing for the removal of outliers when a consistent, nonoutlying measurement is not available. (orig.)

  20. Frequency selective non-linear blending to improve image quality in liver CT

    Energy Technology Data Exchange (ETDEWEB)

    Bongers, M.N.; Bier, G.; Kloth, C.; Schabel, C.; Nikolaou, K.; Horger, M. [University Hospital of Tuebingen (Germany). Dept. of Diagnostic and Interventional Radiology; Fritz, J. [Johns Hopkins University School of Medicine, Baltimore, MD (United States). Russell H. Morgan Dept. of Radiology and Radiological Science

    2016-12-15

    To evaluate the effects of a new frequency selective non-linear blending (NLB) algorithm on the contrast resolution of liver CT with low intravascular concentration of iodine contrast. Our local ethics committee approved this retrospective study. The informed consent requirement was waived. CT exams of 25 patients (60% female, mean age: 65±16 years of age) with late phase CT scans of the liver were included as a model for poor intrahepatic vascular contrast enhancement. Optimal post-processing settings to enhance the contrast of hepatic vessels were determined. Outcome variables included signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of hepatic vessels and SNR of liver parenchyma of standard and post-processed images. Image quality was quantified by two independent readers using Likert scales. The post-processing settings for the visualization of hepatic vasculature were optimal at a center of 115HU, delta of 25HU, and slope of 5. Image noise was statistically indifferent between standard and post-processed images. The CNR between the hepatic vasculature (HV) and liver parenchyma could be significantly increased for liver veins (CNR{sub Standard} 1.62±1.10, CNR{sub NLB} 3.6±2.94, p=0.0002) and portal veins (CNR{sub Standard} 1.31±0.85, CNR{sub NLB} 2.42±3.03, p=0.046). The SNR of liver parenchyma was significantly higher on post-processed images (SNR{sub NLB} 11.26±3.16, SNR{sub Standard} 8.85± 2.27, p=0.008). The overall image quality and depiction of HV were significantly higher on post-processed images (NLB{sub DHV}: 4 [3-4.75], S{sub tandardDHV}: 2 [1.3-2.5], p=<0.0001; {sub NLBIQ}: 4 [4-4], {sub StandardIQ}: 2 [2-3], p=<0.0001). The use of a frequency selective non-linear blending algorithm increases the contrast resolution of liver CT and can improve the visibility of the hepatic vasculature in the setting of a low contrast ratio between vessels and the parenchyma.

  1. Iterative Lavrentiev regularization for symmetric kernel-driven operator equations: with application to digital image restoration problems

    Institute of Scientific and Technical Information of China (English)

    WANG Yanfei; GU Xingfa; YU Tao; FAN Shufang

    2005-01-01

    The symmetric kernel-driven operator equations play an important role in mathematical physics, engineering, atmospheric image processing and remote sensing sciences. Such problems are usually ill-posed in the sense that even if a unique solution exists, the solution need not depend continuously on the input data. One common technique to overcome the difficulty is applying the Tikhonov regularization to the symmetric kernel operator equations, which is more generally called the Lavrentiev regularization.It has been shown that the iterative implementation of the Tikhonov regularization can improve the rate of convergence. Therefore in this paper, we study the iterative Lavrentiev regularization method in a similar way when applying it to symmetric kernel problems which appears frequently in applications, say digital image restoration problems. We first prove the convergence property, and then under the widely used Morozov discrepancy principle(MDP), we prove the regularity of the method. Numerical performance for digital image restoration is included to confirm the theory. It seems that the iterated Lavrentiev regularization with the MDP strategy is appropriate for solving symmetric kernel problems.

  2. Nonlinear photoacoustic microscopy via a loss modulation technique: from detection to imaging.

    Science.gov (United States)

    Lai, Yu-Hung; Lee, Szu-Yu; Chang, Chieh-Feng; Cheng, Yu-Hsiang; Sun, Chi-Kuang

    2014-01-13

    In order to achieve high-resolution deep-tissue imaging, multi-photon fluorescence microscopy and photoacoustic tomography had been proposed in the past two decades. However, combining the advantages of these two imaging systems to achieve optical-spatial resolution with an ultrasonic-penetration depth is still a field with challenges. In this paper, we investigate the detection of the two-photon photoacoustic ultrasound, and first demonstrate background-free two-photon photoacoustic imaging in a phantom sample. To generate the background-free two-photon photoacoustic signals, we used a high-repetition rate femtosecond laser to induce narrowband excitation. Combining a loss modulation technique, we successfully created a beating on the light intensity, which not only provides pure sinusoidal modulation, but also ensures the spectrum sensitivity and frequency selectivity. By using the lock-in detection, the power dependency experiment validates our methodology to frequency-select the source of the nonlinearity. This ensures our capability of measuring the background-free two-photon photoacoustic waves by detecting the 2nd order beating signal directly. Furthermore, by mixing the nanoparticles and fluorescence dyes as contrast agents, the two-photon photoacoustic signal was found to be enhanced and detected. In the end, we demonstrate subsurface two-photon photoacoustic bio-imaging based on the optical scanning mechanism inside phantom samples.

  3. Reorganization characteristics of speech cortex during speech restoration following total laryngectomy A functional magnetic resonance imaging follow-up

    Institute of Scientific and Technical Information of China (English)

    Jianzhong Yin; Yonggang Xue; Peng Lin; Xuchu Weng; Ji Qi

    2011-01-01

    During speech restoration following laryngectomy, language-related cortical areas develop connections with new primary motor neurons. The present study followed up 18 patients after total resection of laryngeal carcinoma. According to an evaluation of pronunciation, patients were assigned to three groups: poor, moderate and good pronunciation. Functional magnetic resonance imaging revealed significant increases in the number of activated voxels and the intensity of activation changes in the left middle frontal gyrus, left precentral gyrus, left postcentral gyrus, left supplementary motor area, left anterior cingulate gyrus and right fusiform gyrus between the moderate pronunciation group compared with the poor and good pronunciation groups. We propose that these brain regions play an important role in the progress of speech restoration, and improvements in pronunciation learning for patients following laryngectomy. However, during the later period of speech restoration, the number of activated voxels and intensity changes in these regions decreased to the level of healthy controls, indicating that the learning and instruction effects weakened once patients had mastered pronunciation techniques.

  4. A compact microscope setup for multimodal nonlinear imaging in clinics and its application to disease diagnostics.

    Science.gov (United States)

    Meyer, Tobias; Baumgartl, Martin; Gottschall, Thomas; Pascher, Torbjörn; Wuttig, Andreas; Matthäus, Christian; Romeike, Bernd F M; Brehm, Bernhard R; Limpert, Jens; Tünnermann, Andreas; Guntinas-Lichius, Orlando; Dietzek, Benjamin; Schmitt, Michael; Popp, Jürgen

    2013-07-21

    The past years have seen increasing interest in nonlinear optical microscopic imaging approaches for the investigation of diseases due to the method's unique capabilities of deep tissue penetration, 3D sectioning and molecular contrast. Its application in clinical routine diagnostics, however, is hampered by large and costly equipment requiring trained staff and regular maintenance, hence it has not yet matured to a reliable tool for application in clinics. In this contribution implementing a novel compact fiber laser system into a tailored designed laser scanning microscope results in a small footprint easy to use multimodal imaging platform enabling simultaneously highly efficient generation and acquisition of second harmonic generation (SHG), two-photon excited fluorescence (TPEF) as well as coherent anti-Stokes Raman scattering (CARS) signals with optimized CARS contrast for lipid imaging for label-free investigation of tissue samples. The instrument combining a laser source and a microscope features a unique combination of the highest NIR transmission and a fourfold enlarged field of view suited for investigating large tissue specimens. Despite its small size and turnkey operation rendering daily alignment dispensable the system provides the highest flexibility, an imaging speed of 1 megapixel per second and diffraction limited spatial resolution. This is illustrated by imaging samples of squamous cell carcinoma of the head and neck (HNSCC) and an animal model of atherosclerosis allowing for a complete characterization of the tissue composition and morphology, i.e. the tissue's morphochemistry. Highly valuable information for clinical diagnostics, e.g. monitoring the disease progression at the cellular level with molecular specificity, can be retrieved. Future combination with microscopic probes for in vivo imaging or even implementation in endoscopes will allow for in vivo grading of HNSCC and characterization of plaque deposits towards the detection of high

  5. Satellite Image-based Estimates of Snow Water Equivalence in Restored Ponderosa Pine Forests in Northern Arizona

    Science.gov (United States)

    Sankey, T.; Springer, A. E.; O'Donnell, F. C.; Donald, J.; McVay, J.; Masek Lopez, S.

    2014-12-01

    The U.S. Forest Service plans to conduct forest restoration treatments through the Four Forest Restoration Initiative (4FRI) on hundreds of thousands of acres of ponderosa pine forest in northern Arizona over the next 20 years with the goals of reducing wildfire hazard and improving forest health. The 4FRI's key objective is to thin and burn the forests to create within-stand openings that "promote snowpack accumulation and retention which benefit groundwater recharge and watershed processes at the fine (1 to 10 acres) scale". However, little is known about how these openings created by restoration treatments affect snow water equivalence (SWE) and soil moisture, which are key parts of the water balance that greatly influence water availability for healthy trees and for downstream water users in the Sonoran Desert. We have examined forest canopy cover by calculating a Normalized Difference Vegetation Index (NDVI), a key indicator of green vegetation cover, using Landsat satellite data. We have then compared NDVI between treatments at our study sites in northern Arizona and have found statistically significant differences in tree canopy cover between treatments. The control units have significantly greater forest canopy cover than the treated units. The thinned units also have significantly greater tree canopy cover than the thin-and-burn units. Winter season Landsat images have also been analyzed to calculate Normalized Difference Snow Index (NDSI), a key indicator of snow water equivalence and snow accumulation at the treated and untreated forests. The NDSI values from these dates are examined to determine if snow accumulation and snow water equivalence vary between treatments at our study sites. NDSI is significantly greater at the treated units than the control units. In particular, the thinned forest units have significantly greater snow cover than the control units. Our results indicate that forest restoration treatments result in increased snow pack

  6. Spatio-temporal features of vegetation restoration and variation after the Wenchuan earthquake with satellite images

    Science.gov (United States)

    Peng, Hou; Qiao, Wang; Yipeng, Yang; Weiguo, Jiang; Bingfeng, Yang; Qiang, Chen; Lihua, Yuan; Fanming, Kong; Xi, Chen; Guanjie, Wang

    2014-01-01

    The Wenchuan earthquake was a deadly earthquake that occurred on May 12, 2008, in Sichuan province of China. With the help of classic statistic methods, including arithmetic mean, standard deviation and linear trend estimation, vegetation restoration was recognized by analyzing spatio-temporal features of normalized difference vegetation index (NDVI) before and after this earthquake. Results indicate: (1) spatial distribution of NDVI mean values remains similar from 1998 to 2011. Higher values are mainly found in north, whereas lower values are mainly distributed over southeast, which is in good correlation with elevation and landform. Vegetation damage is at different levels in different seismic intensity (SI) regions: the higher SI is, the worse vegetation damage is. (2) Over the whole region, standard deviation is bigger after earthquake than before. Both absolute and relative changes in ecosystem stability increase with increasing SI. In different counties, variation of ecosystem stability is more obvious after earthquake, increase of standard deviation is approximately 6.5 times. Relatively, vegetation regionalization is the smallest analysis unit. Consequently, changes resulting from earthquake are unobvious. (3) Linear trend estimation coefficient increases from 0.0079 before the earthquake to 0.0359 after the earthquake in this whole region. This indicates that the plant ecosystem is rapidly restored between 2009 and 2011. The biggest linear trend is for the hill region, indicating good plant restoration and increase after earthquake. Fluctuation of linear trend estimation coefficient in different counties is more obvious after earthquake. Vegetation restoration after earthquake is most obvious in the regions that suffered the greatest SI (SI10 and SI11). In contrast, fluctuation in linear trend estimation coefficient of annual NDVI mean value for different classes of vegetation is more obvious before earthquake.

  7. Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system

    Science.gov (United States)

    Tao, S.; Trzasko, J. D.; Gunter, J. L.; Weavers, P. T.; Shu, Y.; Huston, J., III; Lee, S. K.; Tan, E. T.; Bernstein, M. A.

    2017-01-01

    Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resonance imaging cannot be perfectly linear and always contain higher-order, nonlinear components. If ignored during image reconstruction, gradient nonlinearity (GNL) manifests as image geometric distortion. Given an estimate of the GNL field, this distortion can be corrected to a degree proportional to the accuracy of the field estimate. The GNL of a gradient system is typically characterized using a spherical harmonic polynomial model with model coefficients obtained from electromagnetic simulation. Conventional whole-body gradient systems are symmetric in design; typically, only odd-order terms up to the 5th-order are required for GNL modeling. Recently, a high-performance, asymmetric gradient system was developed, which exhibits more complex GNL that requires higher-order terms including both odd- and even-orders for accurate modeling. This work characterizes the GNL of this system using an iterative calibration method and a fiducial phantom used in ADNI (Alzheimer’s Disease Neuroimaging Initiative). The phantom was scanned at different locations inside the 26 cm diameter-spherical-volume of this gradient, and the positions of fiducials in the phantom were estimated. An iterative calibration procedure was utilized to identify the model coefficients that minimize the mean-squared-error between the true fiducial positions and the positions estimated from images corrected using these coefficients. To examine the effect of higher-order and even-order terms, this calibration was performed using spherical harmonic polynomial of different orders up to the 10th-order including even- and odd-order terms, or odd-order only. The results showed that the model coefficients of this gradient can be successfully estimated. The residual root-mean-squared-error after correction using up to the 10th-order coefficients was reduced to 0.36 mm, yielding spatial accuracy comparable to

  8. Robust Nonlinear Regression: A Greedy Approach Employing Kernels With Application to Image Denoising

    Science.gov (United States)

    Papageorgiou, George; Bouboulis, Pantelis; Theodoridis, Sergios

    2017-08-01

    We consider the task of robust non-linear regression in the presence of both inlier noise and outliers. Assuming that the unknown non-linear function belongs to a Reproducing Kernel Hilbert Space (RKHS), our goal is to estimate the set of the associated unknown parameters. Due to the presence of outliers, common techniques such as the Kernel Ridge Regression (KRR) or the Support Vector Regression (SVR) turn out to be inadequate. Instead, we employ sparse modeling arguments to explicitly model and estimate the outliers, adopting a greedy approach. The proposed robust scheme, i.e., Kernel Greedy Algorithm for Robust Denoising (KGARD), is inspired by the classical Orthogonal Matching Pursuit (OMP) algorithm. Specifically, the proposed method alternates between a KRR task and an OMP-like selection step. Theoretical results concerning the identification of the outliers are provided. Moreover, KGARD is compared against other cutting edge methods, where its performance is evaluated via a set of experiments with various types of noise. Finally, the proposed robust estimation framework is applied to the task of image denoising, and its enhanced performance in the presence of outliers is demonstrated.

  9. TU-CD-BRA-12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

    Energy Technology Data Exchange (ETDEWEB)

    Li, L; Tan, S [Huazhong University of Science and Technology, Wuhan, Hubei (China); Lu, W [University of Maryland School of Medicine, Baltimore, MD (United States)

    2015-06-15

    Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was used on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural

  10. The optimal code searching method with an improved criterion of coded exposure for remote sensing image restoration

    Science.gov (United States)

    He, Lirong; Cui, Guangmang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

    2015-03-01

    Coded exposure photography makes the motion de-blurring a well-posed problem. The integration pattern of light is modulated using the method of coded exposure by opening and closing the shutter within the exposure time, changing the traditional shutter frequency spectrum into a wider frequency band in order to preserve more image information in frequency domain. The searching method of optimal code is significant for coded exposure. In this paper, an improved criterion of the optimal code searching is proposed by analyzing relationship between code length and the number of ones in the code, considering the noise effect on code selection with the affine noise model. Then the optimal code is obtained utilizing the method of genetic searching algorithm based on the proposed selection criterion. Experimental results show that the time consuming of searching optimal code decreases with the presented method. The restoration image is obtained with better subjective experience and superior objective evaluation values.

  11. In search for the original image: Luciano Freire and the theory and practice of painting restoration in Portugal circa 1900

    Directory of Open Access Journals (Sweden)

    António João Cruz

    2007-01-01

    Full Text Available From the fragmentary statements found in several texts, especially from a report written in the 1930's that presents memoir notes, this paper intends to reconstitute, as much as possible, the restoration theory and practice of Luciano Freire (1864-1934. He treated many of the most important paintings belonging to Portuguese museums and, according to his words, those interventions were justified, above all, by the damages caused by past restorers, through repaints, which was frequent, or through cleaning, which originated the worst problems, and by the damages caused by the ambient conditions surrounding the paintings. In general, the interventions aimed at recovering the original image. Although Luciano Freire was, in theory, an adept of the complete cleaning of dirt and varnishes and complete removal of retouches and repaints, as it was done in National Gallery, London, in practice he admitted that when the retouches and repaints were well done and in good condition they were not to be removed. He considered that losses should be reintegrated and his thoughts were divided by the recovering the original image and the respect for the original work. He usually ended up considering that mimetic retouching could only be done when enough clues were present. Therefore, retouching had limits that, however, he recognizes, he crossed at times. Although did not use radiographs, he attributed great importance to treatment documentation through photography or other means.

