Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

Science.gov (United States)

Ren, Zhong; Liu, Guodong; Huang, Zhen

2012-11-01

The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

Passive ranging using a filter-based non-imaging method based on oxygen absorption.

Science.gov (United States)

Yu, Hao; Liu, Bingqi; Yan, Zongqun; Zhang, Yu

2017-10-01

To solve the problem of poor real-time measurement caused by a hyperspectral imaging system and to simplify the design in passive ranging technology based on oxygen absorption spectrum, a filter-based non-imaging ranging method is proposed. In this method, three bandpass filters are used to obtain the source radiation intensities that are located in the oxygen absorption band near 762 nm and the band's left and right non-absorption shoulders, and a photomultiplier tube is used as the non-imaging sensor of the passive ranging system. Range is estimated by comparing the calculated values of band-average transmission due to oxygen absorption, τ O 2 , against the predicted curve of τ O 2 versus range. The method is tested under short-range conditions. Accuracy of 6.5% is achieved with the designed experimental ranging system at the range of 400 m.

Color image guided depth image super resolution using fusion filter

Science.gov (United States)

He, Jin; Liang, Bin; He, Ying; Yang, Jun

2018-04-01

Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter

Directory of Open Access Journals (Sweden)

Qingjiao Sun

2016-01-01

Full Text Available Pathological image enhancement is a significant topic in the field of pathological image processing. This paper proposes a high dynamic range (HDR pathological image enhancement method based on improved bias field correction and guided image filter (GIF. Firstly, a preprocessing including stain normalization and wavelet denoising is performed for Haematoxylin and Eosin (H and E stained pathological image. Then, an improved bias field correction model is developed to enhance the influence of light for high-frequency part in image and correct the intensity inhomogeneity and detail discontinuity of image. Next, HDR pathological image is generated based on least square method using low dynamic range (LDR image, H and E channel images. Finally, the fine enhanced image is acquired after the detail enhancement process. Experiments with 140 pathological images demonstrate the performance advantages of our proposed method as compared with related work.

Evaluation of an image-based tracking workflow with Kalman filtering for automatic image plane alignment in interventional MRI.

Science.gov (United States)

Neumann, M; Cuvillon, L; Breton, E; de Matheli, M

2013-01-01

Recently, a workflow for magnetic resonance (MR) image plane alignment based on tracking in real-time MR images was introduced. The workflow is based on a tracking device composed of 2 resonant micro-coils and a passive marker, and allows for tracking of the passive marker in clinical real-time images and automatic (re-)initialization using the microcoils. As the Kalman filter has proven its benefit as an estimator and predictor, it is well suited for use in tracking applications. In this paper, a Kalman filter is integrated in the previously developed workflow in order to predict position and orientation of the tracking device. Measurement noise covariances of the Kalman filter are dynamically changed in order to take into account that, according to the image plane orientation, only a subset of the 3D pose components is available. The improved tracking performance of the Kalman extended workflow could be quantified in simulation results. Also, a first experiment in the MRI scanner was performed but without quantitative results yet.

Defogging of road images using gain coefficient-based trilateral filter

Science.gov (United States)

Singh, Dilbag; Kumar, Vijay

2018-01-01

Poor weather conditions are responsible for most of the road accidents year in and year out. Poor weather conditions, such as fog, degrade the visibility of objects. Thus, it becomes difficult for drivers to identify the vehicles in a foggy environment. The dark channel prior (DCP)-based defogging techniques have been found to be an efficient way to remove fog from road images. However, it produces poor results when image objects are inherently similar to airlight and no shadow is cast on them. To eliminate this problem, a modified restoration model-based DCP is developed to remove the fog from road images. The transmission map is also refined by developing a gain coefficient-based trilateral filter. Thus, the proposed technique has an ability to remove fog from road images in an effective manner. The proposed technique is compared with seven well-known defogging techniques on two benchmark foggy images datasets and five real-time foggy images. The experimental results demonstrate that the proposed approach is able to remove the different types of fog from roadside images as well as significantly improve the image's visibility. It also reveals that the restored image has little or no artifacts.

Brain MR Image Restoration Using an Automatic Trilateral Filter With GPU-Based Acceleration.

Science.gov (United States)

Chang, Herng-Hua; Li, Cheng-Yuan; Gallogly, Audrey Haihong

2018-02-01

Noise reduction in brain magnetic resonance (MR) images has been a challenging and demanding task. This study develops a new trilateral filter that aims to achieve robust and efficient image restoration. Extended from the bilateral filter, the proposed algorithm contains one additional intensity similarity funct-ion, which compensates for the unique characteristics of noise in brain MR images. An entropy function adaptive to intensity variations is introduced to regulate the contributions of the weighting components. To hasten the computation, parallel computing based on the graphics processing unit (GPU) strategy is explored with emphasis on memory allocations and thread distributions. To automate the filtration, image texture feature analysis associated with machine learning is investigated. Among the 98 candidate features, the sequential forward floating selection scheme is employed to acquire the optimal texture features for regularization. Subsequently, a two-stage classifier that consists of support vector machines and artificial neural networks is established to predict the filter parameters for automation. A speedup gain of 757 was reached to process an entire MR image volume of 256 × 256 × 256 pixels, which completed within 0.5 s. Automatic restoration results revealed high accuracy with an ensemble average relative error of 0.53 ± 0.85% in terms of the peak signal-to-noise ratio. This self-regulating trilateral filter outperformed many state-of-the-art noise reduction methods both qualitatively and quantitatively. We believe that this new image restoration algorithm is of potential in many brain MR image processing applications that require expedition and automation.

A vector Wiener filter for dual-radionuclide imaging

International Nuclear Information System (INIS)

Links, J.M.; Prince, J.L.; Gupta, S.N.

1996-01-01

The routine use of a single radionuclide for patient imaging in nuclear medicine can be complemented by studies employing two tracers to examine two different processes in a single organ, most frequently by simultaneous imaging of both radionuclides in two different energy windows. In addition, simultaneous transmission/emission imaging with dual-radionuclides has been described, with one radionuclide used for the transmission study and a second for the emission study. There is thus currently considerable interest in dual-radionuclide imaging. A major problem with all dual-radionuclide imaging is the crosstalk between the two radionuclides. Such crosstalk frequently occurs, because scattered radiation from the higher energy radionuclide is detected in the lower energy window, and because the lower energy radionuclide may have higher energy emissions which are detected in the higher energy window. The authors have previously described the use of Fourier-based restoration filtering in single photon emission computed tomography (SPECT) and positron emission tomography (PET) to improve quantitative accuracy by designing a Wiener or other Fourier filter to partially restore the loss of contrast due to scatter and finite spatial resolution effects. The authors describe here the derivation and initial validation of an extension of such filtering for dual-radionuclide imaging that simultaneously (1) improves contrast in each radionuclide's direct image, (2) reduces image noise, and (3) reduces the crosstalk contribution from the other radionuclide. This filter is based on a vector version of the Wiener filter, which is shown to be superior [in the minimum mean square error (MMSE) sense] to the sequential application of separate crosstalk and restoration filters

Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

Science.gov (United States)

Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

2014-05-01

In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

Fusion of multispectral and panchromatic images using multirate filter banks

Institute of Scientific and Technical Information of China (English)

Wang Hong; Jing Zhongliang; Li Jianxun

2005-01-01

In this paper, an image fusion method based on the filter banks is proposed for merging a high-resolution panchromatic image and a low-resolution multispectral image. Firstly, the filter banks are designed to merge different signals with minimum distortion by using cosine modulation. Then, the filter banks-based image fusion is adopted to obtain a high-resolution multispectral image that combines the spectral characteristic of low-resolution data with the spatial resolution of the panchromatic image. Finally, two different experiments and corresponding performance analysis are presented. Experimental results indicate that the proposed approach outperforms the HIS transform, discrete wavelet transform and discrete wavelet frame.

Cluster Based Vector Attribute Filtering

NARCIS (Netherlands)

Kiwanuka, Fred N.; Wilkinson, Michael H.F.

2016-01-01

Morphological attribute filters operate on images based on properties or attributes of connected components. Until recently, attribute filtering was based on a single global threshold on a scalar property to remove or retain objects. A single threshold struggles in case no single property or

Image denoising using new pixon representation based on fuzzy filtering and partial differential equations

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Nikpour, Mohsen

2012-01-01

In this paper, we have proposed two extensions to pixon-based image modeling. The first one is using bicubic interpolation instead of bilinear interpolation and the second one is using fuzzy filtering method, aiming to improve the quality of the pixonal image. Finally, partial differential...

Hyper-spectral modulation fluorescent imaging using double acousto-optical tunable filter based on TeO2-crystals

International Nuclear Information System (INIS)

Zaytsev, Kirill I; Perchik, Alexey V; Chernomyrdin, Nikita V; Yurchenko, Stanislav O; Kudrin, Konstantin G; Reshetov, Igor V

2015-01-01

We have proposed a method for hyper-spectral fluorescent imaging based on acousto-optical filtering. The object of interest was pumped using ultraviolet radiation of mercury lamp equipped with monochromatic excitation filter with the window of transparency centered at 365 nm. Double TeO 2 -based acousto-optical filter, tunable in range from 430 to 780 nm and having 2 nm bandwidth of spectral transparency, was used in order to detect quasimonochromatic images of object fluorescence. Modulating of ultraviolet pump intensity was used in order to reduce an impact of non-fluorescent background on the sample fluorescent imaging. The technique for signal-to-noise ratio improvement, based on fluorescence intensity estimation via digital processing of modulated video sequence of fluorescent object, was introduced. We have implemented the proposed technique for the test sample studying and we have discussed its possible applications

Directional Joint Bilateral Filter for Depth Images

Directory of Open Access Journals (Sweden)

Anh Vu Le

2014-06-01

Full Text Available Depth maps taken by the low cost Kinect sensor are often noisy and incomplete. Thus, post-processing for obtaining reliable depth maps is necessary for advanced image and video applications such as object recognition and multi-view rendering. In this paper, we propose adaptive directional filters that fill the holes and suppress the noise in depth maps. Specifically, novel filters whose window shapes are adaptively adjusted based on the edge direction of the color image are presented. Experimental results show that our method yields higher quality filtered depth maps than other existing methods, especially at the edge boundaries.

An Improved Filtering Method for Quantum Color Image in Frequency Domain

Science.gov (United States)

Li, Panchi; Xiao, Hong

2018-01-01

In this paper we investigate the use of quantum Fourier transform (QFT) in the field of image processing. We consider QFT-based color image filtering operations and their applications in image smoothing, sharpening, and selective filtering using quantum frequency domain filters. The underlying principle used for constructing the proposed quantum filters is to use the principle of the quantum Oracle to implement the filter function. Compared with the existing methods, our method is not only suitable for color images, but also can flexibly design the notch filters. We provide the quantum circuit that implements the filtering task and present the results of several simulation experiments on color images. The major advantages of the quantum frequency filtering lies in the exploitation of the efficient implementation of the quantum Fourier transform.

Imaging spectrometer using a liquid crystal tunable filter

Science.gov (United States)

Chrien, Thomas G.; Chovit, Christopher; Miller, Peter J.

1993-09-01

A demonstration imaging spectrometer using a liquid crystal tunable filter (LCTF) was built and tested on a hot air balloon platform. The LCTF is a tunable polarization interference or Lyot filter. The LCTF enables a small, light weight, low power, band sequential imaging spectrometer design. An overview of the prototype system is given along with a description of balloon experiment results. System model performance predictions are given for a future LCTF based imaging spectrometer design. System design considerations of LCTF imaging spectrometers are discussed.

Restoration of nuclear medicine images using adaptive Wiener filters

International Nuclear Information System (INIS)

Meinel, G.

1989-01-01

An adaptive Wiener filter implementation for restoration of nuclear medicine images is described. These are considerably disturbed both deterministically (definition) and stochastically (Poisson's quantum noise). After introduction of an image model, description of necessary parameter approximations and information on optimum design methods the implementation is described. The filter operates adaptively as concerns the local signal-to-noise ratio and is based on a filter band concept. To verify the restoration effect size numbers are introduced and the filter is tested against these numbers. (author)

Two-dimensional filtering of SPECT images using the Metz and Wiener filters

International Nuclear Information System (INIS)

King, M.A.; Schwinger, R.B.; Penney, B.C.; Doherty, P.W.