  12. Nonlinear Optical Imaging to Evaluate the Impact of Obesity on Mammary Gland and Tumor Stroma

    Directory of Open Access Journals (Sweden)

    Thuc T. Le

    2007-05-01

    Full Text Available Obesity is an established risk factor for breast cancer incidence and mortality. However, the mechanism that links obesity to tumorigenesis is not well understood. Here we combined nonlinear optical imaging technologies with an early-onset diet-induced obesity breast cancer animal model to evaluate the impact of obesity on the composition of mammary gland and tumor stroma. Using coherent anti-Stokes Raman scattering and second harmonic generation on the same platform, we simultaneously imaged mammary adipocytes, blood capillaries, collagen fibrils, and tumor cells without any labeling. We observed that obesity increases the size of lipid droplets of adipocytes in mammary gland and collagen content in mammary tumor stroma, respectively. Such impacts of obesity on mammary gland and tumor stroma could not be analyzed using standard two-dimensional histologic evaluation. Given the importance of mammary stroma to the growth and migration of tumor cells, our observation provides the first imaging evidence that supports the relationship between obesity and breast cancer risk.

  13. Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

    Science.gov (United States)

    Tuia, Devis; Marcos, Diego; Camps-Valls, Gustau

    2016-10-01

    Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corresponding band to be matched between the images. An alternative builds upon manifold alignment. Manifold alignment performs a multidimensional relative normalization of the data prior to product generation that can cope with data of different dimensionality (e.g. different number of bands) and possibly unpaired examples. Aligning data distributions is an appealing strategy, since it allows to provide data spaces that are more similar to each other, regardless of the subsequent use of the transformed data. In this paper, we study a methodology that aligns data from different domains in a nonlinear way through kernelization. We introduce the Kernel Manifold Alignment (KEMA) method, which provides a flexible and discriminative projection map, exploits only a few labeled samples (or semantic ties) in each domain, and reduces to solving a generalized eigenvalue problem. We successfully test KEMA in multi-temporal and multi-source very high resolution classification tasks, as well as on the task of making a model invariant to shadowing for hyperspectral imaging.

  14. Nonlinear optical techniques for imaging and manipulating the mouse central nervous system

    Science.gov (United States)

    Farrar, Matthew John

    The spinal cord of vertebrates serves as the conduit for somatosensory information and motor control, as well as being the locus of neural circuits that govern fast reflexes and patterned behaviors, such as walking in mammals or swimming in fish. Consequently, pathologies of the spinal cord -such as spinal cord injury (SCI)- lead to loss of motor control and sensory perception, with accompanying decline in life expectancy and quality of life. Despite the devastating effects of these diseases, few therapies exist to substantially ameliorate patient outcome. In part, studies of spinal cord pathology have been limited by the inability to perform in vivo imaging at the level of cellular processes. The focus of this thesis is to present the underlying theory for and demonstration of novel multi-photon microscopy (MPM) and optical manipulation techniques as they apply to studies the mouse central nervous system (CNS), with an emphasis on the spinal cord. The scientific findings which have resulted from the implementation of these techniques are also presented. In particular, we have demonstrated that third harmonic generation is a dye-free method of imaging CNS myelin, a fundamental constituent of the spinal cord that is difficult to label using exogenous dyes and/or transgenic constructs. Since gaining optical access to the spinal cord is a prerequisite for spinal cord imaging, we review our development of a novel spinal cord imaging chamber and surgical procedure which allowed us to image for multiple weeks following implantation without the need for repeated surgeries. We also have used MPM to characterize spinal venous blood flow before and after point occlusions. We review a novel nonlinear microscopy technique that may serve to show optical interfaces in three dimensions inside scattering tissue. Finally, we discuss a model and show results of optoporation, a means of transfecting cells with genetic constructs. Brief reviews of MPM and SCI are also presented.

  15. Nonlinear contrast enhancement in photoacoustic molecular imaging with gold nanosphere encapsulated nanoemulsions

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Chen-wei; Lombardo, Michael; Larson-Smith, Kjersta; Perez, Camilo; Xia, Jinjun; Matula, Thomas; Pozzo, Danilo; O' Donnell, Matthew [Departments of Bioengineering and Chemical Engineering, and Applied Physics Lab, University of Washington, Seattle, Washington 98195 (United States); Pelivanov, Ivan [Departments of Bioengineering and Chemical Engineering, and Applied Physics Lab, University of Washington, Seattle, Washington 98195 (United States); International Laser Center, Moscow State University, Moscow (Russian Federation)

    2014-01-20

    A composite contrast agent, a nanoemulsion bead with assembled gold nanospheres at the interface, is proposed to improve the specific contrast of photoacoustic molecular imaging. A phase transition in the bead's core is induced by absorption of a nanosecond laser pulse with a fairly low laser fluence (∼3.5 mJ/cm{sup 2}), creating a transient microbubble through dramatically enhanced thermal expansion. This generates nonlinear photoacoustic signals with more than 10 times larger amplitude compared to that of a linear agent with the same optical absorption. By applying a differential scheme similar to ultrasound pulse inversion, more than 40 dB contrast enhancement is demonstrated with suppression of background signals.

  16. SOM-based nonlinear least squares twin SVM via active contours for noisy image segmentation

    Science.gov (United States)

    Xie, Xiaomin; Wang, Tingting

    2017-02-01

    In this paper, a nonlinear least square twin support vector machine (NLSTSVM) with the integration of active contour model (ACM) is proposed for noisy image segmentation. Efforts have been made to seek the kernel-generated surfaces instead of hyper-planes for the pixels belonging to the foreground and background, respectively, using the kernel trick to enhance the performance. The concurrent self organizing maps (SOMs) are applied to approximate the intensity distributions in a supervised way, so as to establish the original training sets for the NLSTSVM. Further, the two sets are updated by adding the global region average intensities at each iteration. Moreover, a local variable regional term rather than edge stop function is adopted in the energy function to ameliorate the noise robustness. Experiment results demonstrate that our model holds the higher segmentation accuracy and more noise robustness.

  17. Sparse nonlinear inverse imaging for shot count reduction in inverse lithography.

    Science.gov (United States)

    Wu, Xiaofei; Liu, Shiyuan; Lv, Wen; Lam, Edmund Y

    2015-10-19

    Inverse lithography technique (ILT) is significant to reduce the feature size of ArF optical lithography due to its strong ability to overcome the optical proximity effect. A critical issue for inverse lithography is the complex curvilinear patterns produced, which are very costly to write due to the large number of shots needed with the current variable shape beam (VSB) writers. In this paper, we devise an inverse lithography method to reduce the shot count by incorporating a model-based fracturing (MBF) in the optimization. The MBF is formulated as a sparse nonlinear inverse imaging problem based on representing the mask as a linear combination of shots followed by a threshold function. The problem is approached with a Gauss-Newton algorithm, which is adapted to promote sparsity of the solution, corresponding to the reduction of the shot count. Simulations of inverse lithography are performed on several test cases, and results demonstrate reduced shot count of the resulting mask.

  18. A non-linear preprocessing for opto-digital image encryption using multiple-parameter discrete fractional Fourier transform

    Science.gov (United States)

    Azoug, Seif Eddine; Bouguezel, Saad

    2016-01-01

    In this paper, a novel opto-digital image encryption technique is proposed by introducing a new non-linear preprocessing and using the multiple-parameter discrete fractional Fourier transform (MPDFrFT). The non-linear preprocessing is performed digitally on the input image in the spatial domain using a piecewise linear chaotic map (PLCM) coupled with the bitwise exclusive OR (XOR). The resulting image is multiplied by a random phase mask before applying the MPDFrFT to whiten the image. Then, a chaotic permutation is performed on the output of the MPDFrFT using another PLCM different from the one used in the spatial domain. Finally, another MPDFrFT is applied to obtain the encrypted image. The parameters of the PLCMs together with the multiple fractional orders of the MPDFrFTs constitute the secret key for the proposed cryptosystem. Computer simulation results and security analysis are presented to show the robustness of the proposed opto-digital image encryption technique and the great importance of the new non-linear preprocessing introduced to enhance the security of the cryptosystem and overcome the problem of linearity encountered in the existing permutation-based opto-digital image encryption schemes.

  19. Non-linear imaging techniques visualize the lipid profile of C. elegans

    Science.gov (United States)

    Mari, Meropi; Petanidou, Barbara; Palikaras, Konstantinos; Fotakis, Costas; Tavernarakis, Nektarios; Filippidis, George

    2015-07-01

    The non-linear techniques Second and Third Harmonic Generation (SHG, THG) have been employed simultaneously to record three dimensional (3D) imaging and localize the lipid content of the muscular areas (ectopic fat) of Caenorhabditis elegans (C. elegans). Simultaneously, Two-Photon Fluorescence (TPEF) was used initially to localize the stained lipids with Nile Red, but also to confirm the THG potential to image lipids successfully. In addition, GFP labelling of the somatic muscles, proves the initial suggestion of the existence of ectopic fat on the muscles and provides complementary information to the SHG imaging of the pharynx. The ectopic fat may be related to a complex of pathological conditions including type-2 diabetes, hypertension and cardiovascular diseases. The elucidation of the molecular path leading to the development of metabolic syndrome is a vital issue with high biological significance and necessitates accurate methods competent of monitoring lipid storage distribution and dynamics in vivo. THG microscopy was employed as a quantitative tool to monitor the lipid accumulation in non-adipose tissues in the pharyngeal muscles of 12 unstained specimens while the SHG imaging revealed the anatomical structure of the muscles. The ectopic fat accumulation on the pharyngeal muscles increases in wild type (N2) C. elegans between 1 and 9 days of adulthood. This suggests a correlation of the ectopic fat accumulation with the aging. Our results can provide new evidence relating the deposition of ectopic fat with aging, but also validate SHG and THG microscopy modalities as new, non-invasive tools capable of localizing and quantifying selectively lipid accumulation and distribution.

  20. Research on the Image Restoration of Fog and Haze%雾霾图像复原技术研究

    Institute of Scientific and Technical Information of China (English)

    陈阳; 李浩; 禹凤

    2015-01-01

    The phenomenon of haze causes low visibility, image blurring and color fading, thereby affecting subsequent processing of the image. By using dark channel prior and guided filtering, the haze recovery process to enhance the visibility of a series of images is successful. On the basis of the successful implementation of haze image restoration, deals with haze video by using time-domain information. Using time line information and dark channel prior method can effectively improve the efficiency of haze video processing and enhance the unity of fog and haze recovery video.%雾霾造成视野的限制,使图像模糊以及色彩淡化,进而影响图像的后续处理。利用暗通道先验和导向滤波方法能有效地进行雾霾图像复原,增强其可视性。在处理雾霾图像复原的基础上,对雾霾视频进行雾霾复原处理,利用时间轴信息的暗通道先验方法能有效提高雾霾视频处理的效率及增强处理后的雾霾复原视频的色调统一性。

  1. A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

    Science.gov (United States)

    Karimi, Davood; Ward, Rabab K.

    2016-03-01

    Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

  2. Assessing the quality of restored images in optical long-baseline interferometry

    CERN Document Server

    Gomes, Nuno; Thiébaut, Éric

    2016-01-01

    Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics, and selecting a few based on general properties. Then, a variety of image reconstruction cases is considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MiRA software, and several merit functions are put to test. It is found that convolution by an effect...

  3. Latest Methods of Image Enhancement and Restoration for Computed Tomography: A Concise Review

    Directory of Open Access Journals (Sweden)

    Zohair AL-AMEEN

    2015-03-01

    Full Text Available It is known that computed tomography (CT images are corrupted by many degradations including: blurring, low contrast or noise due to different real-world limitations. Thus, it is necessary to filter these images before starting the diagnostic process. In recent years, extensive research has been carried out to reduce such undesirable degradations, in which substantial achievements have been attained from skillful researchers by providing various innovative methods. Such methods contributed significantly in improving the poor visual quality of CT images. In this article, a review about six contemporary methods for each of image enhancement, denoising and deblurring is provided due to the high-profile of CT images in the medical field. Hence, after the prevalent causes of the degradations are highlighted, adequate elucidations about the literature methods are delivered. Finally, an inclusive summary is provided.

  4. Imaging nanomaterials in vitro and in vivo by exploring their intrinsic nonlinear optical signals

    Science.gov (United States)

    Tong, Ling

    The extension of nanotechnology to biomedical system creates a new and fast developing field, nanomedicine. A wide range of nanoparticles has been developed as imaging agents or drug carriers. However, the translation of nanomedicines to a clinical setting has been slowed down due to a limited fundamental understanding of the nano-bio interaction. My thesis work describes the efforts in imaging the behavior of nanomaterials in live cells and animals by exploring the nonlinear optical properties. The first part of my thesis focuses on study of metallic and semiconducting nanoparticles in biological environment using their nonlinear optical signals. In chapter 2, systemic circulation of PEGylated gold nanorods (GNRs) is visualized by intravital two-photon luminescence (TPL) imaging. A biphasic clearance is demonstrated with branched PEG showing longer circulation. Following clearance, cellular biodistribution of GNRs in organs is mapped by TPL imaging. GNRs accumulate in macrophages in liver and spleen (Langmuir, 2009, 25, 12454-12459). In chapter 3, a bright three-photon luminescence is discovered from Au-Ag alloyed nanostructure by excitation with a femtosecond laser at 1290 nm, which enables bio-imaging with negligible photothermal toxicity and tissue autofluorescence (Angew Chemie, 2010, 49, 3485-3488, inside cover story). In chapter 4, a new contrast is invented for label-free, real-time imaging of single-walled carbon nanotubes (SWNTs) by pump-probe microscopy. At pump/probe wavelength of 707 and 885 nm, semiconducting and metallic SWNTs (S-SWNTs and M-SWNTs) exhibit intense stimulated emission and absorption signals, which allow us to monitor the intracellular trafficking, distribution in tissues, and systemic circulation in vivo with single-nanotube sensitivity and sub-micron resolution. The second part presents label-free imaging of nanomedicines in live cells by coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS) microscopy

  5. Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images

    CERN Document Server

    Yothers, Mitchell P; Bumm, Lloyd A

    2016-01-01

    We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly-resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors (NNs) are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform (DHCT). Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional re...

  6. Imaging of normal and pathologic joint synovium using nonlinear optical microscopy as a potential diagnostic tool

    Science.gov (United States)

    Tiwari, Nivedan; Chabra, Sanjay; Mehdi, Sheherbano; Sweet, Paula; Krasieva, Tatiana B.; Pool, Roy; Andrews, Brian; Peavy, George M.

    2010-09-01

    An estimated 1.3 million people in the United States suffer from rheumatoid arthritis (RA). RA causes profound changes in the synovial membrane of joints, and without early diagnosis and intervention, progresses to permanent alterations in joint structure and function. The purpose of this study is to determine if nonlinear optical microscopy (NLOM) can utilize the natural intrinsic fluorescence properties of tissue to generate images that would allow visualization of the structural and cellular composition of fresh, unfixed normal and pathologic synovial tissue. NLOM is performed on rabbit knee joint synovial samples using 730- and 800-nm excitation wavelengths. Less than 30 mW of excitation power delivered with a 40×, 0.8-NA water immersion objective is sufficient for the visualization of synovial structures to a maximum depth of 70 μm without tissue damage. NLOM imaging of normal and pathologic synovial tissue reveals the cellular structure, synoviocytes, adipocytes, collagen, vascular structures, and differential characteristics of inflammatory infiltrates without requiring tissue processing or staining. Further study to evaluate the ability of NLOM to assess the characteristics of pathologic synovial tissue and its potential role for the management of disease is warranted.

  7. Nonlinear optical imaging and Raman microspectrometry of the cell nucleus throughout the cell cycle.

    Science.gov (United States)

    Pliss, Artem; Kuzmin, Andrey N; Kachynski, Aliaksandr V; Prasad, Paras N

    2010-11-17

    Fundamental understanding of cellular processes at molecular level is of considerable importance in cell biology as well as in biomedical disciplines for early diagnosis of infection and cancer diseases, and for developing new molecular medicine-based therapies. Modern biophotonics offers exclusive capabilities to obtain information on molecular composition, organization, and dynamics in a cell by utilizing a combination of optical spectroscopy and optical imaging. We introduce here a combination of Raman microspectrometry, together with coherent anti-Stokes Raman scattering (CARS) and two-photon excited fluorescence (TPEF) nonlinear optical microscopy, to study macromolecular organization of the nucleus throughout the cell cycle. Site-specific concentrations of proteins, DNA, RNA, and lipids were determined in nucleoli, nucleoplasmic transcription sites, nuclear speckles, constitutive heterochromatin domains, mitotic chromosomes, and extrachromosomal regions of mitotic cells by quantitative confocal Raman microspectrometry. A surprising finding, obtained in our study, is that the local concentration of proteins does not increase during DNA compaction. We also demonstrate that postmitotic DNA decondensation is a gradual process, continuing for several hours. The quantitative Raman spectroscopic analysis was corroborated with CARS/TPEF multimodal imaging to visualize the distribution of protein, DNA, RNA, and lipid macromolecules throughout the cell cycle.