1984-01-01

Presently, single photon emission computed tomographic (SPECT) images are usually reconstructed by arbitrarily selecting a one-dimensional ''window'' function for use in reconstruction. A better method would be to automatically choose among a family of two-dimensional image restoration filters in such a way as to produce ''optimum'' image quality. Two-dimensional image processing techniques offer the advantages of a larger statistical sampling of the data for better noise reduction, and two-dimensional image deconvolution to correct for blurring during acquisition. An investigation of two such ''optimal'' digital image restoration techniques (the count-dependent Metz filter and the Wiener filter) was made. They were applied both as two-dimensional ''window'' functions for preprocessing SPECT images, and for filtering reconstructed images. Their performance was compared by measuring image contrast and per cent fractional standard deviation (% FSD) in multiple-acquisitions of the Jaszczak SPECT phantom at two different count levels. A statistically significant increase in image contrast and decrease in % FSD was observed with these techniques when compared to the results of reconstruction with a ramp filter. The adaptability of the techniques was manifested in a lesser % reduction in % FSD at the high count level coupled with a greater enhancement in image contrast. Using an array processor, processing time was 0.2 sec per image for the Metz filter and 3 sec for the Wiener filter. It is concluded that two-dimensional digital image restoration with these techniques can produce a significant increase in SPECT image quality

Frequency Domain Image Filtering Using CUDA

Directory of Open Access Journals (Sweden)

Muhammad Awais Rajput

2014-10-01

Full Text Available In this paper, we investigate the implementation of image filtering in frequency domain using NVIDIA?s CUDA (Compute Unified Device Architecture. In contrast to signal and image filtering in spatial domain which uses convolution operations and hence is more compute-intensive for filters having larger spatial extent, the frequency domain filtering uses FFT (Fast Fourier Transform which is much faster and significantly reduces the computational complexity of the filtering. We implement the frequency domain filtering on CPU and GPU respectively and analyze the speed-up obtained from the CUDA?s parallel processing paradigm. In order to demonstrate the efficiency of frequency domain filtering on CUDA, we implement three frequency domain filters, i.e., Butterworth, low-pass and Gaussian for processing different sizes of images on CPU and GPU respectively and perform the GPU vs. CPU benchmarks. The results presented in this paper show that the frequency domain filtering with CUDA achieves significant speed-up over the CPU processing in frequency domain with the same level of (output image quality on both the processing architectures

Frequency domain image filtering using cuda

International Nuclear Information System (INIS)

Rajput, M.A.; Khan, U.A.

2014-01-01

In this paper, we investigate the implementation of image filtering in frequency domain using NVIDIA's CUDA (Compute Unified Device Architecture). In contrast to signal and image filtering in spatial domain which uses convolution operations and hence is more compute-intensive for filters having larger spatial extent, the frequency domain filtering uses FFT (Fast Fourier Transform) which is much faster and significantly reduces the computational complexity of the filtering. We implement the frequency domain filtering on CPU and GPU respectively and analyze the speed-up obtained from the CUDA's parallel processing paradigm. In order to demonstrate the efficiency of frequency domain filtering on CUDA, we implement three frequency domain filters, i.e., Butter worth, low-pass and Gaussian for processing different sizes of images on CPU and GPU respectively and perform the GPU vs. CPU benchmarks. The results presented in this paper show that the frequency domain filtering with CUDA achieves significant speed-up over the CPU processing in frequency domain with the same level of (output) image quality on both the processing architectures. (author)

Vector Directional Distance Rational Hybrid Filters for Color Image Restoration

Directory of Open Access Journals (Sweden)

L. Khriji

2005-12-01

Full Text Available A new class of nonlinear filters, called vector-directional distance rational hybrid filters (VDDRHF for multispectral image processing, is introduced and applied to color image-filtering problems. These filters are based on rational functions (RF. The VDDRHF filter is a two-stage filter, which exploits the features of the vector directional distance filter (VDDF, the center weighted vector directional distance filter (CWVDDF and those of the rational operator. The filter output is a result of vector rational function (VRF operating on the output of three sub-functions. Two vector directional distance (VDDF filters and one center weighted vector directional distance filter (CWVDDF are proposed to be used in the first stage due to their desirable properties, such as, noise attenuation, chromaticity retention, and edges and details preservation. Experimental results show that the new VDDRHF outperforms a number of widely known nonlinear filters for multi-spectral image processing such as the vector median filter (VMF, the generalized vector directional filters (GVDF and distance directional filters (DDF with respect to all criteria used.

Spatial filters for focusing ultrasound images

DEFF Research Database (Denmark)

Jensen, Jørgen Arendt; Gori, Paola

2001-01-01

, but the approach always yields point spread functions better or equal to a traditional dynamically focused image. Finally, the process was applied to in-vivo clinical images of the liver and right kidney from a 28 years old male. The data was obtained with a single element transducer focused at 100 mm....... A new method for making spatial matched filter focusing of RF ultrasound data is proposed based on the spatial impulse response description of the imaging. The response from a scatterer at any given point in space relative to the transducer can be calculated, and this gives the spatial matched filter...... for synthetic aperture imaging for single element transducers. It is evaluated using the Field II program. Data from a single 3 MHz transducer focused at a distance of 80 mm is processed. Far from the transducer focal region, the processing greatly improves the image resolution: the lateral slice...

Multiscale infrared and visible image fusion using gradient domain guided image filtering

Science.gov (United States)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods.

Science.gov (United States)

Hoak, Anthony; Medeiros, Henry; Povinelli, Richard J

2017-03-03

We develop an interactive likelihood (ILH) for sequential Monte Carlo (SMC) methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL) and TUD-Stadtmitte) using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA) and classification of events, activities and relationships for multi-object trackers (CLEAR MOT)). In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

Directory of Open Access Journals (Sweden)

Byeong Hak Kim

2017-12-01

Full Text Available Unmanned aerial vehicles (UAVs are equipped with optical systems including an infrared (IR camera such as electro-optical IR (EO/IR, target acquisition and designation sights (TADS, or forward looking IR (FLIR. However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC and scene-based NUC (SBNUC. However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA. In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR and long wave infrared (LWIR images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

Science.gov (United States)

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-01-01

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

Science.gov (United States)

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-12-27

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

A robust nonlinear filter for image restoration.

Science.gov (United States)

Koivunen, V

1995-01-01

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

Imaging spin filter for electrons based on specular reflection from iridium (001)

Energy Technology Data Exchange (ETDEWEB)

Kutnyakhov, D.; Lushchyk, P. [Johannes Gutenberg-Universität, Institut für Physik, 55099 Mainz (Germany); Fognini, A.; Perriard, D. [Laboratorium für Festkörperphysik, ETH Zürich, 8093 Zürich (Switzerland); Kolbe, M.; Medjanik, K.; Fedchenko, E.; Nepijko, S.A.; Elmers, H.J. [Johannes Gutenberg-Universität, Institut für Physik, 55099 Mainz (Germany); Salvatella, G.; Stieger, C.; Gort, R.; Bähler, T.; Michlmayer, T.; Acremann, Y.; Vaterlaus, A. [Laboratorium für Festkörperphysik, ETH Zürich, 8093 Zürich (Switzerland); Giebels, F.; Gollisch, H.; Feder, R. [Universität Duisburg-Essen, Theoretische Festkörperphysik, 47057 Duisburg (Germany); Tusche, C. [Max Planck-Institut für Mikrostrukturphysik, 06120 Halle (Germany); and others

2013-07-15

As Stern–Gerlach type spin filters do not work with electrons, spin analysis of electron beams is accomplished by spin-dependent scattering processes based on spin–orbit or exchange interaction. Existing polarimeters are single-channel devices characterized by an inherently low figure of merit (FoM) of typically 10{sup −4}–10{sup −3}. This single-channel approach is not compatible with parallel imaging microscopes and also not with modern electron spectrometers that acquire a certain energy and angular interval simultaneously. We present a novel type of polarimeter that can transport a full image by making use of k-parallel conservation in low-energy electron diffraction. We studied specular reflection from Ir (001) because this spin-filter crystal provides a high analyzing power combined with a “lifetime” in UHV of a full day. One good working point is centered at 39 eV scattering energy with a broad maximum of 5 eV usable width. A second one at about 10 eV shows a narrower profile but much higher FoM. A relativistic layer-KKR SPLEED calculation shows good agreement with measurements. - Highlights: • Novel type of spin polarimeter can transport a full image by making use of k{sup →}{sub ||} conservation in LEED. • When combined with a hemispherical analyzer, it acquires a certain energy and angular interval simultaneously. • Ir (001) based spin-filter provides a high analyzing power combined with a “lifetime” in UHV of a full day. • Parallel spin detection improves spin polarimeter efficiency by orders of magnitude. • A relativistic layer-KKR SPLEED calculation shows good agreement with measurements.

Selected annotated bibliographies for adaptive filtering of digital image data

Science.gov (United States)

Mayers, Margaret; Wood, Lynnette

1988-01-01

Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity.Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze.Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

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Yuanqiang Ren

2017-05-01

Full Text Available Structural health monitoring (SHM of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

Feature-Based Nonlocal Polarimetric SAR Filtering

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Xiaoli Xing

2017-10-01

Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

Cat Swarm Optimization Based Functional Link Artificial Neural Network Filter for Gaussian Noise Removal from Computed Tomography Images

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M. Kumar

2016-01-01

Full Text Available Gaussian noise is one of the dominant noises, which degrades the quality of acquired Computed Tomography (CT image data. It creates difficulties in pathological identification or diagnosis of any disease. Gaussian noise elimination is desirable to improve the clarity of a CT image for clinical, diagnostic, and postprocessing applications. This paper proposes an evolutionary nonlinear adaptive filter approach, using Cat Swarm Functional Link Artificial Neural Network (CS-FLANN to remove the unwanted noise. The structure of the proposed filter is based on the Functional Link Artificial Neural Network (FLANN and the Cat Swarm Optimization (CSO is utilized for the selection of optimum weight of the neural network filter. The applied filter has been compared with the existing linear filters, like the mean filter and the adaptive Wiener filter. The performance indices, such as peak signal to noise ratio (PSNR, have been computed for the quantitative analysis of the proposed filter. The experimental evaluation established the superiority of the proposed filtering technique over existing methods.

Image-Based Multi-Target Tracking through Multi-Bernoulli Filtering with Interactive Likelihoods

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Anthony Hoak

2017-03-01

Full Text Available We develop an interactive likelihood (ILH for sequential Monte Carlo (SMC methods for image-based multiple target tracking applications. The purpose of the ILH is to improve tracking accuracy by reducing the need for data association. In addition, we integrate a recently developed deep neural network for pedestrian detection along with the ILH with a multi-Bernoulli filter. We evaluate the performance of the multi-Bernoulli filter with the ILH and the pedestrian detector in a number of publicly available datasets (2003 PETS INMOVE, Australian Rules Football League (AFL and TUD-Stadtmitte using standard, well-known multi-target tracking metrics (optimal sub-pattern assignment (OSPA and classification of events, activities and relationships for multi-object trackers (CLEAR MOT. In all datasets, the ILH term increases the tracking accuracy of the multi-Bernoulli filter.

Combination of Wiener filtering and singular value decomposition filtering for volume imaging PET

International Nuclear Information System (INIS)

Shao, L.; Lewitt, R.M.; Karp, J.S.

1995-01-01

Although the three-dimensional (3D) multi-slice rebinning (MSRB) algorithm in PET is fast and practical, and provides an accurate reconstruction, the MSRB image, in general, suffers from the noise amplified by its singular value decomposition (SVD) filtering operation in the axial direction. Their aim in this study is to combine the use of the Wiener filter (WF) with the SVD to decrease the noise and improve the image quality. The SVD filtering ''deconvolves'' the spatially variant axial response function while the WF suppresses the noise and reduces the blurring not modeled by the axial SVD filter but included in the system modulation transfer function. Therefore, the synthesis of these two techniques combines the advantages of both filters. The authors applied this approach to the volume imaging HEAD PENN-PET brain scanner with an axial extent of 256 mm. This combined filter was evaluated in terms of spatial resolution, image contrast, and signal-to-noise ratio with several phantoms, such as a cold sphere phantom and 3D brain phantom. Specifically, the authors studied both the SVD filter with an axial Wiener filter and the SVD filter with a 3D Wiener filter, and compared the filtered images to those from the 3D reprojection (3DRP) reconstruction algorithm. Their results indicate that the Wiener filter increases the signal-to-noise ratio and also improves the contrast. For the MSRB images of the 3D brain phantom, after 3D WF, both the Gray/White and Gray/Ventricle ratios were improved from 1.8 to 2.8 and 2.1 to 4.1, respectively. In addition, the image quality with the MSRB algorithm is close to that of the 3DRP algorithm with 3D WF applied to both image reconstructions

Implementational Aspects of the Contourlet Filter Bank and Application in Image Coding

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Truong T. Nguyen

2009-02-01

Full Text Available This paper analyzed the implementational aspects of the contourlet filter bank (or the pyramidal directional filter bank (PDFB, and considered its application in image coding. First, details of the binary tree-structured directional filter bank (DFB are presented, including a modification to minimize the phase delay factor and necessary steps for handling rectangular images. The PDFB is viewed as an overcomplete filter bank, and the directional filters are expressed in terms of polyphase components of the pyramidal filter bank and the conventional DFB. The aliasing effect of the conventional DFB and the Laplacian pyramid to the directional filters is then considered, and the conditions for reducing this effect are presented. The new filters obtained by redesigning the PDFBs satisfying these requirements have much better frequency responses. A hybrid multiscale filter bank consisting of the PDFB at higher scales and the traditional maximally decimated wavelet filter bank at lower scales is constructed to provide a sparse image representation. A novel embedded image coding system based on the image decomposition and a morphological dilation algorithm is then presented. The coding algorithm efficiently clusters the significant coefficients using progressive morphological operations. Context models for arithmetic coding are designed to exploit the intraband dependency and the correlation existing among the neighboring directional subbands. Experimental results show that the proposed coding algorithm outperforms the current state-of-the-art wavelet-based coders, such as JPEG2000, for images with directional features.

Image super-resolution reconstruction based on regularization technique and guided filter

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

2017-06-01

In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

SD LMS L-Filters for Filtration of Gray Level Images in Timespatial Domain Based on GLCM Features

Directory of Open Access Journals (Sweden)

Robert Hudec

2008-01-01

Full Text Available In this paper, the new kind of adaptive signal-dependent LMS L-filter for suppression of a mixed noise in greyscale images is developed. It is based on the texture parameter measurement as modification of spatial impulse detector structure. Moreover, the one of GLCM (Gray Level Co-occurrence Matrix features, namely, the contrast or inertia adjusted by threshold as switch between partial filters is utilised. Finally, at the positions of partial filters the adaptive LMS versions of L-filters are chosen.

Image enhancement by spatial frequency post-processing of images obtained with pupil filters

Science.gov (United States)

Estévez, Irene; Escalera, Juan C.; Stefano, Quimey Pears; Iemmi, Claudio; Ledesma, Silvia; Yzuel, María J.; Campos, Juan

2016-12-01

The use of apodizing or superresolving filters improves the performance of an optical system in different frequency bands. This improvement can be seen as an increase in the OTF value compared to the OTF for the clear aperture. In this paper we propose a method to enhance the contrast of an image in both its low and its high frequencies. The method is based on the generation of a synthetic Optical Transfer Function, by multiplexing the OTFs given by the use of different non-uniform transmission filters on the pupil. We propose to capture three images, one obtained with a clear pupil, one obtained with an apodizing filter that enhances the low frequencies and another one taken with a superresolving filter that improves the high frequencies. In the Fourier domain the three spectra are combined by using smoothed passband filters, and then the inverse transform is performed. We show that we can create an enhanced image better than the image obtained with the clear aperture. To evaluate the performance of the method, bar tests (sinusoidal tests) with different frequency content are used. The results show that a contrast improvement in the high and low frequencies is obtained.

3D Wavelet-Based Filter and Method

Science.gov (United States)

Moss, William C.; Haase, Sebastian; Sedat, John W.

2008-08-12

A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

Science.gov (United States)

Ahmad, Asif; Asif, Amina; Rajpoot, Nasir; Arif, Muhammad; Minhas, Fayyaz Ul Amir Afsar

2017-11-21

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist .

An adaptive Kalman filter for speckle reductions in ultrasound images

International Nuclear Information System (INIS)

Castellini, G.; Labate, D.; Masotti, L.; Mannini, E.; Rocchi, S.

1988-01-01

Speckle is the term used to describe the granular appearance found in ultrasound images. The presence of speckle reduces the diagnostic potential of the echographic technique because it tends to mask small inhomogeneities of the investigated tissue. We developed a new method of speckle reductions that utilizes an adaptive one-dimensional Kalman filter based on the assumption that the observed image can be considered as a superimposition of speckle on a ''true images''. The filter adaptivity, necessary to avoid loss of resolution, has been obtained by statistical considerations on the local signal variations. The results of the applications of this particular Kalman filter, both on A-Mode and B-MODE images, show a significant speckle reduction

Convex blind image deconvolution with inverse filtering

Science.gov (United States)

Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong

2018-03-01

Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.

Complex noise suppression using a sparse representation and 3D filtering of images

Science.gov (United States)

Kravchenko, V. F.; Ponomaryov, V. I.; Pustovoit, V. I.; Palacios-Enriquez, A.

2017-08-01

A novel method for the filtering of images corrupted by complex noise composed of randomly distributed impulses and additive Gaussian noise has been substantiated for the first time. The method consists of three main stages: the detection and filtering of pixels corrupted by impulsive noise, the subsequent image processing to suppress the additive noise based on 3D filtering and a sparse representation of signals in a basis of wavelets, and the concluding image processing procedure to clean the final image of the errors emerged at the previous stages. A physical interpretation of the filtering method under complex noise conditions is given. A filtering block diagram has been developed in accordance with the novel approach. Simulations of the novel image filtering method have shown an advantage of the proposed filtering scheme in terms of generally recognized criteria, such as the structural similarity index measure and the peak signal-to-noise ratio, and when visually comparing the filtered images.

Efficient Filtering of Noisy Fingerprint Images

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Maria Liliana Costin

2016-01-01

Full Text Available Fingerprint identification is an important field in the wide domain of biometrics with many applications, in different areas such: judicial, mobile phones, access systems, airports. There are many elaborated algorithms for fingerprint identification, but none of them can guarantee that the results of identification are always 100 % accurate. A first step in a fingerprint image analysing process consists in the pre-processing or filtering. If the result after this step is not by a good quality the upcoming identification process can fail. A major difficulty can appear in case of fingerprint identification if the images that should be identified from a fingerprint image database are noisy with different type of noise. The objectives of the paper are: the successful completion of the noisy digital image filtering, a novel more robust algorithm of identifying the best filtering algorithm and the classification and ranking of the images. The choice about the best filtered images of a set of 9 algorithms is made with a dual method of fuzzy and aggregation model. We are proposing through this paper a set of 9 filters with different novelty designed for processing the digital images using the following methods: quartiles, medians, average, thresholds and histogram equalization, applied all over the image or locally on small areas. Finally the statistics reveal the classification and ranking of the best algorithms.

Development of an adaptive bilateral filter for evaluating color image difference

Science.gov (United States)

Wang, Zhaohui; Hardeberg, Jon Yngve

2012-04-01

Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

Fast bilateral filtering of CT-images

Energy Technology Data Exchange (ETDEWEB)

Steckmann, Sven; Baer, Matthias; Kachelriess, Marc [Erlangen-Nuernberg Univ., Erlangen (Germany). Inst. of Medical Physics (IMP)

2011-07-01

The Bilateral filter is able to get a lower noise level while retaining the edges in images. The downside of a bilateral filter is the high order of the problem itself. While having a Volume size of N with a dimension of d and a filter window of r the problem is of size N{sup d} . r{sup d}. In the literature there are some proposals for speeding up by reducing this order by approximating a component of the filter. This leads to inaccurate results which often implies non acceptable artifacts for medical imaging. A better way for medical imaging is to speed up the filter itself while leaving the basic structure intact. This is the way our implementation uses. We solve the problem of calculating the function of e{sup -x} in an efficient way on modern architectures, and the problem of vectorizing the filtering process. As result we implemented a filter which is 2.5 times faster than the highly optimized basic approach. By comparing the basic analytical approach with the final algorithm, the differences in quality of the computing process is negligible to the human eye. We are able to process a volume with 512{sup 3} voxels with a filter of 25 x 25 x 1 in 21 s on a modern Intel Xeon platform with two X5590 processors running at 3.33 GHz. (orig.)

Quantum Image Filtering in the Frequency Domain

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MANTA, V. I.

2013-08-01

Full Text Available In this paper we address the emerging field of Quantum Image Processing. We investigate the use of quantum computing systems to represent and manipulate images. In particular, we consider the basic task of image filtering. We prove that a quantum version for this operation can be achieved, even though the quantum convolution of two sequences is physically impossible. In our approach we use the principle of the quantum oracle to implement the filter function. We provide the quantum circuit that implements the filtering task and present the results of several simulation experiments on grayscale images. There are important differences between the classical and the quantum implementations for image filtering. We analyze these differences and show that the major advantage of the quantum approach lies in the exploitation of the efficient implementation of the quantum Fourier transform.

32Still Image Compression Algorithm Based on Directional Filter Banks

OpenAIRE

Chunling Yang; Duanwu Cao; Li Ma

2010-01-01

Hybrid wavelet and directional filter banks (HWD) is an effective multi-scale geometrical analysis method. Compared to wavelet transform, it can better capture the directional information of images. But the ringing artifact, which is caused by the coefficient quantization in transform domain, is the biggest drawback of image compression algorithms in HWD domain. In this paper, by researching on the relationship between directional decomposition and ringing artifact, an improved decomposition ...

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

Science.gov (United States)

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

AER image filtering

Science.gov (United States)

Gómez-Rodríguez, F.; Linares-Barranco, A.; Paz, R.; Miró-Amarante, L.; Jiménez, G.; Civit, A.

2007-05-01

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows real-time virtual massive connectivity among huge number of neurons located on different chips.[1] By exploiting high speed digital communication circuits (with nano-seconds timing), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Neurons generate "events" according to their activity levels. That is, more active neurons generate more events per unit time and access the interchip communication channel more frequently than neurons with low activity. In Neuromorphic system development, AER brings some advantages to develop real-time image processing system: (1) AER represents the information like time continuous stream not like a frame; (2) AER sends the most important information first (although this depends on the sender); (3) AER allows to process information as soon as it is received. When AER is used in artificial vision field, each pixel is considered like a neuron, so pixel's intensity is represented like a sequence of events; modifying the number and the frequency of these events, it is possible to make some image filtering. In this paper we present four image filters using AER: (a) Noise addition and suppression, (b) brightness modification, (c) single moving object tracking and (d) geometrical transformations (rotation, translation, reduction and magnification). For testing and debugging, we use USB-AER board developed by Robotic and Technology of Computers Applied to Rehabilitation (RTCAR) research group. This board is based on an FPGA, devoted to manage the AER functionality. This board also includes a micro-controlled for USB communication, 2 Mbytes RAM and 2 AER ports (one for input and one for output).

Edge-based correlation image registration for multispectral imaging

Science.gov (United States)

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

Multi-look polarimetric SAR image filtering using simulated annealing

DEFF Research Database (Denmark)

Schou, Jesper

2000-01-01

Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

Filter and Filter Bank Design for Image Texture Recognition

Energy Technology Data Exchange (ETDEWEB)

Randen, Trygve

1997-12-31

The relevance of this thesis to energy and environment lies in its application to remote sensing such as for instance sea floor mapping and seismic pattern recognition. The focus is on the design of two-dimensional filters for feature extraction, segmentation, and classification of digital images with textural content. The features are extracted by filtering with a linear filter and estimating the local energy in the filter response. The thesis gives a review covering broadly most previous approaches to texture feature extraction and continues with proposals of some new techniques. 143 refs., 59 figs., 7 tabs.

Real-time single image dehazing based on dark channel prior theory and guided filtering

Science.gov (United States)

Zhang, Zan

2017-10-01

Images and videos taken outside the foggy day are serious degraded. In order to restore degraded image taken in foggy day and overcome traditional Dark Channel prior algorithms problems of remnant fog in edge, we propose a new dehazing method.We first find the fog area in the dark primary color map to obtain the estimated value of the transmittance using quadratic tree. Then we regard the gray-scale image after guided filtering as atmospheric light map and remove haze based on it. Box processing and image down sampling technology are also used to improve the processing speed. Finally, the atmospheric light scattering model is used to restore the image. A plenty of experiments show that algorithm is effective, efficient and has a wide range of application.

Image denoising by sparse 3-D transform-domain collaborative filtering.