  8. Imaging ectopic fat deposition in Caenorhabditis elegans muscles using nonlinear microscopy.

    Science.gov (United States)

    Mari, Meropi; Filippidis, George; Palikaras, Konstantinos; Petanidou, Barbara; Fotakis, Costas; Tavernarakis, Nektarios

    2015-06-01

    The elucidation of the molecular mechanisms that lead to the development of metabolic syndrome, a complex of pathological conditions including type-2 diabetes, hypertension, and cardiovascular diseases, is an important issue with high biological significance and requires accurate methods capable of monitoring lipid storage distribution and dynamics in vivo. In this study, the nonlinear phenomena of second and third harmonic generation (SHG, THG) have been employed simultaneously as label-free, nondestructive diagnostic techniques, for the monitoring and the complementary three-dimensional (3D) imaging and analysis of the muscular areas and the lipid content localization. THG microscopy was used as a quantitative tool in order to record the accumulation of lipids in nonadipose tissues in the pharyngeal muscles of 18 Caenorhabditis elegans (C. elegans) specimens, while the SHG imaging provided the detailed anatomical information about the structure of the muscles. The ectopic accumulation of fat on the pharyngeal muscles increases in wild-type (N2) C. elegans between 1 and 9 days of adulthood. This suggests a correlation of ectopic fat accumulation with the process of aging. Our results can contribute to the unraveling of the link between the deposition of ectopic fat and aging, but mainly to the validation of SHG and THG microscopy modalities as new, noninvasive tools to localize and quantify selectively lipid formation and distribution.

  9. A Kernel—based Nonlinear Subspace Projection Method for Dimensionality Reduction of Hyperspectral Image Data

    Institute of Scientific and Technical Information of China (English)

    GUYanfeng; ZHANGYe; QUANTaifan

    2003-01-01

    A challenging problem in using hyper-spectral data is to eliminate redundancy and preserve useful spectral information for applications. In this pa-per, a kernel-based nonlinear subspace projection (KNSP)method is proposed for feature extraction and dimension-ality reduction in hyperspectral images. The proposed method includes three key steps: subspace partition of hyperspectral data, feature extraction using kernel-based principal component analysis (KPCA) and feature selec-tion based on class separability in the subspaces. Accord-ing to the strong correlation between neighboring bands,the whole data space is partitioned to requested subspaces.In each subspace, the KPCA method is used to effectively extract spectral feature and eliminate redundancies. A criterion function based on class discrimination and sepa-rability is used for the transformed feature selection. For the purpose of testifying its effectiveness, the proposed new method is compared with the classical principal component analysis (PCA) and segmented principal component trans-formation (SPCT). A hyperspectral image classification is performed on AVIRIS data. which have 224 svectral bands.Experimental results show that KNSP is very effective for feature extraction and dimensionality reduction of hyper-spectral data and provides significant improvement over classical PCA and current SPCT technique.

  10. Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

    Science.gov (United States)

    Baseler, Heidi A; Young, Andrew W; Jenkins, Rob; Mike Burton, A; Andrews, Timothy J

    2016-12-01

    Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

    Science.gov (United States)

    Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

    2013-01-01

    This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

  12. Study of a new method for three-dimensional restoration from single image

    Institute of Scientific and Technical Information of China (English)

    XIE Ming-hong

    2009-01-01

    The aim of three-dimensional recovery technology from the image is to recover the relative height of each point on the surface from the light variations in the single image and carry out the recovery. A new method that recovers three-dimensional is presented object based on radius basis function for the image from the unknown light source direction, which constructs a surface equation by the network, uses the reflectivity function as a constraint, continuonsly estimates the light source direction in the self-learning process of the network from the bright spots around the spread of the image, and eventually obtains a satisfactory surface equation. This method makes the resumption of surface good continuity and smoothness, and can recover the height value of each network point of the image and be automatically inserted in any point the among the network. It is suitable for the image of Lambert reflection model and the image of the Specular reflection model and the mixed-reflex model.

  13. Assessing the quality of restored images in optical long-baseline interferometry

    Science.gov (United States)

    Gomes, Nuno; Garcia, Paulo J. V.; Thiébaut, Éric

    2017-03-01

    Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics and selecting a few based on general properties. Then, a variety of image reconstruction cases are considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MIRA software, and several merit functions are put to test. It is found that convolution by an effective point spread function is required for proper image quality assessment. The effective angular resolution of the images is superior to naive expectation based on the maximum frequency sampled by the array. This is due to the prior information used in the aperture synthesis algorithm and to the nature of the objects considered. The ℓ1-norm is the most robust of all considered metrics, because being linear it is less sensitive to image smoothing by high regularization levels. For the cases considered, this metric allows the implementation of automatic quality assessment of reconstructed images, with a performance similar to human selection.

  14. Parallel ProXimal Algorithm for Image Restoration Using Hybrid Regularization

    CERN Document Server

    Pustelnik, Nelly; Pesquet, Jean-Christophe

    2009-01-01

    Regularization approaches have demonstrated their effectiveness for solving ill-posed problems. However, in the context of variational restoration methods, a challenging question remains, which is how to find a good regularizer. While total variation introduces staircase effects, wavelet domain regularization brings other artefacts, e.g. ringing. However, a compromise can be found by introducing a hybrid regularization including several terms non necessarily acting in the same domain (e.g. spatial and wavelet transform domains). We adopt a convex optimization framework where the criterion to be minimized is split in the sum of more than two terms. For spatial domain regularization, isotropic or anisotropic total variation definitions using various gradient filters are considered. An accelerated version of the Parallel ProXimal Algorithm is proposed to perform the minimization. Some difficulties in the computation of the proximity operators involved in this algorithm are also addressed in this paper. Numerical...

  15. Brain Phosphorus Magnetic Resonance Spectroscopy Imaging of Sleep Homeostasis and Restoration in Drug Dependence

    Directory of Open Access Journals (Sweden)

    George H. Trksak

    2007-01-01

    Full Text Available Numerous reports have documented a high occurrence of sleep difficulties in drug-dependent populations, prompting researchers to characterize sleep profiles and physiology in drug abusing populations. This mini-review examines studies indicating that drug-dependent populations exhibit alterations in sleep homeostatic and restoration processes in response to sleep deprivation. Sleep deprivation is a principal sleep research tool that results in marked physiological challenge, which provides a means to examine sleep homeostatic processes in response to extended wakefulness. A report from our laboratory demonstrated that following recovery sleep from sleep deprivation, brain high-energy phosphates particularly beta–nucleoside triphosphate (beta-NTP are markedly increased as measured with phosphorus magnetic resonance spectroscopy (MRS. A more recent study examined the effects of sleep deprivation in opiate-dependent methadone-maintained (MM subjects. The study demonstrated increases in brain beta-NTP following recovery sleep. Interestingly, these increases were of a markedly greater magnitude in MM subjects compared to control subjects. A similar study examined sleep deprivation in cocaine-dependent subjects demonstrating that cocaine-dependent subjects exhibit greater increases in brain beta-NTP following recovery sleep when compared to control subjects. The studies suggest that sleep deprivation in both MM subjects and cocaine-dependent subjects is characterized by greater changes in brain ATP levels than control subjects. Greater enhancements in brain ATP following recovery sleep may reflect a greater disruption to or impact of sleep deprivation in drug dependent subjects, whereby sleep restoration processes may be unable to properly regulate brain ATP and maintain brain high-energy equilibrium. These studies support the notion of a greater susceptibility to sleep loss in drug dependent populations. Additional sleep studies in drug abusing

  16. Low-Rank Decomposition Based Restoration of Compressed Images via Adaptive Noise Estimation.

    Science.gov (United States)

    Zhang, Xinfeng; Lin, Weisi; Xiong, Ruiqin; Liu, Xianming; Ma, Siwei; Gao, Wen

    2016-07-07

    Images coded at low bit rates in real-world applications usually suffer from significant compression noise, which significantly degrades the visual quality. Traditional denoising methods are not suitable for the content-dependent compression noise, which usually assume that noise is independent and with identical distribution. In this paper, we propose a unified framework of content-adaptive estimation and reduction for compression noise via low-rank decomposition of similar image patches. We first formulate the framework of compression noise reduction based upon low-rank decomposition. Compression noises are removed by soft-thresholding the singular values in singular value decomposition (SVD) of every group of similar image patches. For each group of similar patches, the thresholds are adaptively determined according to compression noise levels and singular values. We analyze the relationship of image statistical characteristics in spatial and transform domains, and estimate compression noise level for every group of similar patches from statistics in both domains jointly with quantization steps. Finally, quantization constraint is applied to estimated images to avoid over-smoothing. Extensive experimental results show that the proposed method not only improves the quality of compressed images obviously for post-processing, but are also helpful for computer vision tasks as a pre-processing method.

  17. Inspection of copper canisters for spent nuclear fuel by means of ultrasound. Nonlinear acoustics, synthetic aperture imaging

    Energy Technology Data Exchange (ETDEWEB)

    Lingvall, Fredrik; Ping Wu; Stepinski, Tadeusz [Uppsala Univ., (Sweden). Dept. of Materials Science

    2003-03-01

    This report contains results concerning inspection of copper canisters for spent nuclear fuel by means of ultrasound obtained at Signals and Systems, Uppsala University in year 2001/2002. The first chapter presents results of an investigation of a new method for synthetic aperture imaging. The new method presented here takes the form of a 2D filter based on minimum mean squared error (MMSE) criteria. The filter, which varies with the target position in two dimensions includes information about spatial impulse response (SIR) of the imaging system. Spatial resolution of the MMSE method is investigated and compared experimentally to that of the classical SAFT and phased array imaging. It is shown that the resolution of the MMSE algorithm, evaluated for imaging immersed copper specimen is superior to that observed for the two above-mentioned methods. Extended experimental and theoretical research concerning the potential of nonlinear waves and material harmonic imaging is presented in the second chapter. An experimental work is presented that was conducted using the RITEC RAM-5000 ultrasonic system capable of providing a high power tone-burst output. A new method for simulation of nonlinear acoustic waves that is a combination of the angular spectrum approach and the Burger's equation is also presented. This method was used for simulating nonlinear elastic waves radiated by the annular transducer that was used in the experiments.

  18. Exact spectrum of non-linear chirp scaling and its application in geosynchronous synthetic aperture radar imaging

    Directory of Open Access Journals (Sweden)

    Chen Qi

    2013-07-01

    Full Text Available Non-linear chirp scaling (NLCS is a feasible method to deal with time-variant frequency modulation (FM rate problem in synthetic aperture radar (SAR imaging. However, approximations in derivation of NLCS spectrum lead to performance decline in some cases. Presented is the exact spectrum of the NLCS function. Simulation with a geosynchronous synthetic aperture radar (GEO-SAR configuration is implemented. The results show that using the presented spectrum can significantly improve imaging performance, and the NLCS algorithm is suitable for GEO-SAR imaging after modification.

  19. Accurate measurement of respiratory airway wall thickness in CT images using a signal restoration technique

    Science.gov (United States)

    Park, Sang Joon; Kim, Tae Jung; Kim, Kwang Gi; Lee, Sang Ho; Goo, Jin Mo; Kim, Jong Hyo

    2008-03-01

    Airway wall thickness (AWT) is an important bio-marker for evaluation of pulmonary diseases such as chronic bronchitis, bronchiectasis. While an image-based analysis of the airway tree can provide precise and valuable airway size information, quantitative measurement of AWT in Multidetector-Row Computed Tomography (MDCT) images involves various sources of error and uncertainty. So we have developed an accurate AWT measurement technique for small airways with three-dimensional (3-D) approach. To evaluate performance of these techniques, we used a set of acryl tube phantom was made to mimic small airways to have three different sizes of wall diameter (4.20, 1.79, 1.24 mm) and wall thickness (1.84, 1.22, 0.67 mm). The phantom was imaged with MDCT using standard reconstruction kernel (Sensation 16, Siemens, Erlangen). The pixel size was 0.488 mm × 0.488 mm × 0.75 mm in x, y, and z direction respectively. The images were magnified in 5 times using cubic B-spline interpolation, and line profiles were obtained for each tube. To recover faithful line profile from the blurred images, the line profiles were deconvolved with a point spread kernel of the MDCT which was estimated using the ideal tube profile and image line profile. The inner diameter, outer diameter, and wall thickness of each tube were obtained with full-width-half-maximum (FWHM) method for the line profiles before and after deconvolution processing. Results show that significant improvement was achieved over the conventional FWHM method in the measurement of AWT.

  20. A new automated assessment method for contrast-detail images by applying support vector machine and its robustness to nonlinear image processing.

    Science.gov (United States)

    Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

    2013-09-01

    The automated contrast-detail (C-D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C-D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C-D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5-5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C-D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C-D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C-D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

  1. Artifacts in field free line magnetic particle imaging in the presence of inhomogeneous and nonlinear magnetic fields

    Directory of Open Access Journals (Sweden)

    Medimagh Hanne

    2015-09-01

    Full Text Available Introduction: Magnetic Particle Imaging (MPI is an emerging medical imaging modality that detects super-paramagnetic particles exploiting their nonlinear magnetization response. Spatial encoding can be realized using a Field Free Line (FFL, which is generated, rotated and translated through the Field of View (FOV using a combination of magnetic gradient fields and homogeneous excitation fields. When scaling up systems and/or enlarging the FOV in comparison to the scanner bore, ensuring homogeneity and linearity of the magnetic fields becomes challenging. The present contribution describes the first comprehensive, systematic study on the influence of magnetic field imperfections in FFL MPI. Methods: In a simulation study, 14 different FFL scanner setups have been examined. Starting from an ideal scanner using perfect magnetic fields, defined imperfections have been introduced in a range of configurations (nonlinear gradient fields, inhomogeneous excitation fields, or inhomogeneous receive fields, or a combination thereof. In the first part of the study, the voltage induced in the receive channels parallel and perpendicular to the FFL translation have been studied for discrete FFL angles. In the second part, an imaging process has been simulated comparing different image reconstruction approaches. Results: The induced voltage signals demonstrate illustratively the effect of the magnetic field imperfections. In images reconstructed using a Radon-based approach, the magnetic field imperfections lead to pronounced artifacts, especially if a deconvolution using the point spread function is performed. In images reconstructed using a system function based approach, variations in local image quality become visible. Conclusion: For Radon-based image reconstruction in FFL MPI in the presence of inhomogeneous and nonlinear magnetic fields, artifact correction methods will have to be developed. In this regard, a first approach has recently been presented by

  2. A BVMF-B algorithm for nonconvex nonlinear regularized decomposition of spectral x-ray projection images

    Science.gov (United States)

    Pham, Mai Quyen; Ducros, Nicolas; Nicolas, Barbara

    2017-03-01

    Spectral computed tomography (CT) exploits the measurements obtained by a photon counting detector to reconstruct the chemical composition of an object. In particular, spectral CT has shown a very good ability to image K-edge contrast agent. Spectral CT is an inverse problem that can be addressed solving two subproblems, namely the basis material decomposition (BMD) problem and the tomographic reconstruction problem. In this work, we focus on the BMD problem, which is ill-posed and nonlinear. The BDM problem is classically either linearized, which enables reconstruction based on compressed sensing methods, or nonlinearly solved with no explicit regularization scheme. In a previous communication, we proposed a nonlinear regularized Gauss-Newton (GN) algorithm.1 However, this algorithm can only be applied to convex regularization functionals. In particular, the lp (p thorax phantom made of soft tissue, bone and gadolinium, which is scanned with a 90-kV x-ray tube and a 3-bin photon counting detector.

  3. Imaging the anisotropic nonlinear meissner effect in nodal YBa2 Cu3 O7-δ thin-film superconductors.

    Science.gov (United States)

    Zhuravel, Alexander P; Ghamsari, B G; Kurter, C; Jung, P; Remillard, S; Abrahams, J; Lukashenko, A V; Ustinov, Alexey V; Anlage, Steven M

    2013-02-22

    We have directly imaged the anisotropic nonlinear Meissner effect in an unconventional superconductor through the nonlinear electrodynamic response of both (bulk) gap nodes and (surface) Andreev bound states. A superconducting thin film is patterned into a compact self-resonant spiral structure, excited near resonance in the radio-frequency range, and scanned with a focused laser beam perturbation. At low temperatures, direction-dependent nonlinearities in the reactive and resistive properties of the resonator create photoresponse that maps out the directions of nodes, or of bound states associated with these nodes, on the Fermi surface of the superconductor. The method is demonstrated on the nodal superconductor YBa2Cu3O7-δ and the results are consistent with theoretical predictions for the bulk and surface contributions.

  4. Computationally efficient nonlinear edge preserving smoothing of n-D medical images via scale-space fingerprint analysis

    Energy Technology Data Exchange (ETDEWEB)

    Reutter, B.W.; Algazi, V.R.; Huesman, R.H.