Science.gov (United States)

Dabov, Kostadin; Foi, Alessandro; Katkovnik, Vladimir; Egiazarian, Karen

2007-08-01

We propose a novel image denoising strategy based on an enhanced sparse representation in transform domain. The enhancement of the sparsity is achieved by grouping similar 2-D image fragments (e.g., blocks) into 3-D data arrays which we call "groups." Collaborative filtering is a special procedure developed to deal with these 3-D groups. We realize it using the three successive steps: 3-D transformation of a group, shrinkage of the transform spectrum, and inverse 3-D transformation. The result is a 3-D estimate that consists of the jointly filtered grouped image blocks. By attenuating the noise, the collaborative filtering reveals even the finest details shared by grouped blocks and, at the same time, it preserves the essential unique features of each individual block. The filtered blocks are then returned to their original positions. Because these blocks are overlapping, for each pixel, we obtain many different estimates which need to be combined. Aggregation is a particular averaging procedure which is exploited to take advantage of this redundancy. A significant improvement is obtained by a specially developed collaborative Wiener filtering. An algorithm based on this novel denoising strategy and its efficient implementation are presented in full detail; an extension to color-image denoising is also developed. The experimental results demonstrate that this computationally scalable algorithm achieves state-of-the-art denoising performance in terms of both peak signal-to-noise ratio and subjective visual quality.

Aircraft Detection from VHR Images Based on Circle-Frequency Filter and Multilevel Features

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Feng Gao

2013-01-01

Full Text Available Aircraft automatic detection from very high-resolution (VHR images plays an important role in a wide variety of applications. This paper proposes a novel detector for aircraft detection from very high-resolution (VHR remote sensing images. To accurately distinguish aircrafts from background, a circle-frequency filter (CF-filter is used to extract the candidate locations of aircrafts from a large size image. A multi-level feature model is then employed to represent both local appearance and spatial layout of aircrafts by means of Robust Hue Descriptor and Histogram of Oriented Gradients. The experimental results demonstrate the superior performance of the proposed method.

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.

High performance 3D adaptive filtering for DSP based portable medical imaging systems

Science.gov (United States)

Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

2015-03-01

Portable medical imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. Despite their constraints on power, size and cost, portable imaging devices must still deliver high quality images. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often cannot be run with sufficient performance on a portable platform. In recent years, advanced multicore digital signal processors (DSP) have been developed that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms on a portable platform. In this study, the performance of a 3D adaptive filtering algorithm on a DSP is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec with an Ultrasound 3D probe. Relative performance and power is addressed between a reference PC (Quad Core CPU) and a TMS320C6678 DSP from Texas Instruments.

Metal artefact reduction for a dental cone beam CT image using image segmentation and backprojection filters

International Nuclear Information System (INIS)

Mohammadi, Mahdi; Khotanlou, Hassan; Mohammadi, Mohammad

2011-01-01

Full text: Due to low dose delivery and fast scanning, the dental Cone Beam CT (CBCT) is the latest technology being implanted for a range of dental imaging. The presence of metallic objects including amalgam or gold fillings in the mouth produces an intuitive image for human jaws. The feasibility of a fast and accurate approach for metal artefact reduction for dental CBCT is investigated. The current study investigates the metal artefact reduction using image segmentation and modification of several sinigrams. In order to reduce metal effects such as beam hardening, streak artefact and intense noises, the application of several algorithms is evaluated. The proposed method includes three stages: preprocessing, reconstruction and post-processing. In the pre-processing stage, in order to reduce the noise level, several phase and frequency filters were applied. At the second stage, based on the specific sinogram achieved for each segment, spline interpolation and weighting backprojection filters were applied to reconstruct the original image. A three-dimensional filter was then applied on reconstructed images, to improve the image quality. Results showed that compared to other available filters, standard frequency filters have a significant influence in the preprocessing stage (ΔHU = 48 ± 6). In addition, with the streak artefact, the probability of beam hardening artefact increases. t e post-processing stage, the application of three-dimensional filters improves the quality of reconstructed images (See Fig. I). Conclusion The proposed method reduces metal artefacts especially where there are more than one metal implanted in the region of interest.

Guided Image Filtering-Based Pan-Sharpening Method: A Case Study of GaoFen-2 Imagery

Directory of Open Access Journals (Sweden)

Yalan Zheng

2017-12-01

Full Text Available GaoFen-2 (GF-2 is a civilian optical satellite self-developed by China equipped with both multispectral and panchromatic sensors, and is the first satellite in China with a resolution below 1 m. Because the pan-sharpening methods on GF-2 imagery have not been a focus of previous works, we propose a novel pan-sharpening method based on guided image filtering and compare the performance to state-of-the-art methods on GF-2 images. Guided image filtering was introduced to decompose and transfer the details and structures from the original panchromatic and multispectral bands. Thereafter, an adaptive model that considers the local spectral relationship was designed to properly inject spatial information back into the original spectral bands. Four pairs of GF-2 images acquired from urban, water body, cropland, and forest areas were selected for the experiments. Both quantitative and visual inspections were used for the assessment. The experimental results demonstrated that for GF-2 imagery acquired over different scenes, the proposed approach consistently achieves high spectral fidelity and enhances spatial details, thereby benefitting the potential classification procedures.

Filter's importance in nuclear cardiology imaging

International Nuclear Information System (INIS)

Jesus, Maria C. de; Lima, Ana L.S.; Santos, Joyra A. dos; Megueriam, Berdj A.

2008-01-01

Full text: Nuclear Medicine is a medical speciality which employs tomography procedures for the diagnosis, treatment and prevention of diseases. One of the most commonly used apparatus is the Single Photon Emission Computed Tomography (SPECT). To perform exams, a very small amount of a radiopharmaceutical must be given to the patient. Then, a gamma camera is placed in convenient positions to perform the photon counting, which is used to reconstruct a full 3 dimensional distribution of the radionuclide inside the body or organ. This reconstruction provides a 3-dimensional image in spatial coordinates, of the body or organ under study, allowing the physician to give the diagnostic. Image reconstruction is usually worked in the frequency domain, due to a great simplification introduced by the Fourier decomposition of image spectra. After the reconstruction, an inverse Fourier transform must be applied to trace back the image into spatial coordinates. To optimize this reconstruction procedure, digital filters are used to remove undesirable components of frequency, which can 'shadow' relevant physical signatures of diseases. Unfortunately, the efficiency of the applied filter is strongly dependent on its own mathematical parameters. In this work we demonstrate how filters interfere on image quality in cardiology examinations with SPECT, concerning perfusion and myocardial viability and the importance of the medical physicist in the choice of the right filters avoiding some serious problems that could occur in the inadequate processing of an image damaging the medical diagnosis. (author)

Fractional order integration and fuzzy logic based filter for denoising of echocardiographic image.

Science.gov (United States)

Saadia, Ayesha; Rashdi, Adnan

2016-12-01

Ultrasound is widely used for imaging due to its cost effectiveness and safety feature. However, ultrasound images are inherently corrupted with speckle noise which severely affects the quality of these images and create difficulty for physicians in diagnosis. To get maximum benefit from ultrasound imaging, image denoising is an essential requirement. To perform image denoising, a two stage methodology using fuzzy weighted mean and fractional integration filter has been proposed in this research work. In stage-1, image pixels are processed by applying a 3 × 3 window around each pixel and fuzzy logic is used to assign weights to the pixels in each window, replacing central pixel of the window with weighted mean of all neighboring pixels present in the same window. Noise suppression is achieved by assigning weights to the pixels while preserving edges and other important features of an image. In stage-2, the resultant image is further improved by fractional order integration filter. Effectiveness of the proposed methodology has been analyzed for standard test images artificially corrupted with speckle noise and real ultrasound B-mode images. Results of the proposed technique have been compared with different state-of-the-art techniques including Lsmv, Wiener, Geometric filter, Bilateral, Non-local means, Wavelet, Perona et al., Total variation (TV), Global Adaptive Fractional Integral Algorithm (GAFIA) and Improved Fractional Order Differential (IFD) model. Comparison has been done on quantitative and qualitative basis. For quantitative analysis different metrics like Peak Signal to Noise Ratio (PSNR), Speckle Suppression Index (SSI), Structural Similarity (SSIM), Edge Preservation Index (β) and Correlation Coefficient (ρ) have been used. Simulations have been done using Matlab. Simulation results of artificially corrupted standard test images and two real Echocardiographic images reveal that the proposed method outperforms existing image denoising techniques

Efficient Scalable Median Filtering Using Histogram-Based Operations.

Science.gov (United States)

Green, Oded

2018-05-01

Median filtering is a smoothing technique for noise removal in images. While there are various implementations of median filtering for a single-core CPU, there are few implementations for accelerators and multi-core systems. Many parallel implementations of median filtering use a sorting algorithm for rearranging the values within a filtering window and taking the median of the sorted value. While using sorting algorithms allows for simple parallel implementations, the cost of the sorting becomes prohibitive as the filtering windows grow. This makes such algorithms, sequential and parallel alike, inefficient. In this work, we introduce the first software parallel median filtering that is non-sorting-based. The new algorithm uses efficient histogram-based operations. These reduce the computational requirements of the new algorithm while also accessing the image fewer times. We show an implementation of our algorithm for both the CPU and NVIDIA's CUDA supported graphics processing unit (GPU). The new algorithm is compared with several other leading CPU and GPU implementations. The CPU implementation has near perfect linear scaling with a speedup on a quad-core system. The GPU implementation is several orders of magnitude faster than the other GPU implementations for mid-size median filters. For small kernels, and , comparison-based approaches are preferable as fewer operations are required. Lastly, the new algorithm is open-source and can be found in the OpenCV library.

Preliminary energy-filtering neutron imaging with time-of-flight method on PKUNIFTY: A compact accelerator based neutron imaging facility at Peking University

Energy Technology Data Exchange (ETDEWEB)

Wang, Hu; Zou, Yubin, E-mail: zouyubin@pku.edu.cn; Wen, Weiwei; Lu, Yuanrong; Guo, Zhiyu

2016-07-01

Peking University Neutron Imaging Facility (PKUNIFTY) works on an accelerator–based neutron source with a repetition period of 10 ms and pulse duration of 0.4 ms, which has a rather low Cd ratio. To improve the effective Cd ratio and thus improve the detection capability of the facility, energy-filtering neutron imaging was realized with the intensified CCD camera and time-of-flight (TOF) method. Time structure of the pulsed neutron source was firstly simulated with Geant4, and the simulation result was evaluated with experiment. Both simulation and experiment results indicated that fast neutrons and epithermal neutrons were concentrated in the first 0.8 ms of each pulse period; meanwhile in the period of 0.8–2.0 ms only thermal neutrons existed. Based on this result, neutron images with and without energy filtering were acquired respectively, and it showed that detection capability of PKUNIFTY was improved with setting the exposure interval as 0.8–2.0 ms, especially for materials with strong moderating capability.

Collaborating Filtering Community Image Recommendation System Based on Scene

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He Tao

2017-01-01

Full Text Available With the advancement of smart city, the development of intelligent mobile terminal and wireless network, the traditional text information service no longer meet the needs of the community residents, community image service appeared as a new media service. “There are pictures of the truth” has become a community residents to understand and master the new dynamic community, image information service has become a new information service. However, there are two major problems in image information service. Firstly, the underlying eigenvalues extracted by current image feature extraction techniques are difficult for users to understand, and there is a semantic gap between the image content itself and the user’s understanding; secondly, in community life of the image data increasing quickly, it is difficult to find their own interested image data. Aiming at the two problems, this paper proposes a unified image semantic scene model to express the image content. On this basis, a collaborative filtering recommendation model of fusion scene semantics is proposed. In the recommendation model, a comprehensiveness and accuracy user interest model is proposed to improve the recommendation quality. The results of the present study have achieved good results in the pilot cities of Wenzhou and Yan'an, and it is applied normally.

Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video

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Marek Szczepański

2017-01-01

Full Text Available We propose a novel filtering technique capable of reducing the multiplicative noise in ultrasound images that is an extension of the denoising algorithms based on the concept of digital paths. In this approach, the filter weights are calculated taking into account the similarity between pixel intensities that belongs to the local neighborhood of the processed pixel, which is called a path. The output of the filter is estimated as the weighted average of pixels connected by the paths. The way of creating paths is pivotal and determines the effectiveness and computational complexity of the proposed filtering design. Such procedure can be effective for different types of noise but fail in the presence of multiplicative noise. To increase the filtering efficiency for this type of disturbances, we introduce some improvements of the basic concept and new classes of similarity functions and finally extend our techniques to a spatiotemporal domain. The experimental results prove that the proposed algorithm provides the comparable results with the state-of-the-art techniques for multiplicative noise removal in ultrasound images and it can be applied for real-time image enhancement of video streams.

A filtering approach to image reconstruction in 3D SPECT

International Nuclear Information System (INIS)

Bronnikov, Andrei V.