    2000-10-11

    Nonlinear edge preserving smoothing often is performed prior to medical image segmentation. The goal of the nonlinear smoothing is to improve the accuracy of the segmentation by preserving changes in image intensity at the boundaries of structures of interest, while smoothing random variations due to noise in the interiors of the structures. Methods include median filtering and morphology operations such as gray scale erosion and dilation, as well as spatially varying smoothing driven by local contrast measures. Rather than irreversibly altering the image data prior to segmentation, the approach described here has the potential to unify nonlinear edge preserving smoothing with segmentation based on differential edge detection at multiple scales. The analysis of n-D image data is decomposed into independent 1-D problems that can be solved quickly. Smoothing in various directions along 1-D profiles through the n-D data is driven by a measure of local structure separation, rather than by a local contrast measure. Isolated edges are preserved independent of their contrast, given an adequate contrast to noise ratio.

  5. Band selection for nonlinear unmixing of hyperspectral images as a maximal clique problem.

    Science.gov (United States)

    Imbiriba, Tales; Bermudez, Jose Carlos; Richard, Cedric

    2017-03-01

    Kernel-based nonlinear mixing models have been applied to unmix spectral information of hyperspectral images when the type of mixing occurring in the scene is too complex or unknown. Such methods, however, usually require the inversion of matrices of sizes equal to the number of spectral bands. Reducing the computational load of these methods remains a challenge in large scale applications. This paper proposes a centralized band selection (BS) method for supervised unmixing in the reproducing kernel Hilbert space (RKHS). It is based upon the coherence criterion, which sets the largest value allowed for correlations between the basis kernel functions characterizing the selected bands in the unmixing model. We show that the proposed BS approach is equivalent to solving a maximum clique problem (MCP), i.e., searching for the biggest complete subgraph in a graph. Furthermore, we devise a strategy for selecting the coherence threshold and the Gaussian kernel bandwidth using coherence bounds for linearly independent bases. Simulation results illustrate the efficiency of the proposed method.

  6. Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

    Science.gov (United States)

    Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

    2016-06-01

    Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

  7. Fuzzy nonlinear proximal support vector machine for land extraction based on remote sensing image.

    Directory of Open Access Journals (Sweden)

    Xiaomei Zhong

    Full Text Available Currently, remote sensing technologies were widely employed in the dynamic monitoring of the land. This paper presented an algorithm named fuzzy nonlinear proximal support vector machine (FNPSVM by basing on ETM(+ remote sensing image. This algorithm is applied to extract various types of lands of the city Da'an in northern China. Two multi-category strategies, namely "one-against-one" and "one-against-rest" for this algorithm were described in detail and then compared. A fuzzy membership function was presented to reduce the effects of noises or outliers on the data samples. The approaches of feature extraction, feature selection, and several key parameter settings were also given. Numerous experiments were carried out to evaluate its performances including various accuracies (overall accuracies and kappa coefficient, stability, training speed, and classification speed. The FNPSVM classifier was compared to the other three classifiers including the maximum likelihood classifier (MLC, back propagation neural network (BPN, and the proximal support vector machine (PSVM under different training conditions. The impacts of the selection of training samples, testing samples and features on the four classifiers were also evaluated in these experiments.

  8. A Kalman Filtering and Nonlinear Penalty Regression Approach for Noninvasive Anemia Detection with Palpebral Conjunctiva Images

    Directory of Open Access Journals (Sweden)

    Yi-Ming Chen

    2017-01-01

    Full Text Available Noninvasive medical procedures are usually preferable to their invasive counterparts in the medical community. Anemia examining through the palpebral conjunctiva is a convenient noninvasive procedure. The procedure can be automated to reduce the medical cost. We propose an anemia examining approach by using a Kalman filter (KF and a regression method. The traditional KF is often used in time-dependent applications. Here, we modified the traditional KF for the time-independent data in medical applications. We simply compute the mean value of the red component of the palpebral conjunctiva image as our recognition feature and use a penalty regression algorithm to find a nonlinear curve that best fits the data of feature values and the corresponding levels of hemoglobin (Hb concentration. To evaluate the proposed approach and several relevant approaches, we propose a risk evaluation scheme, where the entire Hb spectrum is divided into high-risk, low-risk, and doubtful intervals for anemia. The doubtful interval contains the Hb threshold, say 11 g/dL, separating anemia and nonanemia. A suspect sample is the sample falling in the doubtful interval. For the anemia screening purpose, we would like to have as less suspect samples as possible. The experimental results show that the modified KF reduces the number of suspect samples significantly for all the approaches considered here.

  9. Restorative treatment thresholds for interproximal primary caries based on radiographic images: findings from the Dental Practice-Based Research Network

    DEFF Research Database (Denmark)

    Gordan, Valeria V; Garvan, Cynthia W; Heft, Marc W

    2009-01-01

    with restorative intervention in lesions that have penetrated only the enamel surface. This study surveyed dentists from the Dental Practice-Based Research Network (DPBRN) who had reported doing at least some restorative dentistry (n = 901). Dentists were asked to indicate the depth at which they would restore...

  10. Continuous evaluation of land cover restoration of tsunami struck plains in Japan by using several kinds of optical satellite image in time series

    Science.gov (United States)

    Hashiba, H.

    2015-09-01

    The Mw 9.0 earthquake that struck Japan in 2011 was followed by a large-scale tsunami in the Tohoku region. The damage in the coastal plane was extensively displayed through many satellite images. Furthermore, satellite imaging is requested for the ongoing evaluation of the restoration process. The reconstruction of the urban structure, farmlands, grassland, and coastal forest that collapsed under the large tsunami requires effective long-term monitoring. Moreover, the post-tsunami land cover dynamics can be effectively modeled using time-constrained satellite data to establish a prognosis method for the mitigation of future tsunami impact. However, the remote satellite capture of a long-term restoration process is compromised by accumulating spatial resolution effects and seasonal influences. Therefore, it is necessary to devise a method for data selection and dataset structure. In the present study, the restoration processes were investigated in four years following the disaster in a part of the Sendai plain, northeast Japan, from same-season satellite images acquired by different optical sensors. Coastal plains struck by the tsunami are evaluated through land-cover classification processing using the clustering method. The changes in land cover are analyzed from time-series optical images acquired by Landsat-5/TM, 7/ETM+, 8/OLI, EO-1/ALI, and ALOS-1/AVNIR-2. The study reveals several characteristics of the change in the inundation area and signs of artificial and natural restoration.

  11. Cellular imaging of deep organ using two-photon Bessel light-sheet nonlinear structured illumination microscopy

    Science.gov (United States)

    Zhao, Ming; Zhang, Han; Li, Yu; Ashok, Amit; Liang, Rongguang; Zhou, Weibin; Peng, Leilei

    2014-01-01

    In vivo fluorescent cellular imaging of deep internal organs is highly challenging, because the excitation needs to penetrate through strong scattering tissue and the emission signal is degraded significantly by photon diffusion induced by tissue-scattering. We report that by combining two-photon Bessel light-sheet microscopy with nonlinear structured illumination microscopy (SIM), live samples up to 600 microns wide can be imaged by light-sheet microscopy with 500 microns penetration depth, and diffused background in deep tissue light-sheet imaging can be reduced to obtain clear images at cellular resolution in depth beyond 200 microns. We demonstrate in vivo two-color imaging of pronephric glomeruli and vasculature of zebrafish kidney, whose cellular structures located at the center of the fish body are revealed in high clarity by two-color two-photon Bessel light-sheet SIM. PMID:24876996

  12. Second harmonic and subharmonic for non-linear wideband contrast imaging using a capacitive micromachined ultrasonic transducer array.

    Science.gov (United States)

    Novell, Anthony; Escoffre, Jean-Michel; Bouakaz, Ayache

    2013-08-01

    When insonified with suitable ultrasound excitation, contrast microbubbles generate various non-linear scattered components, such as the second harmonic (2H) and the subharmonic (SH). In this study, we exploit the wide frequency bandwidth of capacitive micromachined ultrasonic transducers (CMUTs) to enhance the response from ultrasound contrast agents by selective imaging of both the 2H and SH components simultaneously. To this end, contrast images using the pulse inversion method were recorded with a 64-element CMUT linear array connected to an open scanner. In comparison to imaging at 2H alone, the wideband imaging including both the 2H and SH contributions provided up to 130% and 180% increases in the signal-to-noise and contrast-to-tissue ratios, respectively. The wide-frequency band of CMUTs offers new opportunities for improved ultrasound contrast agent imaging.

  13. Cellular imaging of deep organ using two-photon Bessel light-sheet nonlinear structured illumination microscopy.

    Science.gov (United States)

    Zhao, Ming; Zhang, Han; Li, Yu; Ashok, Amit; Liang, Rongguang; Zhou, Weibin; Peng, Leilei

    2014-05-01

    In vivo fluorescent cellular imaging of deep internal organs is highly challenging, because the excitation needs to penetrate through strong scattering tissue and the emission signal is degraded significantly by photon diffusion induced by tissue-scattering. We report that by combining two-photon Bessel light-sheet microscopy with nonlinear structured illumination microscopy (SIM), live samples up to 600 microns wide can be imaged by light-sheet microscopy with 500 microns penetration depth, and diffused background in deep tissue light-sheet imaging can be reduced to obtain clear images at cellular resolution in depth beyond 200 microns. We demonstrate in vivo two-color imaging of pronephric glomeruli and vasculature of zebrafish kidney, whose cellular structures located at the center of the fish body are revealed in high clarity by two-color two-photon Bessel light-sheet SIM.

  14. Dynamic positron emission tomography image restoration via a kinetics-induced bilateral filter.

    Directory of Open Access Journals (Sweden)

    Zhaoying Bian

    Full Text Available Dynamic positron emission tomography (PET imaging is a powerful tool that provides useful quantitative information on physiological and biochemical processes. However, low signal-to-noise ratio in short dynamic frames makes accurate kinetic parameter estimation from noisy voxel-wise time activity curves (TAC a challenging task. To address this problem, several spatial filters have been investigated to reduce the noise of each frame with noticeable gains. These filters include the Gaussian filter, bilateral filter, and wavelet-based filter. These filters usually consider only the local properties of each frame without exploring potential kinetic information from entire frames. Thus, in this work, to improve PET parametric imaging accuracy, we present a kinetics-induced bilateral filter (KIBF to reduce the noise of dynamic image frames by incorporating the similarity between the voxel-wise TACs using the framework of bilateral filter. The aim of the proposed KIBF algorithm is to reduce the noise in homogeneous areas while preserving the distinct kinetics of regions of interest. Experimental results on digital brain phantom and in vivo rat study with typical (18F-FDG kinetics have shown that the present KIBF algorithm can achieve notable gains over other existing algorithms in terms of quantitative accuracy measures and visual inspection.

  15. Enclosed Laplacian Operator of Nonlinear Anisotropic Diffusion to Preserve Singularities and Delete Isolated Points in Image Smoothing

    Directory of Open Access Journals (Sweden)

    Zhiwu Liao

    2011-01-01

    Full Text Available Existing Nonlinear Anisotropic Diffusion (NAD methods in image smoothing cannot obtain satisfied results near singularities and isolated points because of the discretization errors. In this paper, we propose a new scheme, named Enclosed Laplacian Operator of Nonlinear Anisotropic Diffusion (ELONAD, which allows us to provide a unified framework for points in flat regions, edge points and corners, even can delete isolated points and spurs. ELONAD extends two diffusion directions of classical NAD to eight or more enclosed directions. Thus it not only performs NAD according to modules of enclosed directions which can reduce the influence of traction errors greatly, but also distinguishes isolated points and small spurs from corners which must be preserved. Smoothing results for test patterns and real images using different discretization schemes are also given to test and verify our discussions.

  16. Synthesis and functionalization of a triaryldiamine-base photoconductive/photorefractive composite, and its application to aberrated image restoration

    Science.gov (United States)

    Liang, Yichen

    Organic phoorefractive (PR) composites have recently emerged as an important class of materials for applications including high-density data storage, optical communication, and biomedical imaging. In an effort to further improve their performance, this study focused on the utilization of functionalized semiconductor nanocrystals to photosensitize triaryamine (TPD)-based PR composites, as well as the application of TPD-based PR composites in the restoration of aberrated optical information. A novel approach to functionalize CdSe quantum dot (QCdSe) was firstly introduced where the sulfonated triarydiamine (STPD) was used as charge-transporting ligand to passivate QCdSe. TPD-based photoconductive and PR composites were photosensitized with the STPD-passivated QCdSe (SQCdSe). Due to the charge-transporting capability of STPD, the composites photosensitized with STPD-capped QCdSe exhibited superior performance relative to composites employing more traditional photosensitizers (such as fullerene C60 and trioctylphosphine-capped QCdSe), with figures-of-merit including photoconductivities in excess of 60 pS/cm, two-beam coupling gain coefficients in excess of 110 cm-1, and PR response time of less than 30 ms. In addition, the ability of TPD-based PR composites to correct aberrations associated with a laser beam was described. Here, a severely aberrated laser beam was able to be restored to a nearly unaberrated condition through the PR process, and the potential of this technique for practical applications was well explained. Based on the current experimental geometry, a PR response time of 0.5 s was observed, which is the fastest PR response time reported for a PR composite operating under experimental conditions designed for the correction of optical aberrations.

  17. Image Restoration Based onMulti-channel Blind Restoration and Sparse Representation Method%基于多通道盲复原和改进K-SVD模型的图像恢复

    Institute of Scientific and Technical Information of China (English)

    陈杰; 尚丽; 孙站里

    2015-01-01

    图像盲复原( IBR)问题一直是图像处理中的重要研究课题。目前空间不变的多通道图像盲复原算法研究较为普遍,这种算法具有较好的盲去模糊效果,但是对噪声的抑制能力不足,特别是对含有大量噪声的低分辨率图像而言,消噪效果较差。基于K-奇异值分解( K-SVD )的模型能够有效地处理噪声方差较大的图像,但是不能自适应图像的稀疏先验性。为了解决上述问题,在全变分( TV)多通道IBR算法处理的基础上,结合一种改进的K-SVD消噪模型的优势,提出了一种新的组合图像恢复方法。改进的K-SVD模型考虑了图像特征系数的稀疏先验知识和最大化稀疏度,具有自适应的消噪鲁棒性。分别采用模拟的和真实的低分辨率图像(毫米波图像)进行测试,与采用单一的多通道盲恢复和图像消噪算法相比,实验结果表明所提出的图像恢复方法具有较好的视觉效果和较高的信噪比。%The problem of image blind restoration ( IBR) has been the important research issue in image process-ing. At present, the research of multi-channel with space invariant is very common. This algorithm behaves certain advantages in blind de-blurring, but it is limited to denoise images. Especially, to low resolution ( LR ) images, which contain much unknown noise, the restored effect is worse only using the multi-channel restoration technique. K-mean based singular value decomposition ( K-SVD) model can denoise images with large noise variance, however, it is not self-adaptive to an image’ s priors. To solve this defect, on the basis of processed results by the total variation ( TV) based multi-channel restoration algorithm, further combined a modified K-SVD model’ s advantage in denoising images, a novel combined image restoration method is discussed here. This modified K-SVD model considers the sparse priors and maximize sparsity of image feature coefficients and

  18. Image Prediction Method with Nonlinear Control Lines Derived from Kriging Method with Extracted Feature Points Based on Morphing

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2013-01-01

    Full Text Available Method for image prediction with nonlinear control lines which are derived from extracted feature points from the previously acquired imagery data based on Kriging method and morphing method is proposed. Through comparisons between the proposed method and the conventional linear interpolation and widely used Cubic Spline interpolation methods, it is found that the proposed method is superior to the conventional methods in terms of prediction accuracy.

  19. Beyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging

    Science.gov (United States)

    Chernavskaia, Olga; Heuke, Sandro; Vieth, Michael; Friedrich, Oliver; Schürmann, Sebastian; Atreya, Raja; Stallmach, Andreas; Neurath, Markus F.; Waldner, Maximilian; Petersen, Iver; Schmitt, Michael; Bocklitz, Thomas; Popp, Jürgen

    2016-07-01

    Assessing disease activity is a prerequisite for an adequate treatment of inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis. In addition to endoscopic mucosal healing, histologic remission poses a promising end-point of IBD therapy. However, evaluating histological remission harbors the risk for complications due to the acquisition of biopsies and results in a delay of diagnosis because of tissue processing procedures. In this regard, non-linear multimodal imaging techniques might serve as an unparalleled technique that allows the real-time evaluation of microscopic IBD activity in the endoscopy unit. In this study, tissue sections were investigated using the non-linear multimodal microscopy combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited auto fluorescence (TPEF) and second-harmonic generation (SHG). After the measurement a gold-standard assessment of histological indexes was carried out based on a conventional H&E stain. Subsequently, various geometry and intensity related features were extracted from the multimodal images. An optimized feature set was utilized to predict histological index levels based on a linear classifier. Based on the automated prediction, the diagnosis time interval is decreased. Therefore, non-linear multimodal imaging may provide a real-time diagnosis of IBD activity suited to assist clinical decision making within the endoscopy unit.