2000-01-01

We present a new approach to three-dimensional (3D) image reconstruction using analytical inversion of the exponential divergent beam transform, which can serve as a mathematical model for cone-beam 3D SPECT imaging. We apply a circular cone-beam scan and assume constant attenuation inside a convex area with a known boundary, which is satisfactory in brain imaging. The reconstruction problem is reduced to an image restoration problem characterized by a shift-variant point spread function which is given analytically. The method requires two computation steps: backprojection and filtering. The modulation transfer function (MTF) of the filter is derived by means of an original methodology using the 2D Laplace transform. The filter is implemented in the frequency domain and requires 2D Fourier transform of transverse slices. In order to obtain a shift-invariant cone-beam projection-backprojection operator we resort to an approximation, assuming that the collimator has a relatively large focal length. Nevertheless, numerical experiments demonstrate surprisingly good results for detectors with relatively short focal lengths. The use of a wavelet-based filtering algorithm greatly improves the stability to Poisson noise. (author)

Image pre-filtering for measurement error reduction in digital image correlation

Science.gov (United States)

Zhou, Yihao; Sun, Chen; Song, Yuntao; Chen, Jubing

2015-02-01

In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random

Supervised Filter Learning for Representation Based Face Recognition.

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Chao Bi

Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

Energy Based Clutter Filtering for Vector Flow Imaging

DEFF Research Database (Denmark)

Villagómez Hoyos, Carlos Armando; Jensen, Jonas; Ewertsen, Caroline

2017-01-01

for obtaining vector flow measurements, since the spectra overlaps at high beam-to-flow angles. In this work a distinct approach is proposed, where the energy of the velocity spectrum is used to differentiate among the two signals. The energy based method is applied by limiting the amplitude of the velocity...... spectrum function to a predetermined threshold. The effect of the clutter filtering is evaluated on a plane wave (PW) scan sequence in combination with transverse oscillation (TO) and directional beamforming (DB) for velocity estimation. The performance of the filter is assessed by comparison...

Superresolution restoration of an image sequence: adaptive filtering approach.

Science.gov (United States)

Elad, M; Feuer, A

1999-01-01

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

Improving the quality of brain CT image from Wavelet filters

International Nuclear Information System (INIS)

Pita Machado, Reinaldo; Perez Diaz, Marlen; Bravo Pino, Rolando

2012-01-01

An algorithm to reduce Poisson noise is described using Wavelet filters. Five tomographic images of patients and a head anthropomorphic phantom were used. They were acquired with two different CT machines. Due to the original images contain the acquisition noise; some simulated free noise lesions were added to the images and after that the whole images were contaminated with noise. Contaminated images were filtered with 9 Wavelet filters at different decomposition levels and thresholds. Image quality of filtered and unfiltered images was graded using the Signal to Noise ratio, Normalized Mean Square Error and the Structural Similarity Index, as well as, by the subjective JAFROC methods with 5 observers. Some filters as Bior 3.7 and dB45 improved in a significant way head CT image quality (p<0.05) producing an increment in SNR without visible structural distortions

Spectral characterization in deep UV of an improved imaging KDP acousto-optic tunable filter

International Nuclear Information System (INIS)

Gupta, Neelam; Voloshinov, Vitaly

2014-01-01

Recently, we developed a number of high quality noncollinear acousto-optic tunable filter (AOTF) cells in different birefringent materials with UV imaging capability. Cells based on a single crystal of KDP (potassium dihydrophosphate) had the best transmission efficiency and the optical throughput needed to acquire high quality spectral images at wavelengths above 220 nm. One of the main limitations of these imaging filters was their small angular aperture in air, limited to about 1.0°. In this paper, we describe an improved imaging KDP AOTF operating from the deep UV to the visible region of the spectrum. The linear and angular apertures of the new filter are 10 × 10 mm 2 and 1.8°, respectively. The spectral tuning range is 205–430 nm with a 60 cm −1 spectral resolution. We describe the filter and present experimental results on imaging using both a broadband source and a number of light emitting diodes (LEDs) in the UV, and include the measured spectra of these LEDs obtained with a collinear SiO 2 filter-based spectrometer operating above 255 nm. (paper)

Optimization of Butterworth filter for brain SPECT imaging

International Nuclear Information System (INIS)

Minoshima, Satoshi; Maruno, Hirotaka; Yui, Nobuharu

1993-01-01

A method has been described to optimize the cutoff frequency of the Butterworth filter for brain SPECT imaging. Since a computer simulation study has demonstrated that separation between an object signal and the random noise in projection images in a spatial-frequency domain is influenced by the total number of counts, the cutoff frequency of the Butterworth filter should be optimized for individual subjects according to total counts in a study. To reveal the relationship between the optimal cutoff frequencies and total counts in brain SPECT study, we used a normal volunteer and 99m Tc hexamethyl-propyleneamine oxime (HMPAO) to obtain projection sets with different total counts. High quality images were created from a projection set with an acquisition time of 300-seconds per projection. The filter was optimized by calculating mean square errors from high quality images visually inspecting filtered reconstructed images. Dependence between total counts and optimal cutoff frequencies was clearly demonstrated in a nomogram. Using this nomogram, the optimal cutoff frequency for each study can be estimated from total counts, maximizing visual image quality. The results suggest that the cutoff frequency of Butterworth filter should be determined by referring to total counts in each study. (author)

The value of filtered planar images in pediatric DMSA scans

International Nuclear Information System (INIS)

Mohammed, A.M.; Naddaf, S.Y.; Elgazzar, A.H.; Al-Abdul Salam, A.A.; Omar, A.A.

2006-01-01

The study was designed to demonstrate the value of filtered planar images in paediatric DMSA scanning. One hundred and seventy three patients ranged in age from 15 days to 12 years (mean: 4.3 years) with urinary tract infection (UTI) and clinical and/or laboratory suspicion of acute pyelonephritis (APN) were retrospectively studied. Planar images were filtered using Butterworth filter. The scan findings were reported as positive, negative or equivocal for cortical defects. Each scan was read in a double-blind fashion by two nuclear medicine physicians to evaluate inter-observer variations. Each kidney was divided into three zones, upper, middle and lower, and each zone was graded as positive, negative or equivocal for the presence of renal defects. Renal cortical defects were found in 66 patients (91 kidneys and 186 zones) with filtered images, 58 patients (81 kidneys and 175 zones) with planar images, and 69 patients (87 kidneys and 180 zones) with SPECT images. McNemar's test revealed statistically significant difference between filtered and planar images (p=0.038 for patients, 0.021 for kidneys and 0.034 for number of zones). Inter-observer agreement was 0.877 for filtered images, 0.915 for planar images and 0.915 for SPECT images. It was concluded that filtered planar images of renal cortex are comparable to SPECT images and can be used effectively in place of SPECT, when required, to shorten imaging time and eliminate motion artifacts, especially in the paediatric population. (author)

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Matched Filtering and Convolutional Neural Network.

Science.gov (United States)

Chen, Shuo; Luo, Chenggao; Wang, Hongqiang; Deng, Bin; Cheng, Yongqiang; Zhuang, Zhaowen

2018-04-26

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. However, there are still two problems in three-dimensional (3D) TCAI. Firstly, the large-scale reference-signal matrix based on meshing the 3D imaging area creates a heavy computational burden, thus leading to unsatisfactory efficiency. Secondly, it is difficult to resolve the target under low signal-to-noise ratio (SNR). In this paper, we propose a 3D imaging method based on matched filtering (MF) and convolutional neural network (CNN), which can reduce the computational burden and achieve high-resolution imaging for low SNR targets. In terms of the frequency-hopping (FH) signal, the original echo is processed with MF. By extracting the processed echo in different spike pulses separately, targets in different imaging planes are reconstructed simultaneously to decompose the global computational complexity, and then are synthesized together to reconstruct the 3D target. Based on the conventional TCAI model, we deduce and build a new TCAI model based on MF. Furthermore, the convolutional neural network (CNN) is designed to teach the MF-TCAI how to reconstruct the low SNR target better. The experimental results demonstrate that the MF-TCAI achieves impressive performance on imaging ability and efficiency under low SNR. Moreover, the MF-TCAI has learned to better resolve the low-SNR 3D target with the help of CNN. In summary, the proposed 3D TCAI can achieve: (1) low-SNR high-resolution imaging by using MF; (2) efficient 3D imaging by downsizing the large-scale reference-signal matrix; and (3) intelligent imaging with CNN. Therefore, the TCAI based on MF and CNN has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

An approach of point cloud denoising based on improved bilateral filtering

Science.gov (United States)

Zheng, Zeling; Jia, Songmin; Zhang, Guoliang; Li, Xiuzhi; Zhang, Xiangyin

2018-04-01

An omnidirectional mobile platform is designed for building point cloud based on an improved filtering algorithm which is employed to handle the depth image. First, the mobile platform can move flexibly and the control interface is convenient to control. Then, because the traditional bilateral filtering algorithm is time-consuming and inefficient, a novel method is proposed which called local bilateral filtering (LBF). LBF is applied to process depth image obtained by the Kinect sensor. The results show that the effect of removing noise is improved comparing with the bilateral filtering. In the condition of off-line, the color images and processed images are used to build point clouds. Finally, experimental results demonstrate that our method improves the speed of processing time of depth image and the effect of point cloud which has been built.

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.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

International Nuclear Information System (INIS)

Iliopoulos, AS; Sun, X; Floros, D; Zhang, Y; Yin, FF; Ren, L; Pitsianis, N

2016-01-01

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

Energy Technology Data Exchange (ETDEWEB)

Iliopoulos, AS; Sun, X [Duke University, Durham, NC (United States); Floros, D [Aristotle University of Thessaloniki (Greece); Zhang, Y; Yin, FF; Ren, L [Duke University Medical Center, Durham, NC (United States); Pitsianis, N [Aristotle University of Thessaloniki (Greece); Duke University, Durham, NC (United States)

2016-06-15

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial

A diagnostic imaging approach for online characterization of multi-impact in aircraft composite structures based on a scanning spatial-wavenumber filter of guided wave

Science.gov (United States)

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Su, Zhongqing

2017-06-01

Monitoring of impact and multi-impact in particular in aircraft composite structures has been an intensive research topic in the field of guided-wave-based structural health monitoring (SHM). Compared with the majority of existing methods such as those using signal features in the time-, frequency- or joint time-frequency domain, the approach based on spatial-wavenumber filter of guided wave shows superb advantage in effectively distinguishing particular wave modes and identifying their propagation direction relative to the sensor array. However, there exist two major issues when conducting online characterization of multi-impact event. Firstly, the spatial-wavenumber filter should be realized in the situation that the wavenumber of high spatial resolution of the complicated multi-impact signal cannot be measured or modeled. Secondly, it's difficult to identify the multiple impacts and realize multi-impact localization due to the overlapping of wavenumbers. To address these issues, a scanning spatial-wavenumber filter based diagnostic imaging method for online characterization of multi-impact event is proposed to conduct multi-impact imaging and localization in this paper. The principle of the scanning filter for multi-impact is developed first to conduct spatial-wavenumber filtering and to achieve wavenumber-time imaging of the multiple impacts. Then, a feature identification method of multi-impact based on eigenvalue decomposition and wavenumber searching is presented to estimate the number of impacts and calculate the wavenumber of the multi-impact signal, and an image mapping method is proposed as well to convert the wavenumber-time image to an angle-distance image to distinguish and locate the multiple impacts. A series of multi-impact events are applied to a carbon fiber laminate plate to validate the proposed methods. The validation results show that the localization of the multiple impacts are well achieved.

Implementation of non-linear filters for iterative penalized maximum likelihood image reconstruction

International Nuclear Information System (INIS)

Liang, Z.; Gilland, D.; Jaszczak, R.; Coleman, R.

1990-01-01

In this paper, the authors report on the implementation of six edge-preserving, noise-smoothing, non-linear filters applied in image space for iterative penalized maximum-likelihood (ML) SPECT image reconstruction. The non-linear smoothing filters implemented were the median filter, the E 6 filter, the sigma filter, the edge-line filter, the gradient-inverse filter, and the 3-point edge filter with gradient-inverse filter, and the 3-point edge filter with gradient-inverse weight. A 3 x 3 window was used for all these filters. The best image obtained, by viewing the profiles through the image in terms of noise-smoothing, edge-sharpening, and contrast, was the one smoothed with the 3-point edge filter. The computation time for the smoothing was less than 1% of one iteration, and the memory space for the smoothing was negligible. These images were compared with the results obtained using Bayesian analysis

Multi-dimensional medical images compressed and filtered with wavelets

International Nuclear Information System (INIS)

Boyen, H.; Reeth, F. van; Flerackers, E.

2002-01-01

Full text: Using the standard wavelet decomposition methods, multi-dimensional medical images can be compressed and filtered by repeating the wavelet-algorithm on 1D-signals in an extra loop per extra dimension. In the non-standard decomposition for multi-dimensional images the areas that must be zero-filled in case of band- or notch-filters are more complex than geometric areas such as rectangles or cubes. Adding an additional dimension in this algorithm until 4D (e.g. a 3D beating heart) increases the geometric complexity of those areas even more. The aim of our study was to calculate the boundaries of the formed complex geometric areas, so we can use the faster non-standard decomposition to compress and filter multi-dimensional medical images. Because a lot of 3D medical images taken by PET- or SPECT-cameras have only a few layers in the Z-dimension and compressing images in a dimension with a few voxels is usually not worthwhile, we provided a solution in which one can choose which dimensions will be compressed or filtered. With the proposal of non-standard decomposition on Daubechies' wavelets D2 to D20 by Steven Gollmer in 1992, 1D data can be compressed and filtered. Each additional level works only on the smoothed data, so the transformation-time halves per extra level. Zero-filling a well-defined area alter the wavelet-transform and then performing the inverse transform will do the filtering. To be capable to compress and filter up to 4D-Images with the faster non-standard wavelet decomposition method, we have investigated a new method for calculating the boundaries of the areas which must be zero-filled in case of filtering. This is especially true for band- and notch filtering. Contrary to the standard decomposition method, the areas are no longer rectangles in 2D or cubes in 3D or a row of cubes in 4D: they are rectangles expanded with a half-sized rectangle in the other direction for 2D, cubes expanded with half cubes in one and quarter cubes in the

Comparison of various filtering methods for digital X-ray image processing

International Nuclear Information System (INIS)

Pfluger, T.; Reinfelder, H.E.; Dorschky, K.; Oppelt, A.; Siemens A.G., Erlangen

1987-01-01

Three filtering methods are explained and compared that are used for border edge enhancement of digitally processed X-ray images. The filters are compared by two examples, a radiograph of the chest, and one of the knee joint. The unsharpness mask is found to yield the best compromise between edge enhancement and image noise intensifying effect, whereas the results obtained by the high-pass filter or the Wallis filter are less good for diagnostic evaluation. The filtered images better display narrow lines, structural borders and edges, and finely spotted areas, than the original radiograph, so that diagnostic evaluation is easier after image filtering. (orig.) [de

[Restoration filtering based on projection power spectrum for single-photon emission computed tomography].

Science.gov (United States)

Kubo, N

1995-04-01

To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical "least squares filter" theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the "Butterworth" filtering method (cut-off frequency of 0.15 cycles/pixel), and "Wiener" filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99mTc filled cylinder, were used. NMSE of the "Butterworth" filter, "Wiener" filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images.

Restoration filtering based on projection power spectrum for single-photon emission computed tomography

International Nuclear Information System (INIS)

Kubo, Naoki

1995-01-01

To improve the quality of single-photon emission computed tomographic (SPECT) images, a restoration filter has been developed. This filter was designed according to practical 'least squares filter' theory. It is necessary to know the object power spectrum and the noise power spectrum. The power spectrum is estimated from the power spectrum of a projection, when the high-frequency power spectrum of a projection is adequately approximated as a polynomial exponential expression. A study of the restoration with the filter based on a projection power spectrum was conducted, and compared with that of the 'Butterworth' filtering method (cut-off frequency of 0.15 cycles/pixel), and 'Wiener' filtering (signal-to-noise power spectrum ratio was a constant). Normalized mean-squared errors (NMSE) of the phantom, two line sources located in a 99m Tc filled cylinder, were used. NMSE of the 'Butterworth' filter, 'Wiener' filter, and filtering based on a power spectrum were 0.77, 0.83, and 0.76 respectively. Clinically, brain SPECT images utilizing this new restoration filter improved the contrast. Thus, this filter may be useful in diagnosis of SPECT images. (author)

Iodine filter imaging system for subtraction angiography using synchrotron radiation

Science.gov (United States)

Umetani, K.; Ueda, K.; Takeda, T.; Itai, Y.; Akisada, M.; Nakajima, T.

1993-11-01

A new type of real-time imaging system was developed for transvenous coronary angiography. A combination of an iodine filter and a single energy broad-bandwidth X-ray produces two-energy images for the iodine K-edge subtraction technique. X-ray images are sequentially converted to visible images by an X-ray image intensifier. By synchronizing the timing of the movement of the iodine filter into and out of the X-ray beam, two output images of the image intensifier are focused side by side on the photoconductive layer of a camera tube by an oscillating mirror. Both images are read out by electron beam scanning of a 1050-scanning-line video camera within a camera frame time of 66.7 ms. One hundred ninety two pairs of iodine-filtered and non-iodine-filtered images are stored in the frame memory at a rate of 15 pairs/s. In vivo subtracted images of coronary arteries in dogs were obtained in the form of motion pictures.

Chip-scale fluorescence microscope based on a silo-filter complementary metal-oxide semiconductor image sensor.

Science.gov (United States)

Ah Lee, Seung; Ou, Xiaoze; Lee, J Eugene; Yang, Changhuei

2013-06-01

We demonstrate a silo-filter (SF) complementary metal-oxide semiconductor (CMOS) image sensor for a chip-scale fluorescence microscope. The extruded pixel design with metal walls between neighboring pixels guides fluorescence emission through the thick absorptive filter to the photodiode of a pixel. Our prototype device achieves 13 μm resolution over a wide field of view (4.8 mm × 4.4 mm). We demonstrate bright-field and fluorescence longitudinal imaging of living cells in a compact, low-cost configuration.

Methods of filtering the graph images of the functions

Directory of Open Access Journals (Sweden)

Олександр Григорович Бурса

2017-06-01

Full Text Available The theoretical aspects of cleaning raster images of scanned graphs of functions from digital, chromatic and luminance distortions by using computer graphics techniques have been considered. The basic types of distortions characteristic of graph images of functions have been stated. To suppress the distortion several methods, providing for high-quality of the resulting images and saving their topological features, were suggested. The paper describes the techniques developed and improved by the authors: the method of cleaning the image of distortions by means of iterative contrasting, based on the step-by-step increase in image contrast in the graph by 1%; the method of small entities distortion restoring, based on the thinning of the known matrix of contrast increase filter (the allowable dimensions of the nucleus dilution radius convolution matrix, which provide for the retention of the graph lines have been established; integration technique of the noise reduction method by means of contrasting and distortion restoring method of small entities with known σ-filter. Each method in the complex has been theoretically substantiated. The developed methods involve treatment of graph images as the entire image (global processing and its fragments (local processing. The metrics assessing the quality of the resulting image with the global and local processing have been chosen, the substantiation of the choice as well as the formulas have been given. The proposed complex methods of cleaning the graphs images of functions from grayscale image distortions is adaptive to the form of an image carrier, the distortion level in the image and its distribution. The presented results of testing the developed complex of methods for a representative sample of images confirm its effectiveness

Optical supervised filtering technique based on Hopfield neural network

Science.gov (United States)

Bal, Abdullah

2004-11-01

Hopfield neural network is commonly preferred for optimization problems. In image segmentation, conventional Hopfield neural networks (HNN) are formulated as a cost-function-minimization problem to perform gray level thresholding on the image histogram or the pixels' gray levels arranged in a one-dimensional array [R. Sammouda, N. Niki, H. Nishitani, Pattern Rec. 30 (1997) 921-927; K.S. Cheng, J.S. Lin, C.W. Mao, IEEE Trans. Med. Imag. 15 (1996) 560-567; C. Chang, P. Chung, Image and Vision comp. 19 (2001) 669-678]. In this paper, a new high speed supervised filtering technique is proposed for image feature extraction and enhancement problems by modifying the conventional HNN. The essential improvement in this technique is to use 2D convolution operation instead of weight-matrix multiplication. Thereby, neural network based a new filtering technique has been obtained that is required just 3 × 3 sized filter mask matrix instead of large size weight coefficient matrix. Optical implementation of the proposed filtering technique is executed easily using the joint transform correlator. The requirement of non-negative data for optical implementation is provided by bias technique to convert the bipolar data to non-negative data. Simulation results of the proposed optical supervised filtering technique are reported for various feature extraction problems such as edge detection, corner detection, horizontal and vertical line extraction, and fingerprint enhancement.

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

Science.gov (United States)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

Filters in 2D and 3D Cardiac SPECT Image Processing

Directory of Open Access Journals (Sweden)

Maria Lyra

2014-01-01

Full Text Available Nuclear cardiac imaging is a noninvasive, sensitive method providing information on cardiac structure and physiology. Single photon emission tomography (SPECT evaluates myocardial perfusion, viability, and function and is widely used in clinical routine. The quality of the tomographic image is a key for accurate diagnosis. Image filtering, a mathematical processing, compensates for loss of detail in an image while reducing image noise, and it can improve the image resolution and limit the degradation of the image. SPECT images are then reconstructed, either by filter back projection (FBP analytical technique or iteratively, by algebraic methods. The aim of this study is to review filters in cardiac 2D, 3D, and 4D SPECT applications and how these affect the image quality mirroring the diagnostic accuracy of SPECT images. Several filters, including the Hanning, Butterworth, and Parzen filters, were evaluated in combination with the two reconstruction methods as well as with a specified MatLab program. Results showed that for both 3D and 4D cardiac SPECT the Butterworth filter, for different critical frequencies and orders, produced the best results. Between the two reconstruction methods, the iterative one might be more appropriate for cardiac SPECT, since it improves lesion detectability due to the significant improvement of image contrast.

Document image binarization using "multi-scale" predefined filters

Science.gov (United States)

Saabni, Raid M.

2018-04-01

Reading text or searching for key words within a historical document is a very challenging task. one of the first steps of the complete task is binarization, where we separate foreground such as text, figures and drawings from the background. Successful results of this important step in many cases can determine next steps to success or failure, therefore it is very vital to the success of the complete task of reading and analyzing the content of a document image. Generally, historical documents images are of poor quality due to their storage condition and degradation over time, which mostly cause to varying contrasts, stains, dirt and seeping ink from reverse side. In this paper, we use banks of anisotropic predefined filters in different scales and orientations to develop a binarization method for degraded documents and manuscripts. Using the fact, that handwritten strokes may follow different scales and orientations, we use predefined sets of filter banks having various scales, weights, and orientations to seek a compact set of filters and weights in order to generate diffrent layers of foregrounds and background. Results of convolving these fiters on the gray level image locally, weighted and accumulated to enhance the original image. Based on the different layers, seeds of components in the gray level image and a learning process, we present an improved binarization algorithm to separate the background from layers of foreground. Different layers of foreground which may be caused by seeping ink, degradation or other factors are also separated from the real foreground in a second phase. Promising experimental results were obtained on the DIBCO2011 , DIBCO2013 and H-DIBCO2016 data sets and a collection of images taken from real historical documents.

A Low-Noise CMOS THz Imager Based on Source Modulation and an In-Pixel High-Q Passive Switched-Capacitor N-Path Filter

Science.gov (United States)

Boukhayma, Assim; Dupret, Antoine; Rostaing, Jean-Pierre; Enz, Christian

2016-01-01

This paper presents the first low noise complementary metal oxide semiconductor (CMOS) terahertz (THz) imager based on source modulation and in-pixel high-Q filtering. The 31×31 focal plane array has been fully integrated in a 0.13μm standard CMOS process. The sensitivity has been improved significantly by modulating the active THz source that lights the scene and performing on-chip high-Q filtering. Each pixel encompass a broadband bow tie antenna coupled to an N-type metal-oxide-semiconductor (NMOS) detector that shifts the THz radiation, a low noise adjustable gain amplifier and a high-Q filter centered at the modulation frequency. The filter is based on a passive switched-capacitor (SC) N-path filter combined with a continuous-time broad-band Gm-C filter. A simplified analysis that helps in designing and tuning the passive SC N-path filter is provided. The characterization of the readout chain shows that a Q factor of 100 has been achieved for the filter with a good matching between the analytical calculation and the measurement results. An input-referred noise of 0.2μV RMS has been measured. Characterization of the chip with different THz wavelengths confirms the broadband feature of the antenna and shows that this THz imager reaches a total noise equivalent power of 0.6 nW at 270 GHz and 0.8 nW at 600 GHz. PMID:26950131

A Low-Noise CMOS THz Imager Based on Source Modulation and an In-Pixel High-Q Passive Switched-Capacitor N-Path Filter.