  20. Epi-detected quadruple-modal nonlinear optical microscopy for label-free imaging of the tooth

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zi; Zheng, Wei; Huang, Zhiwei, E-mail: biehzw@nus.edu.sg [Optical Bioimaging Laboratory, Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore 117576 (Singapore); Stephen Hsu, Chin-Ying [Department of Dentistry, Faculty of Dentistry, National University of Singapore and National University Health System, Singapore 119083 (Singapore)

    2015-01-19

    We present an epi-detected quadruple-modal nonlinear optical microscopic imaging technique (i.e., coherent anti-Stokes Raman scattering (CARS), second-harmonic generation (SHG), third-harmonic generation (THG), and two-photon excited fluorescence (TPEF)) based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of the tooth. We demonstrate that high contrast ps-CARS images covering both the fingerprint (500–1800 cm{sup −1}) and high-wavenumber (2500–3800 cm{sup −1}) regions can be acquired to uncover the distributions of mineral and organic biomaterials in the tooth, while high quality TPEF, SHG, and THG images of the tooth can also be acquired under ps laser excitation without damaging the samples. The quadruple-modal nonlinear microscopic images (CARS/SHG/THG/TPEF) acquired provide better understanding of morphological structures and biochemical/biomolecular distributions in the dentin, enamel, and the dentin-enamel junction of the tooth without labeling, facilitating optical diagnosis and characterization of the tooth in dentistry.

  1. 基于模拟方法的水下图像复原%Underwater image restoration based on simulation method

    Institute of Scientific and Technical Information of China (English)

    鲁国春; 聂武; 张赫

    2011-01-01

    采用模板假设、离焦模糊和大气湍流干扰3种退化模型模拟散射过程,对水下图像进行复原.试验表明,模拟方法可行,复原图像质量有明显改善,可为水下图像散射退化机理研究提供参考.%Three degradation models such as template hypothesis,defocus blur and atmospheric turbulence interference were used to simulate scattering process, and restore underwater image.Experiments show that the simulation methods are feasible,and the restored image is improved obviously,which can give reference for scattering mechanism research of underwater image degradation.

  2. Quantitative imaging of nonlinear shear modulus by combining static elastography and shear wave elastography.

    Science.gov (United States)

    Latorre-Ossa, Heldmuth; Gennisson, Jean-Luc; De Brosses, Emilie; Tanter, Mickaël

    2012-04-01

    The study of new tissue mechanical properties such as shear nonlinearity could lead to better tissue characterization and clinical diagnosis. This work proposes a method combining static elastography and shear wave elastography to derive the nonlinear shear modulus by applying the acoustoelasticity theory in quasi-incompressible soft solids. Results demonstrate that by applying a moderate static stress at the surface of the investigated medium, and by following the quantitative evolution of its shear modulus, it is possible to accurately and quantitatively recover the local Landau (A) coefficient characterizing the shear nonlinearity of soft tissues.

  3. Study of frequency pattern of coherent turbulent flow over ripples using image processing with implication in river restoration

    Directory of Open Access Journals (Sweden)

    A. Keshavarzi

    2011-08-01

    Full Text Available River channel change and bed scourings are source of major environmental problem for fish and aquatic habitat. The bed form such as ripples and dunes is the result of an interaction between turbulent flow structure and sediment particles at the bed. The structure of turbulent flow over ripples is important to understand initiation of sediment entrainment and its transport. The focus of this study is the measurement and analysis of the dominant bursting events and the flow structure over ripples in the bed of a channel. Two types of ripples with sinusoidal and triangular forms were tested in this study. The velocities of flow over the ripples were measured in three dimensions using an Acoustic Doppler Velocimeter with a sampling rate of 50 Hz. These velocities were measured at different points within the flow depth from the bed and at different longitudinal positions along the flume. A CCD camera was used to capture 1500 sequential images from the bed and to monitor sediment movement at different positions along the bed. Application of image processing technique enabled us to compute the number of entrained and deposited particles over the ripples. From a quadrant decomposition of instantaneous velocity fluctuations close to the bed, it was found that bursting events downstream of the second ripple, in Quadrants 1 and 3, were dominant whereas upstream of the ripple, Quadrants 2 and 4 were dominant. More importantly consideration of these results indicates that the normalized occurrence probabilities of sweep events are in phase with the bed forms whereas those of ejection event are out of phase with the bed form. Therefore entrainment would be expected to occur upstream and deposition occurs downstream of the ripple. These expectations were confirmed by measurement of entrained and deposited sediment particles from the bed. These above information can be used in practical application for rivers where restoration is required.

  4. 被动毫米波图像恢复的偏微分方程方法%Partial Differential Equation Method for Passive Millimeter Wave Image Restoration

    Institute of Scientific and Technical Information of China (English)

    王本庆; 李兴国

    2009-01-01

    For the problem that passive millimeter wave (MMW) image is fuzzy and of low resolution,the par-tial differential equation (PDE) method is proposed for high-resolution restoration of the image and then the PDE model and the corresponsive image restoration algorithm are given. First, this method denoises the obtained blurred image by using two Gauss function of different scale parameter to get two images which are more blurred,and then obtain the high-resolution image using iteration from the two images. This PDE algorithm is of simple principle and convenient calculation. Passive MMW image restoration of an actual metal target shows that this method is effective.%针对被动毫米波图像模糊和分辨率较低,提出采用偏微分方程方法进行图像的高分辨率恢复,并给出了偏微分方程模型和相应的图像恢复算法.该方法首先把得到的带噪降晰图像进行两个不同尺度的 Gauss 去噪,获得两幅更模糊的再降晰图像,再以这两幅图像为基础,通过迭代计算得到高分辨率图像.偏微分方程方法原理简单并且计算方便,通过对实际金属目标的被动毫米波图像的恢复,显示该方法具有较好的恢复效果.

  5. Nonlinear Microwave Imaging for Breast-Cancer Screening Using Gauss–Newton's Method and the CGLS Inversion Algorithm

    DEFF Research Database (Denmark)

    Rubæk, Tonny; Meaney, P. M.; Meincke, Peter;

    2007-01-01

    Breast-cancer screening using microwave imaging is emerging as a new promising technique as a supplement to X-ray mammography. To create tomographic images from microwave measurements, it is necessary to solve a nonlinear inversion problem, for which an algorithm based on the iterative Gauss-Newton...... method has been developed at Dartmouth College. This algorithm determines the update values at each iteration by solving the set of normal equations of the problem using the Tikhonov algorithm. In this paper, a new algorithm for determining the iteration update values in the Gauss-Newton algorithm...... algorithm is compared to the Gauss-Newton algorithm with Tikhonov regularization and is shown to reconstruct images of similar quality using fewer iterations....

  6. Nonlinear coil sensitivity estimation for parallel magnetic resonance imaging using data-adaptive steering kernel regression method.

    Science.gov (United States)

    Fang, Sheng; Guo, Hua

    2013-01-01

    The parallel magnetic resonance imaging (parallel imaging) technique reduces the MR data acquisition time by using multiple receiver coils. Coil sensitivity estimation is critical for the performance of parallel imaging reconstruction. Currently, most coil sensitivity estimation methods are based on linear interpolation techniques. Such methods may result in Gibbs-ringing artifact or resolution loss, when the resolution of coil sensitivity data is limited. To solve the problem, we proposed a nonlinear coil sensitivity estimation method based on steering kernel regression, which performs a local gradient guided interpolation to the coil sensitivity. The in vivo experimental results demonstrate that this method can effectively suppress Gibbs ringing artifact in coil sensitivity and reduces both noise and residual aliasing artifact level in SENSE reconstruction.

  7. Restorative treatment thresholds for interproximal primary caries based on radiographic images: findings from the Dental Practice-Based Research Network

    DEFF Research Database (Denmark)

    Gordan, Valeria V; Garvan, Cynthia W; Heft, Marc W

    2009-01-01

    with restorative intervention in lesions that have penetrated only the enamel surface. This study surveyed dentists from the Dental Practice-Based Research Network (DPBRN) who had reported doing at least some restorative dentistry (n = 901). Dentists were asked to indicate the depth at which they would restore...... that they would restore a proximal enamel lesion, while 24% would do so once the lesion had reached into the outer third of the dentin. For a low caries risk patient, 39% of respondents reported that they would restore an enamel lesion, and 54% would do so once the lesion had reached into the outer third...... of the dentin. In multivariate analyses that accounted for dentist and practice characteristics, dentists in large group practices were less likely to intervene surgically for enamel caries, regardless of patient's caries risk....

  8. Efficient restoration of variable area soundtracks:

    OpenAIRE

    Abdelâali Hassaïne; Etienne Decencière; Bernard Besserer

    2009-01-01

    The restoration of motion picture films using digital image processing has been an active research field for many years. The restoration of the soundtrack however, has mainly been performed in the sound domain, using signal processing methods, in spite of the fact that it is recorded as a continuous image between the images of the film and the perforations. In this paper a restoration method for variable area soundtrack restoration at the image level is presented. First, a novel method is pro...

  9. Efficient restoration of variable area soundtracks:

    OpenAIRE

    Abdelâali Hassaïne; Etienne Decencière; Bernard Besserer

    2009-01-01

    The restoration of motion picture films using digital image processing has been an active research field for many years. The restoration of the soundtrack however, has mainly been performed in the sound domain, using signal processing methods, in spite of the fact that it is recorded as a continuous image between the images of the film and the perforations. In this paper a restoration method for variable area soundtrack restoration at the image level is presented. First, a novel method is pro...

  10. A novel non-linear recursive filter design for extracting high rate pulse features in nuclear medicine imaging and spectroscopy.

    Science.gov (United States)

    Sajedi, Salar; Kamal Asl, Alireza; Ay, Mohammad R; Farahani, Mohammad H; Rahmim, Arman

    2013-06-01

    Applications in imaging and spectroscopy rely on pulse processing methods for appropriate data generation. Often, the particular method utilized does not highly impact data quality, whereas in some scenarios, such as in the presence of high count rates or high frequency pulses, this issue merits extra consideration. In the present study, a new approach for pulse processing in nuclear medicine imaging and spectroscopy is introduced and evaluated. The new non-linear recursive filter (NLRF) performs nonlinear processing of the input signal and extracts the main pulse characteristics, having the powerful ability to recover pulses that would ordinarily result in pulse pile-up. The filter design defines sampling frequencies lower than the Nyquist frequency. In the literature, for systems involving NaI(Tl) detectors and photomultiplier tubes (PMTs), with a signal bandwidth considered as 15 MHz, the sampling frequency should be at least 30 MHz (the Nyquist rate), whereas in the present work, a sampling rate of 3.3 MHz was shown to yield very promising results. This was obtained by exploiting the known shape feature instead of utilizing a general sampling algorithm. The simulation and experimental results show that the proposed filter enhances count rates in spectroscopy. With this filter, the system behaves almost identically as a general pulse detection system with a dead time considerably reduced to the new sampling time (300 ns). Furthermore, because of its unique feature for determining exact event times, the method could prove very useful in time-of-flight PET imaging.

  11. Blocked-regularized Gmres method of image restoration%图像恢复的分块正则化 Gmres 方法

    Institute of Scientific and Technical Information of China (English)

    陈亚文; 闵涛

    2013-01-01

    利用分块Gmres算法在处理大规模线性方程组时具有的优势,将其同正则化技术相结合应用于图像恢复领域,提出一种新的图像恢复的方法。该方法考虑了图像恢复中的时间复杂度与空间复杂度2个方面。数值模拟时,对不同的方法进行了对比分析,结果表明所提出的方法能够明显改善图像恢复的质量。%The blocked Gmres algorithm has certain superiority in dealing with the large systems of linear equations ,a new algorithm to combine the regularization algorithm with blocked Gmres algorithm in im-age restoration filed is proposed .T he algorithm considers the time and space complexity in image restora-tion .In the numerical simulation ,different methods are compared ,the results show that the method can significantly improves the quality of image restoration .

  12. Verification of nonlinear dynamic structural test results by combined image processing and acoustic analysis

    Science.gov (United States)

    Tene, Yair; Tene, Noam; Tene, G.

    1993-08-01

    An interactive data fusion methodology of video, audio, and nonlinear structural dynamic analysis for potential application in forensic engineering is presented. The methodology was developed and successfully demonstrated in the analysis of heavy transportable bridge collapse during preparation for testing. Multiple bridge elements failures were identified after the collapse, including fracture, cracks and rupture of high performance structural materials. Videotape recording by hand held camcorder was the only source of information about the collapse sequence. The interactive data fusion methodology resulted in extracting relevant information form the videotape and from dynamic nonlinear structural analysis, leading to full account of the sequence of events during the bridge collapse.

  13. Cubication of Conservative Nonlinear Oscillators

    Science.gov (United States)

    Belendez, Augusto; Alvarez, Mariela L.; Fernandez, Elena; Pascual, Immaculada

    2009-01-01

    A cubication procedure of the nonlinear differential equation for conservative nonlinear oscillators is analysed and discussed. This scheme is based on the Chebyshev series expansion of the restoring force, and this allows us to approximate the original nonlinear differential equation by a Duffing equation in which the coefficients for the linear…

  14. PDE-based Non-Linear Diffusion Techniques for Denoising Scientific and Industrial Images: An Empirical Study

    Energy Technology Data Exchange (ETDEWEB)

    Weeratunga, S K; Kamath, C

    2001-12-20

    Removing noise from data is often the first step in data analysis. Denoising techniques should not only reduce the noise, but do so without blurring or changing the location of the edges. Many approaches have been proposed to accomplish this; in this paper, they focus on one such approach, namely the use of non-linear diffusion operators. This approach has been studied extensively from a theoretical viewpoint ever since the 1987 work of Perona and Malik showed that non-linear filters outperformed the more traditional linear Canny edge detector. They complement this theoretical work by investigating the performance of several isotropic diffusion operators on test images from scientific domains. They explore the effects of various parameters such as the choice of diffusivity function, explicit and implicit methods for the discretization of the PDE, and approaches for the spatial discretization of the non-linear operator etc. They also compare these schemes with simple spatial filters and the more complex wavelet-based shrinkage techniques. The empirical results show that, with an appropriate choice of parameters, diffusion-based schemes can be as effective as competitive techniques.

  15. Nonlinear spectral imaging of human hypertrophic scar based on two-photon excited fluorescence and second-harmonic generation.

    Science.gov (United States)

    Chen, G; Chen, J; Zhuo, S; Xiong, S; Zeng, H; Jiang, X; Chen, R; Xie, S

    2009-07-01

    A noninvasive method using microscopy and spectroscopy for analysing the morphology of collagen and elastin and their biochemical variations in skin tissue will enable better understanding of the pathophysiology of hypertrophic scars and facilitate improved clinical management and treatment of this disease. To obtain simultaneously microscopic images and spectra of collagen and elastin fibres in ex vivo skin tissues (normal skin and hypertrophic scar) using a nonlinear spectral imaging method, and to compare the morphological structure and spectral characteristics of collagen and elastin fibres in hypertrophic scar tissues with those of normal skin, to determine whether this approach has potential for in vivo assessment of the pathophysiology of human hypertrophic scars and for monitoring treatment responses as well as for tracking the process of development of hypertrophic scars in clinic. Ex vivo human skin specimens obtained from six patients aged from 10 to 50 years old who were undergoing skin plastic surgery were examined. Five patients had hypertrophic scar lesions and one patient had no scar lesion before we obtained his skin specimen. A total of 30 tissue section samples of 30 mum thickness were analysed by the use of a nonlinear spectral imaging system consisting of a femtosecond excitation light source, a high-throughput scanning inverted microscope, and a spectral imaging detection system. The high-contrast and high-resolution second harmonic generation (SHG) images of collagen and two-photon excited fluorescence (TPEF) images of elastin fibres in hypertrophic scar tissues and normal skin were acquired using the extracting channel tool of the system. The emission spectra were analysed using the image-guided spectral analysis method. The depth-dependent decay constant of the SHG signal and the image texture characteristics of hypertrophic scar tissue and normal skin were used to quantitatively assess the amount, distribution and orientation of their

  16. Nonlinear Denoising and Analysis of Neuroimages With Kernel Principal Component Analysis and Pre-Image Estimation

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Abrahamsen, Trine Julie; Madsen, Kristoffer Hougaard

    2012-01-01

    We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising...... base these illustrations on two fMRI BOLD data sets — one from a simple finger tapping experiment and the other from an experiment on object recognition in the ventral temporal lobe....

  17. Quantitative Assessment of a Novel Super-Resolution Restoration Technique Using HiRISE with Navcam Images: how much Resolution Enhancement is Possible from Repeat-Pass Observations

    Science.gov (United States)

    Tao, Y.; Muller, J.-P.