Science.gov (United States)

Boukhayma, Assim; Dupret, Antoine; Rostaing, Jean-Pierre; Enz, Christian

2016-03-03

This paper presents the first low noise complementary metal oxide semiconductor (CMOS) deletedCMOS terahertz (THz) imager based on source modulation and in-pixel high-Q filtering. The 31 × 31 focal plane array has been fully integrated in a 0 . 13 μ m standard CMOS process. The sensitivity has been improved significantly by modulating the active THz source that lights the scene and performing on-chip high-Q filtering. Each pixel encompass a broadband bow tie antenna coupled to an N-type metal-oxide-semiconductor (NMOS) detector that shifts the THz radiation, a low noise adjustable gain amplifier and a high-Q filter centered at the modulation frequency. The filter is based on a passive switched-capacitor (SC) N-path filter combined with a continuous-time broad-band Gm-C filter. A simplified analysis that helps in designing and tuning the passive SC N-path filter is provided. The characterization of the readout chain shows that a Q factor of 100 has been achieved for the filter with a good matching between the analytical calculation and the measurement results. An input-referred noise of 0 . 2 μ V RMS has been measured. Characterization of the chip with different THz wavelengths confirms the broadband feature of the antenna and shows that this THz imager reaches a total noise equivalent power of 0 . 6 nW at 270 GHz and 0 . 8 nW at 600 GHz.

Fan-beam and cone-beam image reconstruction via filtering the backprojection image of differentiated projection data

International Nuclear Information System (INIS)

Zhuang Tingliang; Leng Shuai; Nett, Brian E; Chen Guanghong

2004-01-01

In this paper, a new image reconstruction scheme is presented based on Tuy's cone-beam inversion scheme and its fan-beam counterpart. It is demonstrated that Tuy's inversion scheme may be used to derive a new framework for fan-beam and cone-beam image reconstruction. In this new framework, images are reconstructed via filtering the backprojection image of differentiated projection data. The new framework is mathematically exact and is applicable to a general source trajectory provided the Tuy data sufficiency condition is satisfied. By choosing a piece-wise constant function for one of the components in the factorized weighting function, the filtering kernel is one dimensional, viz. the filtering process is along a straight line. Thus, the derived image reconstruction algorithm is mathematically exact and efficient. In the cone-beam case, the derived reconstruction algorithm is applicable to a large class of source trajectories where the pi-lines or the generalized pi-lines exist. In addition, the new reconstruction scheme survives the super-short scan mode in both the fan-beam and cone-beam cases provided the data are not transversely truncated. Numerical simulations were conducted to validate the new reconstruction scheme for the fan-beam case

Detection of pulmonary nodules on lung X-ray images. Studies on multi-resolutional filter and energy subtraction images

International Nuclear Information System (INIS)

Sawada, Akira; Sato, Yoshinobu; Kido, Shoji; Tamura, Shinichi

1999-01-01

The purpose of this work is to prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Ribs and vessels are major causes of CAD errors in detection of pulmonary nodules and many researches have tried to solve this problem. So we select conventional X-ray images and energy subtraction X-ray images as types of images, and at the same time select ∇ 2 G (Laplacian of Guassian) filter, Min-DD (Minimum Directional Difference) filter and our multi-resolutional filter as types of digital filters. Also we select two evaluation methods and prove the effectiveness of an energy subtraction image, the effectiveness of Min-DD filter on a conventional X-ray image and the effectiveness of multi-resolutional filter on an energy subtraction image. (author)

Efficient Hardware Implementation For Fingerprint Image Enhancement Using Anisotropic Gaussian Filter.

Science.gov (United States)

Khan, Tariq Mahmood; Bailey, Donald G; Khan, Mohammad A U; Kong, Yinan

2017-05-01

A real-time image filtering technique is proposed which could result in faster implementation for fingerprint image enhancement. One major hurdle associated with fingerprint filtering techniques is the expensive nature of their hardware implementations. To circumvent this, a modified anisotropic Gaussian filter is efficiently adopted in hardware by decomposing the filter into two orthogonal Gaussians and an oriented line Gaussian. An architecture is developed for dynamically controlling the orientation of the line Gaussian filter. To further improve the performance of the filter, the input image is homogenized by a local image normalization. In the proposed structure, for a middle-range reconfigurable FPGA, both parallel compute-intensive and real-time demands were achieved. We manage to efficiently speed up the image-processing time and improve the resource utilization of the FPGA. Test results show an improved speed for its hardware architecture while maintaining reasonable enhancement benchmarks.

A METHOD FOR RECORDING AND VIEWING STEREOSCOPIC IMAGES IN COLOUR USING MULTICHROME FILTERS

DEFF Research Database (Denmark)

2000-01-01

in a conventional stereogram recorded of the scene. The invention makes use of a colour-based encoding technique and viewing filters selected so that the human observer receives, in one eye, an image of nearly full colour information, in the other eye, an essentially monochrome image supplying the parallactic......The aim of the invention is to create techniques for the encoding, production and viewing of stereograms, supplemented by methods for selecting certain optical filters needed in these novel techniques, thus providing a human observer with stereograms each of which consist of a single image...

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.; Schönlieb, C.-B.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

Oriented diffusion filtering for enhancing low-quality fingerprint images

KAUST Repository

Gottschlich, C.

2012-01-01

To enhance low-quality fingerprint images, we present a novel method that first estimates the local orientation of the fingerprint ridge and valley flow and next performs oriented diffusion filtering, followed by a locally adaptive contrast enhancement step. By applying the authors\\' new approach to low-quality images of the FVC2004 fingerprint databases, the authors are able to show its competitiveness with other state-of-the-art enhancement methods for fingerprints like curved Gabor filtering. A major advantage of oriented diffusion filtering over those is its computational efficiency. Combining oriented diffusion filtering with curved Gabor filters led to additional improvements and, to the best of the authors\\' knowledge, the lowest equal error rates achieved so far using MINDTCT and BOZORTH3 on the FVC2004 databases. The recognition performance and the computational efficiency of the method suggest to include oriented diffusion filtering as a standard image enhancement add-on module for real-time fingerprint recognition systems. In order to facilitate the reproduction of these results, an implementation of the oriented diffusion filtering for Matlab and GNU Octave is made available for download. © 2012 The Institution of Engineering and Technology.

Eigenimage filtering of nuclear medicine image sequences

International Nuclear Information System (INIS)

Windham, J.P.; Froelich, J.W.; Abd-Allah, M.

1985-01-01

In many nuclear medicine imaging sequences the localization of radioactivity in organs other than the target organ interferes with imaging of the desired anatomical structure or physiological process. A filtering technique has been developed which suppresses the interfering process while enhancing the desired process. This technique requires the identification of temporal sequential signatures for both the interfering and desired processes. These signatures are placed in the form of signature vectors. Signature matrices, M/sub D/ and M/sub U/, are formed by taking the outer product expansion of the temporal signature vectors for the desired and interfering processes respectively. By using the transformation from the simultaneous diagonalization of these two signature matrices a weighting vector is obtained. The technique is shown to maximize the projection of the desired process while minimizing the interfering process based upon an extension of Rayleigh's Principle. The technique is demonstrated for first pass renal and cardiac flow studies. This filter offers a potential for simplifying and extending the accuracy of diagnostic nuclear medicine procedures

A Kalman Filter-Based Method to Generate Continuous Time Series of Medium-Resolution NDVI Images

Directory of Open Access Journals (Sweden)

Fernando Sedano

2014-12-01

Full Text Available A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing than individually at forward and backward recursions (filtering. Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.

Computer processing of the scintigraphic image using digital filtering techniques

International Nuclear Information System (INIS)

Matsuo, Michimasa

1976-01-01

The theory of digital filtering was studied as a method for the computer processing of scintigraphic images. The characteristics and design techniques of finite impulse response (FIR) digital filters with linear phases were examined using the z-transform. The conventional data processing method, smoothing, could be recognized as one kind of linear phase FIR low-pass digital filtering. Ten representatives of FIR low-pass digital filters with various cut-off frequencies were scrutinized from the frequency domain in one-dimension and two-dimensions. These filters were applied to phantom studies with cold targets, using a Scinticamera-Minicomputer on-line System. These studies revealed that the resultant images had a direct connection with the magnitude response of the filter, that is, they could be estimated fairly well from the frequency response of the digital filter used. The filter, which was estimated from phantom studies as optimal for liver scintigrams using 198 Au-colloid, was successfully applied in clinical use for detecting true cold lesions and, at the same time, for eliminating spurious images. (J.P.N.)

ANALYSIS OF SST IMAGES BY WEIGHTED ENSEMBLE TRANSFORM KALMAN FILTER

OpenAIRE

Sai , Gorthi; Beyou , Sébastien; Memin , Etienne

2011-01-01

International audience; This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based onWeighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas of ...

Human visual modeling and image deconvolution by linear filtering

International Nuclear Information System (INIS)

Larminat, P. de; Barba, D.; Gerber, R.; Ronsin, J.

1978-01-01

The problem is the numerical restoration of images degraded by passing through a known and spatially invariant linear system, and by the addition of a stationary noise. We propose an improvement of the Wiener's filter to allow the restoration of such images. This improvement allows to reduce the important drawbacks of classical Wiener's filter: the voluminous data processing, the lack of consideration of the vision's characteristivs which condition the perception by the observer of the restored image. In a first paragraph, we describe the structure of the visual detection system and a modelling method of this system. In the second paragraph we explain a restoration method by Wiener filtering that takes the visual properties into account and that can be adapted to the local properties of the image. Then the results obtained on TV images or scintigrams (images obtained by a gamma-camera) are commented [fr

Chromatic aberrations correction for imaging spectrometer based on acousto-optic tunable filter with two transducers.

Science.gov (United States)

Zhao, Huijie; Wang, Ziye; Jia, Guorui; Zhang, Ying; Xu, Zefu

2017-10-02

The acousto-optic tunable filter (AOTF) with wide wavelength range and high spectral resolution has long crystal and two transducers. A longer crystal length leads to a bigger chromatic focal shift and the double-transducer arrangement induces angular mutation in diffracted beam, which increase difficulty in longitudinal and lateral chromatic aberration correction respectively. In this study, the two chromatic aberrations are analyzed quantitatively based on an AOTF optical model and a novel catadioptric dual-path configuration is proposed to correct both the chromatic aberrations. The test results exhibit effectiveness of the optical configuration for this type of AOTF-based imaging spectrometer.

Neutron Imaging of Diesel Particulate Filters

International Nuclear Information System (INIS)

Strzelec, Andrea; Bilheux, Hassina Z.; Finney, Charles E.A.; Daw, C. Stuart; Foster, Dave; Rutland, Christopher J.; Schillinger, Burkhard; Schulz, Michael

2009-01-01

This article presents nondestructive neutron computed tomography (nCT) measurements of Diesel Particulate Filters (DPFs) as a method to measure ash and soot loading in the filters. Uncatalyzed and unwashcoated 200cpsi cordierite DPFs exposed to 100% biodiesel (B100) exhaust and conventional ultra low sulfur 2007 certification diesel (ULSD) exhaust at one speed-load point (1500rpm, 2.6bar BMEP) are compared to a brand new (never exposed) filter. Precise structural information about the substrate as well as an attempt to quantify soot and ash loading in the channel of the DPF illustrates the potential strength of the neutron imaging technique

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Active filtering applied to radiographic images unfolded by the Richardson-Lucy algorithm

International Nuclear Information System (INIS)

Almeida, Gevaldo L. de; Silvani, Maria Ines; Lopes, Ricardo T.

2011-01-01

Degradation of images caused by systematic uncertainties can be reduced when one knows the features of the spoiling agent. Typical uncertainties of this kind arise in radiographic images due to the non - zero resolution of the detector used to acquire them, and from the non-punctual character of the source employed in the acquisition, or from the beam divergence when extended sources are used. Both features blur the image, which, instead of a single point exhibits a spot with a vanishing edge, reproducing hence the point spread function - PSF of the system. Once this spoiling function is known, an inverse problem approach, involving inversion of matrices, can then be used to retrieve the original image. As these matrices are generally ill-conditioned, due to statistical fluctuation and truncation errors, iterative procedures should be applied, such as the Richardson-Lucy algorithm. This algorithm has been applied in this work to unfold radiographic images acquired by transmission of thermal neutrons and gamma-rays. After this procedure, the resulting images undergo an active filtering which fairly improves their final quality at a negligible cost in terms of processing time. The filter ruling the process is based on the matrix of the correction factors for the last iteration of the deconvolution procedure. Synthetic images degraded with a known PSF, and undergone to the same treatment, have been used as benchmark to evaluate the soundness of the developed active filtering procedure. The deconvolution and filtering algorithms have been incorporated to a Fortran program, written to deal with real images, generate the synthetic ones and display both. (author)

Adaptive multiresolution Hermite-Binomial filters for image edge and texture analysis

NARCIS (Netherlands)

Gu, Y.H.; Katsaggelos, A.K.