    2016-06-01

    Higher spatial resolution imaging data is always desirable to the international community of planetary scientists interested in improving understanding of surface formation processes. We have previously developed a novel Super-resolution restoration (SRR) technique (Tao & Muller, 2016) using Gotcha sub-pixel matching, orthorectification, and segmented 4th order PDE-TV, called GPT SRR, which is able to restore 5 cm-12.5 cm near rover scale images (equivalent to Navcam projected FoV at a range of ≥ 5 m) from multiple 25 cm resolution NASA MRO HiRISE images. The SRR technique has been successfully applied to the rover traverses for the MER and MSL missions within the EU FP-7 PRoViDE project. These SRR results have revealed new surface information including the imaging of individual rocks (diameter ≥ 25 cm) by comparison of the original HiRISE image and rover Navcam orthorectified image mosaics. In this work, we seek evidence from processing a very large number of stereo reconstruction results from all Navcam stereo images within PRoViDE, registration and comparison with the corresponding SRR image, in order to derive a quantitative assessment on key features including rocks (diameter < 150 cm) and rover track wheel spacing. We summarise statistics from SRR-Navcam measurements and demonstrate that our unique SRR datasets will greatly support the geological and morphological analysis and monitoring of Martian surface and can also be applied to landing site selection, in order to avoid unsuitable terrain, for any future lander/rover as well as help to define future rover paths.

  18. Numerical discretization for nonlinear diffusion filter

    Science.gov (United States)

    Mustaffa, I.; Mizuar, I.; Aminuddin, M. M. M.; Dasril, Y.

    2015-05-01

    Nonlinear diffusion filters are famously used in machine vision for image denoising and restoration. This paper presents a study on the effects of different numerical discretization of nonlinear diffusion filter. Several numerical discretization schemes are presented; namely semi-implicit, AOS, and fully implicit schemes. The results of these schemes are compared by visual results, objective measurement e.g. PSNR and MSE. The results are also compared to a Daubechies wavelet denoising method. It is acknowledged that the two preceding scheme have already been discussed in literature, however comparison to the latter scheme has not been made. The semi-implicit scheme uses an additive operator splitting (AOS) developed to overcome the shortcoming of the explicit scheme i.e., stability for very small time steps. Although AOS has proven to be efficient, from the nonlinear diffusion filter results with different discretization schemes, examples shows that implicit schemes are worth pursuing.

  19. Nonlinear image encryption using a fully phase nonzero-order joint transform correlator in the Gyrator domain

    Science.gov (United States)

    Vilardy, Juan M.; Millán, María S.; Pérez-Cabré, Elisabet

    2017-02-01

    A novel nonlinear image encryption scheme based on a fully phase nonzero-order joint transform correlator architecture (JTC) in the Gyrator domain (GD) is proposed. In this encryption scheme, the two non-overlapping data distributions of the input plane of the JTC are fully encoded in phase and this input plane is transformed using the Gyrator transform (GT); the intensity distribution captured in the GD represents a new definition of the joint Gyrator power distribution (JGPD). The JGPD is modified by two nonlinear operations with the purpose of retrieving the encrypted image, with enhancement of the decrypted signal quality and improvement of the overall security. There are three keys used in the encryption scheme, two random phase masks and the rotation angle of the GT, which are all necessary for a proper decryption. Decryption is highly sensitivity to changes of the rotation angle of the GT as well as to little changes in other parameters or keys. The proposed encryption scheme in the GD still preserves the shift-invariance properties originated in the JTC-based encryption in the Fourier domain. The proposed encryption scheme is more resistant to brute force attacks, chosen-plaintext attacks, known-plaintext attacks, and ciphertext-only attacks, as they have been introduced in the cryptanalysis of the JTC-based encryption system. Numerical results are presented and discussed in order to verify and analyze the feasibility and validity of the novel encryption-decryption scheme.

  20. Inspection of copper canisters for spent nuclear fuel by means of ultrasound. NDE of friction stir welds, nonlinear acoustics, ultrasonic imaging

    Energy Technology Data Exchange (ETDEWEB)

    Stepinski, Tadeusz (ed.); Lingvall, Fredrik; Wennerstroem, Erik; Ping Wu [Uppsala Univ., Dept. of Materials Science (Sweden). Signals and Systems

    2004-01-01

    This report contains results concerning advanced ultrasound for the inspection of copper canisters for spent nuclear fuel obtained at Signals and Systems, Uppsala University in years 2002/2003. After a short introduction a review of the NDE techniques that have been applied to the assessment of friction stir welds (FSW) is presented. The review is based on the results reported by the specialists from the USA, mostly from the aerospace industry. A separate chapter is devoted to the extended experimental and theoretical research concerning potential of nonlinear waves in NDE applications. Further studies concerning nonlinear propagation of acoustic and elastic waves (classical nonlinearity) are reported. Also a preliminary investigation of the nonlinear ultrasonic detection of contacts and interfaces (non-classical nonlinearity) is included. Report on the continuation of previous work concerning computer simulation of nonlinear propagations of ultrasonic beams in water and in immersed solids is also presented. Finally, results of an investigation concerning a new method of synthetic aperture imaging (SAI) and its comparison to the traditional phased array (PA) imaging and to the synthetic aperture focusing technique (SAFT) are presented. A new spatial-temporal filtering method is presented that is a generalization of the previously proposed filter. Spatial resolution of the proposed method is investigated and compared experimentally to that of classical SAFT and PA imaging. Performance of the proposed method for flat targets is also investigated.

  1. Nonlinear microwave imaging using Levenberg-Marquardt method with iterative shrinkage thresholding

    KAUST Repository

    Desmal, Abdulla

    2014-07-01

    Development of microwave imaging methods applicable in sparse investigation domains is becoming a research focus in computational electromagnetics (D.W. Winters and S.C. Hagness, IEEE Trans. Antennas Propag., 58(1), 145-154, 2010). This is simply due to the fact that sparse/sparsified domains naturally exist in many applications including remote sensing, medical imaging, crack detection, hydrocarbon reservoir exploration, and see-through-the-wall imaging.

  2. Document Image Restoration Using Bayesian Inference Method%基于文档图像的贝叶斯重建算法仿真研究

    Institute of Scientific and Technical Information of China (English)

    郭皎; 鄢沛

    2011-01-01

    研究文档图像的分辨率提高问题,针对数字化文档图像在采集过程中遇到的低分辨率、噪声、纸张质量蜕化和形变等因素影响,提出了一种新的贝叶斯估计的最大后验概率算法对文档图像进行恢复和重构.首先利用聚类方法对文档中文字进行自动分类,然后依据每个类别中相同字符的先验知识,例如出现频率,几何特性等,利用一个能量方程来求取最终的MAP最优解,然后一个新颖的MAP迭代算法,反复利用对高分辨率图像的估计来逼近最优解,从而使得最终的高分辨率字符图像获得很高的清晰度.仿真结果表明提出的算法能稳定地提高文字的分辨率,提高文档的识别准确率,并且具有高的运算效率.在此基础上利用本文方法,可以方便的实现多文档或者书籍图像的重建和恢复.%Restoration of documents is a key step for applications in document processing, retrieval understanding as well as digital libraries, for example as in book readers. In this paper, we present a method to restore document images, by using a Maximum a Posteriori ( MAP) framework. The prior probability of the characters is learned from the training document images. The extraction of a single high-quality enhanced text image from a set of degraded images can benefit from a strong prior knowledge. The restoration process should allow for discontinuities and discourage oscillations at the same time. These properties were represented in a total variation based prior model. Results indicate that our method is appropriate for document image restoration, where resolution enhancement is an added gain.

  3. Millimeter wave image restoration based on fuzzy radial basis function neural networks and sparse representation%基于模糊径向基神经网络和稀疏表示的毫米波图像恢复

    Institute of Scientific and Technical Information of China (English)

    尚丽; 苏品刚; 陈杰

    2012-01-01

    As to the problems that Millimeter Wave ( MMW) image is contaminated by much unknown noise and has lower resolution, and considering the non-linear filter property of Fuzzy Radial Basis Function Neural Network ( F-RBFNN) and the self-adaptive denoising property of Sparse Representation (SR) based on K-Singular Value Decomposition (K-SVD), a MMW restoration method was proposed by combining F-RBFNN and sparse representation. In F-RBFNN, the knowledge expression of fuzzy logic and the reasoning ability were combined with the RBFNN's capabilities of fast learning and generalization. In order to realize the non-linear filtering to the MMW image, F-RBFNN's structure and parameters were adjusted according to the real problem. Furthermore, utilizing the advantages of sparse representation method, which the sparse representation behaves the visual characteristic and can denoise effectively when maintaining features of the object, the training results of F-RBFNN were locally denoised once again, and the MMW image with high resolution was obtained. Using the Relative Single Noise Ratio (RSNR) criterion to measure the quality of denoised images, the simulation results show that, compared with other denoising methods such as F-RBFNN, K-SVD denoising, and wavelet denoising, the proposed method combining F-RBFNN and SR can better restore the quality of MMW image.%针对毫米波(MMW)图像包含大量未知噪声、图像分辨率较低的问题,考虑模糊径向基函数神经网络(F-RBFNN)的非线性滤波特性和基于K-奇异值分解(K-SVD)稀疏表示(SR)的自适应消噪特性,提出了一种级联消噪的毫米波图像恢复方法.F-RBFNN将模糊逻辑的知识表达和推理能力与RBFNN的快速学习能力和泛化能力结合起来,可根据实际问题调整网络结构参数,对MMW图像达到非线性滤波的目的.进一步利用K-SVD稀疏表示具有人眼视觉特性,在保持目标特征的同时可有效消噪的优点,对FRBFNN的训练结果再

  4. Restoration of Throwing Soil Motion-Blurred Images%土粒流运动图像模糊退化的恢复

    Institute of Scientific and Technical Information of China (English)

    李伯全; 陈翠英

    2001-01-01

    It describes the motion-blurred images of back-throwing latent soil under up-cut rotary cultivation. Mathematics models of the process are set up and several methods of restoration of the motion-blurred images are discussed. According to the characteristics and causes of the motion-blurred images of back-throw soil, different restoration methods are adopted. In this paper, wienerfilter with optimal windows is used to set different areas of the images and to determine point spread function of each image. A quite satisfactory result is achieved. The study will reduce the difficulty and improve accuracy in the late image processing.%分析了潜土逆转旋耕被抛土粒流运动图像模糊退化机理,依据土粒流运动图像的特点,针对不同的退化机理分别采用了不同的恢复方法. 该文采用带最优窗的维纳滤波恢复方法,对土粒流运动模糊退化图像适当进行分区,确定了合适于各自图像区域的点扩展函数,获得了较为满意的恢复效果,为降低后续处理的难度和提高处理精度提供了可靠保证.

  5. Restoring proximal caries lesions conservatively with tunnel restorations

    Directory of Open Access Journals (Sweden)

    Chu CH

    2013-07-01

    Full Text Available Chun-Hung Chu1, May L Mei,1 Chloe Cheung,1 Romesh P Nalliah2 1Faculty of Dentistry, The University of Hong Kong, Hong Kong, People's Republic of China; 2Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA, USA Abstract: The tunnel restoration has been suggested as a conservative alternative to the conventional box preparation for treating proximal caries. The main advantage of tunnel restoration over the conventional box or slot preparation includes being more conservative and increasing tooth integrity and strength by preserving the marginal ridge. However, tunnel restoration is technique-sensitive and can be particularly challenging for inexperienced restorative dentists. Recent advances in technology, such as the contemporary design of dental handpieces with advanced light-emitting diode (LED and handheld comfort, offer operative dentists better vision, illumination, and maneuverability. The use of magnifying loupes also enhances the visibility of the preparation. The advent of digital radiographic imaging has improved dental imaging and reduced radiation. The new generation of restorative materials has improved mechanical properties. Tunnel restoration can be an option to restore proximal caries if the dentist performs proper case selection and pays attention to the details of the restorative procedures. This paper describes the clinical technique of tunnel restoration and reviews the studies of tunnel restorations. Keywords: operative, practice, tunnel preparation, composite, amalgam, glass ionomer

  6. Comparison Between Linear and Nonlinear Models of Mixed Pixels in Remote Sensing Satellite Images Based on Cierniewski Surface BRDF Model by Means of Monte Carlo Ray Tracing Simulation

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2013-04-01

    Full Text Available Comparative study on linear and nonlinear mixed pixel models of which pixels in remote sensing satellite images is composed with plural ground cover materials mixed together, is conducted for remote sensing satellite image analysis. The mixed pixel models are based on Cierniewski of ground surface reflectance model. The comparative study is conducted by using of Monte Carlo Ray Tracing: MCRT simulations. Through simulation study, the difference between linear and nonlinear mixed pixel models is clarified. Also it is found that the simulation model is validated.

  7. Combined nonlinear laser imaging (two-photon excitation fluorescence, second and third-harmonic generation, and fluorescence lifetime imaging microscopies) in ovarian tumors

    Science.gov (United States)

    Adur, J.; Pelegati, V. B.; de Thomaz, A. A.; Bottcher-Luiz, F.; Andrade, L. A. L. A.; Almeida, D. B.; Carvalho, H. F.; Cesar, C. L.

    2012-03-01

    We applied Two-photon Excited Fluorescence (TPEF), Second/Third Harmonic Generation (SHG and THG) and Fluorescence Lifetime Imaging (FLIM) Non Linear Optics (NLO) Laser-Scanning Microscopy within the same imaging platform to evaluate their use as a diagnostic tool in ovarian tumors. We assess of applicability of this multimodal approach to perform a pathological evaluation of serous and mucinous tumors in human samples. The combination of TPEF-SHG-THG imaging provided complementary information about the interface epithelium/stromal, such as the transformation of epithelium surface (THG) and the overall fibrillar tissue architecture (SHG). The fact that H&E staining is the standard method used in clinical pathology and that the stored samples are usually fixed makes it important a re-evaluation of these samples with NLO microscopy to compare new results with a library of already existing samples. FLIM, however, depends on the chemical environment around the fluorophors that was completely changed after fixation; therefore it only makes sense in unstained samples. Our FLIM results in unstained samples demonstrate that it is possible to discriminate healthy epithelia from serous or mucinous epithelia. Qualitative and quantitative analysis of the different imaging modalities used showed that multimodal nonlinear microscopy has the potential to differentiate between cancerous and healthy ovarian tissue.

  8. Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

    Energy Technology Data Exchange (ETDEWEB)

    Heasler, Patrick G.; Posse, Christian; Hylden, Jeff L.; Anderson, Kevin K.

    2007-06-13

    This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. This shows that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty.

  9. Low-frequency vibration modulation of guided waves to image nonlinear scatterers for structural health monitoring

    Science.gov (United States)

    Jiao, J. P.; Drinkwater, B. W.; Neild, S. A.; Wilcox, P. D.

    2009-06-01

    Guided wave structural health monitoring offers the prospect of continuous interrogation of large plate-like structures with a sparse network of permanently attached sensors. Currently, the most common approach is to monitor changes in the received signals by subtraction from a reference signal obtained when the structure was known to be defect-free. In this paper a comparison is made between this defect-free subtraction approach and a technique in which low-frequency vibration modulation of guided wave signals is used to detect nonlinear scatterers. The modulation technique potentially overcomes the need for the defect-free reference measurement as the subtraction is now made between different parts of an externally applied low-frequency vibration. Linear defects were simulated by masses bonded onto a plate and nonlinear scatterers were simulated by loading a similar mass against the plate. The experimental results show that the defect-free subtraction technique performs well in detecting the bonded mass whereas the modulation technique is able to discriminate between the bonded and loaded masses. Furthermore, because the modulation technique does not require a defect-free reference, it is shown to be relatively independent of temperature effects, a significant problem for reference based subtraction techniques.

  10. Single shot trajectory design for region-specific imaging using linear and nonlinear magnetic encoding fields.

    Science.gov (United States)

    Layton, Kelvin J; Gallichan, Daniel; Testud, Frederik; Cocosco, Chris A; Welz, Anna M; Barmet, Christoph; Pruessmann, Klaas P; Hennig, Jürgen; Zaitsev, Maxim

    2013-09-01

    It has recently been demonstrated that nonlinear encoding fields result in a spatially varying resolution. This work develops an automated procedure to design single-shot trajectories that create a local resolution improvement in a region of interest. The technique is based on the design of optimized local k-space trajectories and can be applied to arbitrary hardware configurations that employ any number of linear and nonlinear encoding fields. The trajectories designed in this work are tested with the currently available hardware setup consisting of three standard linear gradients and two quadrupolar encoding fields generated from a custom-built gradient insert. A field camera is used to measure the actual encoding trajectories up to third-order terms, enabling accurate reconstructions of these demanding single-shot trajectories, although the eddy current and concomitant field terms of the gradient insert have not been completely characterized. The local resolution improvement is demonstrated in phantom and in vivo experiments. Copyright © 2012 Wiley Periodicals, Inc.

  11. Non-linear quantization for arbitrary distributions and applications to Medical Image Processing

    CERN Document Server

    Tannous, C

    2002-01-01

    We report the development of a scalar quantization approach that helps build tables of decision and reconstruction levels for any probability density function (pdf). Several example pdf's are used for illustration: Uniform, Gaussian, Laplace, one-sided Rayleigh, and Gamma (One sided and double-sided symmetrical). The main applications of the methodology are principally aimed at Multiresolution Image compression where generally the Stretched Exponential pdf is encountered. Specialising to this important case, we perform quantization and information entropy calculations from selected medical MRI (Magnetic Resonance Imaging) pictures of the human brain. The image histograms are fitted to a Stretched exponential model and the corresponding entropies are compared.

  12. Nonlinear Structure-Aware Image Sharpening with Difference of Smoothing Operators

    Directory of Open Access Journals (Sweden)

    Amin eKheradmand

    2015-10-01

    Full Text Available In this paper, we propose an effective data-adaptive filtering mechanism for sharpening of noisy and moderately blurred images. We establish the connection of our proposed data-adaptive filtering procedure with the classic Difference of Gaussians (DoG operator widely used in image processing and computer graphics. Our proposed filter renders a data-adaptive and noise robust version of the classical DoG filter. We also discuss interesting special cases of our general sharpening method. Experimental results verify the effectiveness of the proposed technique for sharpening real images.

  13. Signal restoration method for restraining the range walk error of Geiger-mode avalanche photodiode lidar in acquiring a merged three-dimensional image.

    Science.gov (United States)

    Xu, Lu; Zhang, Yu; Zhang, Yong; Wu, Long; Yang, Chenghua; Yang, Xu; Zhang, Zijing; Zhao, Yuan

    2017-04-10

    The fluctuation in the number of signal photoelectrons will cause a range walk error in a Geiger-mode avalanche photodiode (Gm-APD) lidar, which significantly depends on the target intensity. For a nanosecond-pulsed laser, the range walk error of traditional time-of-flight will cause deterioration. A new signal restoration method, based on the Poisson probability response model and the center-of-mass algorithm, is proposed to restrain the range walk error. We obtain a high-precision depth and intensity merged 3D image using this method. The range accuracy is 0.6 cm, and the intensity error is less than 3%.

  14. Inspection of copper canisters for spent nuclear fuel by means of ultrasound. Phased arrays, ultrasonic imaging and nonlinear acoustics

    Energy Technology Data Exchange (ETDEWEB)

    Stepinski, Tadeusz (ed.); Ping Wu; Wennerstroem, Erik [Uppsala Univ. (Sweden). Signals and Systems

    2004-09-01

    This report contains the research results concerning advanced ultrasound for the inspection of copper canisters for spent nuclear fuel obtained at Signals and Systems, Uppsala University in years 2003/2004. After a short introduction a review of beam forming fundamentals required for proper understanding phased array operation is included. The factors that determine lateral resolution during ultrasonic imaging of flaws in solids are analyzed and results of simulations modelling contact inspection of copper are presented. In the second chapter an improved synthetic aperture imaging (SAI) technique is introduced. The proposed SAI technique is characterized by an enhanced lateral resolution compared with the previously proposed extended synthetic aperture focusing technique (ESAFT). The enhancement of imaging performance is achieved due to more realistic assumption concerning the probability density function of scatterers in the region of interest. The proposed technique takes the form of a two-step algorithm using the result obtained in the first step as a prior for the second step. Final chapter contains summary of our recent experimental and theoretical research on nonlinear ultrasonics of unbounded interfaces. A new theoretical model for rough interfaces is developed, and the experimental results from the copper specimens that mimic contact cracks of different types are presented. Derivation of the theory and selected measurement results are given in appendix.

  15. Simultaneous nonlinear encryption of grayscale and color images based on phase-truncated fractional Fourier transform and optical superposition principle.

    Science.gov (United States)

    Wang, Xiaogang; Zhao, Daomu

    2013-09-01

    A nonlinear color and grayscale images cryptosystem based on phase-truncated fractional Fourier transform and optical superposition principle is proposed. In order to realize simultaneous encryption of color and grayscale images, each grayscale image is first converted into two phase masks by using an optical coherent superposition, one of which is treated as a part of input information that will be fractional Fourier transformed while the other in the form of a chaotic random phase mask (CRPM) is used as a decryption key. For the purpose of optical performance, all the processes are performed through three channels, i.e., red, green, and blue. Different from most asymmetric encryption methods, the decryption process is designed to be linear for the sake of effective decryption. The encryption level of a double random phase encryption based on phase-truncated Fourier transform is enhanced by extending it into fractional Fourier domain and the load of the keys management and transmission is lightened by using CRPMs. The security of the proposed cryptosystem is discussed and computer simulation results are presented to verify the validity of the proposed method.

  16. A MODIFIED NONLINEAR DIFFUSION MODEL AND ITS APPLICATION TO IMAGE SMOOTHING AND EDGE DETECTION

    Institute of Scientific and Technical Information of China (English)

    Xu Deliang; Wang Yaguang; Zhou Chuqin; Shen Haiping

    2001-01-01

    A modified version of the Cotte, Lions, Morel and Coil theory for image selective smoothing and edge detection is proposed. Comparing with their model, the most important advantage of this modification is that the convolution with Gaussian processes in the filtering process is replaced by solving an initial-boundary value problem for the heat equation, which simplifies the numerical scheme to some extent. Numerical experiments on natural images are presented for this model.

  17. Focal-Plane Imaging of Crossed Beams in Nonlinear Optics Experiments

    Science.gov (United States)

    Bivolaru, Daniel; Herring, G. C.

    2007-01-01

    An application of focal-plane imaging that can be used as a real time diagnostic of beam crossing in various optical techniques is reported. We discuss two specific versions and demonstrate the capability of maximizing system performance with an example in a combined dual-pump coherent anti-Stokes Raman scattering interferometric Rayleigh scattering experiment (CARS-IRS). We find that this imaging diagnostic significantly reduces beam alignment time and loss of CARS-IRS signals due to inadvertent misalignments.

  18. Spectrally resolved cathodoluminescence imaging study of periodic [001]/[00-1] GaAs structures for nonlinear optical conversion

    Energy Technology Data Exchange (ETDEWEB)

    Hortelano, V.; Martinez, O.; Jimenez, J. [GdS Optronlab., Univ. de Valladolid, Paseo de Belen 1, 47011 Valladolid (Spain); Lynch, C.; Snure, M.; Bliss, D. [Air Force Research Laboratory, Sensors Directorate, Hanscom AFB, MA 01731 (United States)

    2012-07-15

    Orientation patterned (OP)-GaAs crystals are very promising as nonlinear optical materials. They are suitable for mid-infrared and terahertz laser sources, by frequency conversion of shorter wavelength pump sources. OP-GaAs crystals must contain low concentrations of defects and must be homogeneous to reduce fluctuations, in the refractive index and the concomitant optical propagation losses. Understanding of the defects with electrooptic signature is crucial to improve the growth conditions for reducing their presence. Spectrally resolved cathodoluminescence imaging is used to study the main defects and how they are distributed throughout the OP-GaAs crystal (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  19. New algorithm to determine true colocalization in combination with image restoration and time-lapse confocal microscopy to MAP kinases in mitochondria.

    Directory of Open Access Journals (Sweden)

    Jorge Ignacio Villalta

    Full Text Available The subcellular localization and physiological functions of biomolecules are closely related and thus it is crucial to precisely determine the distribution of different molecules inside the intracellular structures. This is frequently accomplished by fluorescence microscopy with well-characterized markers and posterior evaluation of the signal colocalization. Rigorous study of colocalization requires statistical analysis of the data, albeit yet no single technique has been established as a standard method. Indeed, the few methods currently available are only accurate in images with particular characteristics. Here, we introduce a new algorithm to automatically obtain the true colocalization between images that is suitable for a wide variety of biological situations. To proceed, the algorithm contemplates the individual contribution of each pixel's fluorescence intensity in a pair of images to the overall Pearsońs correlation and Manders' overlap coefficients. The accuracy and reliability of the algorithm was validated on both simulated and real images that reflected the characteristics of a range of biological samples. We used this algorithm in combination with image restoration by deconvolution and time-lapse confocal microscopy to address the localization of MEK1 in the mitochondria of different cell lines. Appraising the previously described behavior of Akt1 corroborated the reliability of the combined use of these techniques. Together, the present work provides a novel statistical approach to accurately and reliably determine the colocalization in a variety of biological images.

  20. 结合局部与非局部的图像复原方法%Combining local and nonlocal method for image restoration

    Institute of Scientific and Technical Information of China (English)

    李俊英; 肖升

    2015-01-01

    In order to recover the details better, this paper proposed a new image restoration method, which combined the lo-cal total variation (LTV) and the nonlocal total variation (NLTV) models.First, it extracted the details accurately from the image.Then, the method applied the NLTV model only on the details, and applied the LTV model only on the residual image components.The proposed method, which used the advantages of both the LTV and NLTV models, could recover the image details better.A large number of experimental results indicate that the proposed method outperforms several recent image resto-ration methods, not only the subjective vision has the betterment obviously, but also the PSNR improves between 0.11 dB and 2.28 dB.%为了更好地复原图像的细节,提出了一种结合局部与非局部的图像复原方法。将图像中的细节准确地提取出来,对提取的细节进行非局部全变差约束,同时对剩下的图像成分进行局部全变差约束。提出的方法很好地结合了非局部全变差和局部全变差的优点,实现了图像细节更好的复原。实验结果表明,提出的方法与近几年的一些较好的图像复原方法相比,不仅主观的视觉效果得到了明显的改进,而且客观的峰值信噪比也增加了0.11~2.28 dB。

  1. Facing "the Curse of Dimensionality": Image Fusion and Nonlinear Dimensionality Reduction for Advanced Data Mining and Visualization of Astronomical Images

    Science.gov (United States)

    Pesenson, Meyer; Pesenson, I. Z.; McCollum, B.

    2009-05-01

    The complexity of multitemporal/multispectral astronomical data sets together with the approaching petascale of such datasets and large astronomical surveys require automated or semi-automated methods for knowledge discovery. Traditional statistical methods of analysis may break down not only because of the amount of data, but mostly because of the increase of the dimensionality of data. Image fusion (combining information from multiple sensors in order to create a composite enhanced image) and dimension reduction (finding lower-dimensional representation of high-dimensional data) are effective approaches to "the curse of dimensionality,” thus facilitating automated feature selection, classification and data segmentation. Dimension reduction methods greatly increase computational efficiency of machine learning algorithms, improve statistical inference and together with image fusion enable effective scientific visualization (as opposed to mere illustrative visualization). The main approach of this work utilizes recent advances in multidimensional image processing, as well as representation of essential structure of a data set in terms of its fundamental eigenfunctions, which are used as an orthonormal basis for the data visualization and analysis. We consider multidimensional data sets and images as manifolds or combinatorial graphs and construct variational splines that minimize certain Sobolev norms. These splines allow us to reconstruct the eigenfunctions of the combinatorial Laplace operator by using only a small portion of the graph. We use the first two or three eigenfunctions for embedding large data sets into two- or three-dimensional Euclidean space. Such reduced data sets allow efficient data organization, retrieval, analysis and visualization. We demonstrate applications of the algorithms to test cases from the Spitzer Space Telescope. This work was carried out with funding from the National Geospatial-Intelligence Agency University Research Initiative

  2. Nonlinear ultrasonic imaging method for closed cracks using subtraction of responses at different external loads.

    Science.gov (United States)

    Ohara, Yoshikazu; Horinouchi, Satoshi; Hashimoto, Makoto; Shintaku, Yohei; Yamanaka, Kazushi

    2011-08-01

    To improve the selectivity of closed cracks for objects other than cracks in ultrasonic imaging, we propose an extension of a novel imaging method, namely, subharmonic phased array for crack evaluation (SPACE) as well as another approach using the subtraction of responses at different external loads. By applying external static or dynamic loads to closed cracks, the contact state in the cracks varies, resulting in an intensity change of responses at cracks. In contrast, objects other than cracks are independent of external load. Therefore, only cracks can be extracted by subtracting responses at different loads. In this study, we performed fundamental experiments on a closed fatigue crack formed in an aluminum alloy compact tension (CT) specimen using the proposed method. We examined the static load dependence of SPACE images and the dynamic load dependence of linear phased array (PA) images by simulating the external loads with a servohydraulic fatigue testing machine. By subtracting the images at different external loads, we show that this method is useful in extracting only the intensity change of responses related to closed cracks, while canceling the responses of objects other than cracks.

  3. Non-linear optical imaging and fibre-based spectroscopy of fresh colon biopsies

    Science.gov (United States)

    Cicchi, R.; Sturiale, A.; Nesi, G.; Kapsokalyvas, D.; Tonelli, F.; Pavone, F. S.

    2012-06-01

    Two-photon fluorescence (TPEF) microscopy is a powerful tool to image human tissues up to 200 microns depth without any exogenously added probe. TPEF can take advantage of the autofluorescence of molecules intrinsically contained in a biological tissue, as such NADH, elastin, collagen, and flavins. Two-photon microscopy has been already successfully used to image several types of tissues, including skin, muscles, tendons, bladder. Nevertheless, its usefulness in imaging colon tissue has not been deeply investigated yet. In this work we have used combined two-photon excited fluorescence (TPEF), second harmonic generation microscopy (SHG), fluorescence lifetime imaging microscopy (FLIM), and multispectral two-photon emission detection (MTPE) to investigate different kinds of human ex-vivo fresh biopsies of colon. Morphological and spectroscopic analyses allowed to characterize both healthy mucosa, polyp, and colon samples in a good agreement with common routine histology. Even if further analysis, as well as a more significant statistics on a large number of samples would be helpful to discriminate between low, mild, and high grade cancer, our method is a promising tool to be used as diagnostic confirmation of histological results, as well as a diagnostic tool in a multiphoton endoscope or colonoscope to be used in in-vivo imaging applications.

  4. Voice restoration

    NARCIS (Netherlands)

    Hilgers, F.J.M.; Balm, A.J.M.; van den Brekel, M.W.M.; Tan, I.B.; Remacle, M.; Eckel, H.E.

    2010-01-01

    Surgical prosthetic voice restoration is the best possible option for patients to regain oral communication after total laryngectomy. It is considered to be the present "gold standard" for voice rehabilitation of laryngectomized individuals. Surgical prosthetic voice restoration, in essence, is alwa

  5. Nonlinear ultrasonic phased array imaging of closed cracks using global preheating and local cooling

    Science.gov (United States)

    Ohara, Yoshikazu; Takahashi, Koji; Ino, Yoshihiro; Yamanaka, Kazushi

    2015-10-01

    Closed cracks are the main cause of underestimation in ultrasonic inspection, because the ultrasound transmits through the crack. Specifically, the measurement of closed-crack depth in coarse-grained materials, which are highly attenuative due to linear scatterings at the grains, is the most difficult issue. To solve this problem, we have developed a temporary crack opening method, global preheating and local cooling (GPLC), using tensile thermal stress, and a high-selectivity imaging method, load difference phased array (LDPA), based on the subtraction of phased array images between different stresses. To demonstrate our developed method, we formed a closed fatigue crack in coarse-grained stainless steel (SUS316L) specimen. As a result of applying it to the specimen, the high-selectivity imaging performance was successfully demonstrated. This will be useful in improving the measurement accuracy of closed-crack depths in coarse-grained material.

  6. The Nonlinear Statistics of High-contrast Patches in Natural Images

    DEFF Research Database (Denmark)

    Lee, Ann; Pedersen, Kim Steenstrup; Mumford, David

    2003-01-01

    of natural images, not just marginals, and the need to understand the intrinsic dimensionality and nature of the data. We believe that object-like structures in the world and the sensor properties of the probing device generate observations that are concentrated along predictable shapes in state space. Our......Recently, there has been a great deal of interest in modeling the non-Gaussian structures of natural images. However, despite the many advances in the direction of sparse coding and multi-resolution analysis, the full probability distribution of pixel values in a neighborhood has not yet been...... study of natural image statistics accounts for local geometries (such as edges) in natural scenes, but does not impose such strong assumptions on the data as independent components or sparse coding by linear change of bases....

  7. Nonlinear research of an image motion stabilization system embedded in a space land-survey telescope

    Science.gov (United States)

    Somov, Yevgeny; Butyrin, Sergey; Siguerdidjane, Houria

    2017-01-01

    We consider an image motion stabilization system embedded into a space telescope for a scanning optoelectronic observation of terrestrial targets. Developed model of this system is presented taking into account physical hysteresis of piezo-ceramic driver and a time delay at a forming of digital control. We have presented elaborated algorithms for discrete filtering and digital control, obtained results on analysis of the image motion velocity oscillations in the telescope focal plane, and also methods for terrestrial and in-flight verification of the system.

  8. 变分框架下的多尺度图像恢复与重建%Multiscale Image Restoration and Reconstruction in the Framework of Variation

    Institute of Scientific and Technical Information of China (English)

    唐利明; 黄大荣

    2013-01-01

    变分图像分解,通过极小化能量泛函将图像分解为不同的特征分量,可以被应用到图像的恢复和重建。提出了变分框架下的多尺度图像恢复和重建的思想。基于这种思想,首先提出了一个单参数的(BV ,G ,E )三元变分分解模型,并且理论分析了参数与不同特征分量的尺度的关系。然后将此模型的参数选为一个二进制序列,得到多尺度的(BV ,G ,E )变分分解。该多尺度变分分解可以将图像分解为一序列图像结构、纹理和噪声。证明了此多尺度分解的收敛性并且基于对偶理论和交替迭代算法给出了其数值求解方法。最后将提出的多尺度的(BV ,G ,E )变分分解应用到图像恢复和重建,实验结果证实了理论分析的正确性,显示了将此模型进行图像多尺度恢复和重建的有效性,和与一些其他分解模型相比较的优越性。%By minimizing the energy functional ,we can obtain the variational image decomposition which decomposes image into different characteristic components ,and can be used for image restoration and reconstruction .An idea of multiscale image restoration and reconstruction in the framework of variation is proposed .Based on this idea ,firstly ,a single-parameter (BV ,G ,E ) trituple decomposition model is proposed ,and the relationship between the parameter and the scale of each component is studied the-oretically .And then ,by replacing the parameter with a binary sequence ,we achieve a multiscale (BV ,G ,E) decomposition which can decompose an image into a sequence of image structure ,texture and noise .The convergence of this multiscale decomposition is proved ,and an efficient numerical method based on the duality theory and alternate iteration algorithm is introduced to solve it .At last ,the proposed multiscale (BV ,G ,E ) decomposition is applied for image restoration and reconstruction .Numerical results sup-port the

  9. A deep learning approach to estimate chemically-treated collagenous tissue nonlinear anisotropic stress-strain responses from microscopy images.

    Science.gov (United States)

    Liang, Liang; Liu, Minliang; Sun, Wei

    2017-09-20

    Biological collagenous tissues comprised of networks of collagen fibers are suitable for a broad spectrum of medical applications owing to their attractive mechanical properties. In this study, we developed a noninvasive approach to estimate collagenous tissue elastic properties directly from microscopy images using Machine Learning (ML) techniques. Glutaraldehyde-treated bovine pericardium (GLBP) tissue, widely used in the fabrication of bioprosthetic heart valves and vascular patches, was chosen to develop a representative application. A Deep Learning model was designed and trained to process second harmonic generation (SHG) images of collagen networks in GLBP tissue samples, and directly predict the tissue elastic mechanical properties. The trained model is capable of identifying the overall tissue stiffness with a classification accuracy of 84%, and predicting the nonlinear anisotropic stress-strain curves with average regression errors of 0.021 and 0.031. Thus, this study demonstrates the feasibility and great potential of using the Deep Learning approach for fast and noninvasive assessment of collagenous tissue elastic properties from microstructural images. In this study, we developed, to our best knowledge, the first Deep Learning-based approach to estimate the elastic properties of collagenous tissues directly from noninvasive second harmonic generation images. The success of this study holds promise for the use of Machine Learning techniques to noninvasively and efficiently estimate the mechanical properties of many structure-based biological materials, and it also enables many potential applications such as serving as a quality control tool to select tissue for the manufacturing of medical devices (e.g. bioprosthetic heart valves). Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  10. Multimodal optical setup for nonlinear and fluorescence lifetime imaging microscopies: improvement on a commercial confocal inverted microscope

    Science.gov (United States)

    Pelegati, V. B.; Adur, J.; de Thomaz, A. A.; Almeida, D. B.; Baratti, M. O.; Carvalho, H. F.; Cesar, C. L.

    2012-03-01

    In this work we proposed and built a multimodal optical setup that extends a commercially available confocal microscope (Olympus FV300) to include nonlinear optical (NLO) microscopy and fluorescence lifetime imaging microscopy (FLIM). The NLO microscopies included two-photon fluorescence (TPFE), Second Harmonic Generation (SHG) and Third Harmonic Generation (THG). The whole system, including FLIM, used only one laser source composed of an 80 MHz femtosecond laser. The commercial Ti:sapphire lasers can be tuned up to 690-1040 nm bringing the THG signal to the 350 nm region where most microscope optics do not work. However, the third harmonic is only generated at the sample, meaning that we only have to take care of the collection optics. To do that we used a remote photomultiplier to acquire the THG signal at the 310-350 nm wavelength window. After performing the tests to guarantee that we are observing actually SHG/THG signals we than used this system to acquire multimodal images of several biological samples, from epithelial cancer to vegetables. The ability to see the collagen network together with the cell nuclei proved to be important for cancer tissues diagnosis. Moreover, FLIM provides information about the cell metabolism, also very important for cancer cell processes.

  11. Nonlinear imaging techniques for the observation of cell membrane perturbation due to pulsed electric field exposure

    Science.gov (United States)

    Moen, Erick K.; Beier, Hope T.; Thompson, Gary L.; Roth, Caleb C.; Ibey, Bennett L.

    2014-03-01

    Nonlinear optical probes, especially those involving second harmonic generation (SHG), have proven useful as sensors for near-instantaneous detection of alterations to orientation or energetics within a substance. This has been exploited to some success for observing conformational changes in proteins. SHG probes, therefore, hold promise for reporting rapid and minute changes in lipid membranes. In this report, one of these probes is employed in this regard, using nanosecond electric pulses (nsEPs) as a vehicle for instigating subtle membrane perturbations. The result provides a useful tool and methodology for the observation of minute membrane perturbation, while also providing meaningful information on the phenomenon of electropermeabilization due to nsEP. The SHG probe Di- 4-ANEPPDHQ is used in conjunction with a tuned optical setup to demonstrate nanoporation preferential to one hemisphere, or pole, of the cell given a single square shaped pulse. The results also confirm a correlation of pulse width to the amount of poration. Furthermore, the polarity of this event and the membrane physics of both hemispheres, the poles facing either electrode, were tested using bipolar pulses consisting of two pulses of opposite polarity. The experiment corroborates findings by other researchers that these types of pulses are less effective in causing repairable damage to the lipid membrane of cells.

  12. A fast nonlinear regression method for estimating permeability in CT perfusion imaging.

    Science.gov (United States)

    Bennink, Edwin; Riordan, Alan J; Horsch, Alexander D; Dankbaar, Jan Willem; Velthuis, Birgitta K; de Jong, Hugo W

    2013-11-01

    Blood-brain barrier damage, which can be quantified by measuring vascular permeability, is a potential predictor for hemorrhagic transformation in acute ischemic stroke. Permeability is commonly estimated by applying Patlak analysis to computed tomography (CT) perfusion data, but this method lacks precision. Applying more elaborate kinetic models by means of nonlinear regression (NLR) may improve precision, but is more time consuming and therefore less appropriate in an acute stroke setting. We propose a simplified NLR method that may be faster and still precise enough for clinical use. The aim of this study is to evaluate the reliability of in total 12 variations of Patlak analysis and NLR methods, including the simplified NLR method. Confidence intervals for the permeability estimates were evaluated using simulated CT attenuation-time curves with realistic noise, and clinical data from 20 patients. Although fixating the blood volume improved Patlak analysis, the NLR methods yielded significantly more reliable estimates, but took up to 12 × longer to calculate. The simplified NLR method was ∼4 × faster than other NLR methods, while maintaining the same confidence intervals (CIs). In conclusion, the simplified NLR method is a new, reliable way to estimate permeability in stroke, fast enough for clinical application in an acute stroke setting.

  13. Pulse splitter-based nonlinear microscopy for live-cardiomyocyte imaging

    OpenAIRE

    Wang, Zhonghai; Qin, Wan; Shao, Yonghong; Ma, Siyu; Borg, Thomas K.; GAO, BRUCE Z.

    2014-01-01

    Second harmonic generation (SHG) microscopy is a new imaging technique used in sarcomeric-addition studies. However, during the early stage of cell culture in which sarcomeric additions occur, the neonatal cardiomyocytes that we have been working with are very sensitive to photodamage, the resulting high rate of cell death prevents systematic study of sarcomeric addition using a conventional SHG system. To address this challenge, we introduced use of the pulse-splitter system developed by Na ...

  14. MULTIPLE REFLECTION EFFECTS IN NONLINEAR MIXTURE MODEL FOR HYPERSPECTRAL IMAGE ANALYSIS

    OpenAIRE

    Liu, C. Y.; Ren, H.

    2016-01-01

    Hyperspectral spectrometers can record electromagnetic energy with hundreds or thousands of spectral channels. With such high spectral resolution, the spectral information has better capability for material identification. Because of the spatial resolution, one pixel in hyperspectral images usually covers several meters, and it may contain more than one material. Therefore, the mixture model must be considered. Linear mixture model (LMM) has been widely used for remote sensing target...

  15. Integrated nonlinear optical imaging microscope for on-axis crystal detection and centering at a synchrotron beamline

    Energy Technology Data Exchange (ETDEWEB)

    Madden, Jeremy T.; Toth, Scott J.; Dettmar, Christopher M.; Newman, Justin A.; Oglesbee, Robert A.; Hedderich, Hartmut G.; Everly, R. Michael [Purdue University, 560 Oval Drive, West Lafayette, IN 47906 (United States); Becker, Michael [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439 (United States); Ronau, Judith A. [Purdue University, 560 Oval Drive, West Lafayette, IN 47906 (United States); Buchanan, Susan K. [National Institutes of Health, Building 50, Room 4503, 50 South Drive, Bethesda, MD 20814 (United States); Cherezov, Vadim [The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 (United States); Morrow, Marie E. [Purdue University, 560 Oval Drive, West Lafayette, IN 47906 (United States); Xu, Shenglan; Ferguson, Dale; Makarov, Oleg [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439 (United States); Das, Chittaranjan [Purdue University, 560 Oval Drive, West Lafayette, IN 47906 (United States); Fischetti, Robert [Advanced Photon Source, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439 (United States); Simpson, Garth J., E-mail: gsimpson@purdue.edu [Purdue University, 560 Oval Drive, West Lafayette, IN 47906 (United States)

    2013-07-01

    Nonlinear optical (NLO) instrumentation has been integrated with synchrotron X-ray diffraction for combined single-platform analysis, examining the viability of NLO microscopy as an alternative to the conventional X-ray raster scan for the purposes of sample centering. Second-harmonic generation microscopy and two-photon excited ultraviolet fluorescence microscopy were evaluated for crystal detection, and assessed by X-ray raster scanning. Nonlinear optical (NLO) instrumentation has been integrated with synchrotron X-ray diffraction (XRD) for combined single-platform analysis, initially targeting applications for automated crystal centering. Second-harmonic-generation microscopy and two-photon-excited ultraviolet fluorescence microscopy were evaluated for crystal detection and assessed by X-ray raster scanning. Two optical designs were constructed and characterized; one positioned downstream of the sample and one integrated into the upstream optical path of the diffractometer. Both instruments enabled protein crystal identification with integration times between 80 and 150 µs per pixel, representing a ∼10{sup 3}–10{sup 4}-fold reduction in the per-pixel exposure time relative to X-ray raster scanning. Quantitative centering and analysis of phenylalanine hydroxylase from Chromobacterium violaceum cPAH, Trichinella spiralis deubiquitinating enzyme TsUCH37, human κ-opioid receptor complex kOR-T4L produced in lipidic cubic phase (LCP), intimin prepared in LCP, and α-cellulose samples were performed by collecting multiple NLO images. The crystalline samples were characterized by single-crystal diffraction patterns, while α-cellulose was characterized by fiber diffraction. Good agreement was observed between the sample positions identified by NLO and XRD raster measurements for all samples studied.

  16. Restoring forests

    DEFF Research Database (Denmark)

    Jacobs, Douglass F.; Oliet, Juan A.; Aronson, James

    2015-01-01

    of land requiring restoration implies the need for spatial prioritization of restoration efforts according to cost-benefit analyses that include ecological risks. To design resistant and resilient ecosystems that can adapt to emerging circumstances, an adaptive management approach is needed. Global change......, in particular, imparts a high degree of uncertainty about the future ecological and societal conditions of forest ecosystems to be restored, as well as their desired goods and services. We must also reconsider the suite of species incorporated into restoration with the aim of moving toward more stress resistant...... and competitive combinations in the longer term. Non-native species may serve an important role under some circumstances, e.g., to facilitate reintroduction of native species. Propagation and field establishment techniques must promote survival through seedling stress resistance and site preparation. An improved...

  17. Simultaneous observation of collagen and elastin based on the combined nonlinear optical imaging technique coupled with two-channel synchronized detection method

    Science.gov (United States)

    Chen, Jianxin; Zhuo, Shuangmu; Luo, Tianshu; Liu, Dingzhong; Zhao, Jingjun

    2008-08-01

    Collagen and elastin are the most important proteins of the connective tissues in higher vertebrates. In this paper, we present a combined nonlinear optical imaging technique of second-harmonic generation and two-photon excited fluorescence to simultaneously observe the collagen and elastic fiber of dermis in a freshly excised human skin and rabbit aorta using a two-channel synchronized detection method. The obtained two-channel overlay image in the backward direction can clearly distinguish the morphological structure and distribution of collagen and elastic fibers. Tissue spectrum further confirms the obtained structural information. These results suggest that the combined nonlinear optical imaging technique coupled with two-channel synchronized detection method can be an effective tool for detecting collage and elastic fibers without any invasive tissue procedure of slicing, embedding, fixation and staining when two structural proteins are simultaneously present in the biological tissue.

  18. Restoration of dichromatic images gained from CCD/CMOS camera by iterative detection networks with fragmented marginalization at the symbol block level

    Science.gov (United States)

    Kekrt, Daniel; Klíma, Miloš; Fliegel, Karel

    2009-08-01

    Image capturing by CCD/CMOS cameras is encumbered with two fundamental perturbing influences. Time invariant blurring (image convolution with fixed kernel) and time variant noises. Both of these influences can be successfully eliminated by the iterative detection networks (IDNs), that effectively and suboptimally (iteratively) solve 2D MAP criterion through the image decomposition to the small areas. Preferably to the individual pixel level, if this allows the noise distribution (statistically independent noise). Nevertheless, this task is so extremely numerically exacting and therefore the contemporary IDNs are limited only for restorations of dichromatic images. The IDNs are composed of certain, as simple as possible, statistical devices (SISO modules) and can be separated into two basic groups with variable topology (exactly matched to the blurring kernel) and with fixed topology, same for all possible kernels. The paper deals with second group of IDNs, concretely with IDNs whose SISO modules are concatenated in three directions (horizontal, vertical and diagonal). Advantages of such ordering rests in the application flexibility (can be comfortable applied to many irregular cores) and also in the low exigencies to number of memory devices it the IDN. The mentioned IDN type will be implemented in the two different variants suppressing defocusing in the lens of CCD/CMOS sensing system and will be verified in the sphere of a dichromatic 2D barcode detection.

  19. 无源毫米波成像改进POCS超分辨率算法%Passive Millimeter-Wave Image Restoration Based on Improved POCS Algorithm

    Institute of Scientific and Technical Information of China (English)

    赵康; 王建国

    2011-01-01

    The problem of poor resolution of acquired image in the passive millimeter wave imaging stems mainly from antenna size limitations. Thus efficient post-processing is necessary to achieve resolution improvements. The algorithm combines the advantages of Wiener filter restoration algorithm and POCS algorithm based on convex set theoretic. The Wiener filter is employed to restore the pass-band spectrum, and the POCS algorithm is applied to complete spectral extrapolation as the main iterative process to ensure that low-frequency component is not destroyed as spectral extrapolating. Experimental results demonstrate the algorithm improves the convergent rate and is computationally much more efficient than POCS algorithm. The algorithm is easily implemented in real time for passive millimeter wave imaging.%在无源毫米波成像中,因为受天线孔径大小的限制而导致获取的图像分辨率低,所以必须采取有效后处理措施增强分辨率.提出了一种改进的POCS超分辨率算法,该算法结合了Wiener滤波器复原算法和凸集投影(POCS)算法的优点,使用Wiener滤波复原算法恢复图像通带内的低频分量,运用POCS算法作为主迭代过程实现频谱外推,同时保证低频分量不被破坏.实验结果表明,该算法增强了图像的分辨率,改善了收敛速度,减少了计算量,有利于无源毫米波成像超分辨率的实时实现.

  20. 自适应非局部patch正则化图像恢复%Adaptive Nonlocal Patch Regularization for Image Restoration

    Institute of Scientific and Technical Information of China (English)

    刘红毅; 韦志辉; 张峥嵘

    2012-01-01

    Nonlocal means exploits the spatial correlation in an image, and preserves the structure information effectively. Combining the nonlocal patch regularization with TV regularization, we propose a nonlocal patch regularized image restoration model.The improved structure tensor matrix can be used to achieve a data-adaptive weigh function, which can then adjust the similarity match process based on the local structure of a pixel. A more simple and effective algorithm -Split Bregman, is used to solve the model iteratively. Compared with other regularization models, our method performs better in improving the quality of restoration image and the efficiency of the algorithm.%非局部均值利用图像自相似性,有效保持了图像的几何结构信息.提出了非局部patch正则和TV正则结合的图像恢复模型,利用改进的结构张量矩阵构造自适应非局部权函数,根据像素的局部结构计算图像中patch的相似性,提高了图像结构信息的保持性能.在数值解法上,采用分裂Bregman算法迭代求解模型,得到简单快速的迭代形式.数值实验证明所提出方法在提高恢复图像质量和算法效率上都有显著改进.