1994-01-01

A new multiresolution image analysis approach using adaptive Hermite-Binomial filters is presented in this paper. According to the local image structural and textural properties, the analysis filter kernels are made adaptive both in their scales and orders. Applications of such an adaptive filtering

Static Hyperspectral Fluorescence Imaging of Viscous Materials Based on a Linear Variable Filter Spectrometer

Directory of Open Access Journals (Sweden)

Alexander W. Koch

2013-09-01

Full Text Available This paper presents a low-cost hyperspectral measurement setup in a new application based on fluorescence detection in the visible (Vis wavelength range. The aim of the setup is to take hyperspectral fluorescence images of viscous materials. Based on these images, fluorescent and non-fluorescent impurities in the viscous materials can be detected. For the illumination of the measurement object, a narrow-band high-power light-emitting diode (LED with a center wavelength of 370 nm was used. The low-cost acquisition unit for the imaging consists of a linear variable filter (LVF and a complementary metal oxide semiconductor (CMOS 2D sensor array. The translucent wavelength range of the LVF is from 400 nm to 700 nm. For the confirmation of the concept, static measurements of fluorescent viscous materials with a non-fluorescent impurity have been performed and analyzed. With the presented setup, measurement surfaces in the micrometer range can be provided. The measureable minimum particle size of the impurities is in the nanometer range. The recording rate for the measurements depends on the exposure time of the used CMOS 2D sensor array and has been found to be in the microsecond range.

Energy-filtered Photoelectron Emission Microscopy (EF-PEEM) for imaging nanoelectronic materials

International Nuclear Information System (INIS)

Renault, Olivier; Chabli, Amal

2007-01-01

Photoelectron-Emission Microscopy (PEEM) is the most promising approach to photoemission-based (XPS, UPS) imaging techniques with high lateral resolution, typically below 100 nm. It has now reached its maturity with a new generation of instruments with energy-filtering capabilities. Therefore UPS and XPS imaging with energy-filtered PEEM (EF-PEEM) can be applied to technologically-relevant samples. UPS images with contrast in local work function, obtained with laboratory UV sources, are obtained in ultra-high vacuum environment with lateral resolutions better than 50 nm and sensitivies of 20 meV. XPS images with elemental and bonding state contrast can show up lateral resolution better than 200 nm with synchrotron excitation. In this paper, we present the principles and capabilities of EF-PEEM and nanospectroscopy. Then, we focus on an example of application to non-destructive work-function imaging of polycrystalline copper for advanced interconnects, where it is shown that EF-PEEM is an alternative to Kelvin probes

An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Kai Hu

2015-01-01

Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.

Use of morphologic filters in the computerized detection of lung nodules in digital chest images

International Nuclear Information System (INIS)

Yoshimura, H.; Giger, M.L.; Doi, K.; Ahn, N.; MacMahon, H.

1989-01-01

The authors have previously described a computerized scheme for the detection of lung nodules based on a difference-image approach, which had a detection accuracy of 70% with 7--8 false positives per image. Currently, they are investigating morphologic filters for the further enhancement/suppression of nodule-signals and the removal of false-positives. Gray-level morphologic filtering is performed on clinical chest radiographs digitized with an optical drum scanner. Various shapes and sequences of erosion and dilation filters (i.e., determination of the minimum and maximum gray levels, respectively) were examined for signal enhancement and suppression for sue in the difference- image approach

A filtering approach to edge preserving MAP estimation of images.

Science.gov (United States)

Humphrey, David; Taubman, David

2011-05-01

The authors present a computationally efficient technique for maximum a posteriori (MAP) estimation of images in the presence of both blur and noise. The image is divided into statistically independent regions. Each region is modelled with a WSS Gaussian prior. Classical Wiener filter theory is used to generate a set of convex sets in the solution space, with the solution to the MAP estimation problem lying at the intersection of these sets. The proposed algorithm uses an underlying segmentation of the image, and a means of determining the segmentation and refining it are described. The algorithm is suitable for a range of image restoration problems, as it provides a computationally efficient means to deal with the shortcomings of Wiener filtering without sacrificing the computational simplicity of the filtering approach. The algorithm is also of interest from a theoretical viewpoint as it provides a continuum of solutions between Wiener filtering and Inverse filtering depending upon the segmentation used. We do not attempt to show here that the proposed method is the best general approach to the image reconstruction problem. However, related work referenced herein shows excellent performance in the specific problem of demosaicing.

Filter and slice thickness selection in SPECT image reconstruction

International Nuclear Information System (INIS)

Ivanovic, M.; Weber, D.A.; Wilson, G.A.; O'Mara, R.E.

1985-01-01

The choice of filter and slice thickness in SPECT image reconstruction as function of activity and linear and angular sampling were investigated in phantom and patient imaging studies. Reconstructed transverse and longitudinal spatial resolution of the system were measured using a line source in a water filled phantom. Phantom studies included measurements of the Data Spectrum phantom; clinical studies included tomographic procedures in 40 patients undergoing imaging of the temporomandibular joint. Slices of the phantom and patient images were evaluated for spatial of the phantom and patient images were evaluated for spatial resolution, noise, and image quality. Major findings include; spatial resolution and image quality improve with increasing linear sampling frequencies over the range of 4-8 mm/p in the phantom images, best spatial resolution and image quality in clinical images were observed at a linear sampling frequency of 6mm/p, Shepp and Logan filter gives the best spatial resolution for phantom studies at the lowest linear sampling frequency; smoothed Shepp and Logan filter provides best quality images without loss of resolution at higher frequencies and, spatial resolution and image quality improve with increased angular sampling frequency in the phantom at 40 c/p but appear to be independent of angular sampling frequency at 400 c/p

Improvement of natural image search engines results by emotional filtering

Directory of Open Access Journals (Sweden)

Patrice Denis

2016-04-01

Full Text Available With the Internet 2.0 era, managing user emotions is a problem that more and more actors are interested in. Historically, the first notions of emotion sharing were expressed and defined with emoticons. They allowed users to show their emotional status to others in an impersonal and emotionless digital world. Now, in the Internet of social media, every day users share lots of content with each other on Facebook, Twitter, Google+ and so on. Several new popular web sites like FlickR, Picassa, Pinterest, Instagram or DeviantArt are now specifically based on sharing image content as well as personal emotional status. This kind of information is economically very valuable as it can for instance help commercial companies sell more efficiently. In fact, with this king of emotional information, business can made where companies will better target their customers needs, and/or even sell them more products. Research has been and is still interested in the mining of emotional information from user data since then. In this paper, we focus on the impact of emotions from images that have been collected from search image engines. More specifically our proposition is the creation of a filtering layer applied on the results of such image search engines. Our peculiarity relies in the fact that it is the first attempt from our knowledge to filter image search engines results with an emotional filtering approach.

Photonics-Based Microwave Image-Reject Mixer

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Dan Zhu

2018-03-01

Full Text Available Recent developments in photonics-based microwave image-reject mixers (IRMs are reviewed with an emphasis on the pre-filtering method, which applies an optical or electrical filter to remove the undesired image, and the phase cancellation method, which is realized by introducing an additional phase to the converted image and cancelling it through coherent combination without phase shift. Applications of photonics-based microwave IRM in electronic warfare, radar systems and satellite payloads are described. The inherent challenges of implementing photonics-based microwave IRM to meet specific requirements of the radio frequency (RF system are discussed. Developmental trends of the photonics-based microwave IRM are also discussed.

Superharmonic imaging with chirp coded excitation: filtering spectrally overlapped harmonics.

Science.gov (United States)

Harput, Sevan; McLaughlan, James; Cowell, David M J; Freear, Steven

2014-11-01

Superharmonic imaging improves the spatial resolution by using the higher order harmonics generated in tissue. The superharmonic component is formed by combining the third, fourth, and fifth harmonics, which have low energy content and therefore poor SNR. This study uses coded excitation to increase the excitation energy. The SNR improvement is achieved on the receiver side by performing pulse compression with harmonic matched filters. The use of coded signals also introduces new filtering capabilities that are not possible with pulsed excitation. This is especially important when using wideband signals. For narrowband signals, the spectral boundaries of the harmonics are clearly separated and thus easy to filter; however, the available imaging bandwidth is underused. Wideband excitation is preferable for harmonic imaging applications to preserve axial resolution, but it generates spectrally overlapping harmonics that are not possible to filter in time and frequency domains. After pulse compression, this overlap increases the range side lobes, which appear as imaging artifacts and reduce the Bmode image quality. In this study, the isolation of higher order harmonics was achieved in another domain by using the fan chirp transform (FChT). To show the effect of excitation bandwidth in superharmonic imaging, measurements were performed by using linear frequency modulated chirp excitation with varying bandwidths of 10% to 50%. Superharmonic imaging was performed on a wire phantom using a wideband chirp excitation. Results were presented with and without applying the FChT filtering technique by comparing the spatial resolution and side lobe levels. Wideband excitation signals achieved a better resolution as expected, however range side lobes as high as -23 dB were observed for the superharmonic component of chirp excitation with 50% fractional bandwidth. The proposed filtering technique achieved >50 dB range side lobe suppression and improved the image quality without

Large-Scale Query-by-Image Video Retrieval Using Bloom Filters

OpenAIRE

Araujo, Andre; Chaves, Jason; Lakshman, Haricharan; Angst, Roland; Girod, Bernd

2016-01-01

We consider the problem of using image queries to retrieve videos from a database. Our focus is on large-scale applications, where it is infeasible to index each database video frame independently. Our main contribution is a framework based on Bloom filters, which can be used to index long video segments, enabling efficient image-to-video comparisons. Using this framework, we investigate several retrieval architectures, by considering different types of aggregation and different functions to ...

Denoising of MR images using FREBAS collaborative filtering

International Nuclear Information System (INIS)

Ito, Satoshi; Hizume, Masayuki; Yamada, Yoshifumi

2011-01-01

We propose a novel image denoising strategy based on the correlation in the FREBAS transformed domain. FREBAS transform is a kind of multi-resolution image analysis which consists of two different Fresnel transforms. It can decompose images into down-scaled images of the same size with a different frequency bandwidth. Since these decomposed images have similar distributions for the same directions from the center of the FREBAS domain, even when the FREBAS signal is hidden by noise in the case of a low-signal-to-noise ratio (SNR) image, the signal distribution can be estimated using the distribution of the FREBAS signal located near the position of interest. We have developed a collaborative Wiener filter in the FREBAS transformed domain which implements collaboration of the standard deviation of the position of interest and that of analogous positions. The experimental results demonstrated that the proposed algorithm improves the SNR in terms of both the total SNR and the SNR at the edges of images. (author)

M2 FILTER FOR SPECKLE NOISE SUPPRESSION IN BREAST ULTRASOUND IMAGES

Directory of Open Access Journals (Sweden)

E.S. Samundeeswari

2016-11-01

Full Text Available Breast cancer, commonly found in women is a serious life threatening disease due to its invasive nature. Ultrasound (US imaging method plays an effective role in screening early detection and diagnosis of Breast cancer. Speckle noise generally affects medical ultrasound images and also causes a number of difficulties in identifying the Region of Interest. Suppressing speckle noise is a challenging task as it destroys fine edge details. No specific filter is designed yet to get a noise free BUS image that is contaminated by speckle noise. In this paper M2 filter, a novel hybrid of linear and nonlinear filter is proposed and compared to other spatial filters with 3×3 kernel size. The performance of the proposed M2 filter is measured by statistical quantity parameters like MSE, PSNR and SSI. The experimental analysis clearly shows that the proposed M2 filter outperforms better than other spatial filters by 2% high PSNR values with regards to speckle suppression.

KALMAN FILTER BASED FEATURE ANALYSIS FOR TRACKING PEOPLE FROM AIRBORNE IMAGES

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B. Sirmacek

2012-09-01

Full Text Available Recently, analysis of man events in real-time using computer vision techniques became a very important research field. Especially, understanding motion of people can be helpful to prevent unpleasant conditions. Understanding behavioral dynamics of people can also help to estimate future states of underground passages, shopping center like public entrances, or streets. In order to bring an automated solution to this problem, we propose a novel approach using airborne image sequences. Although airborne image resolutions are not enough to see each person in detail, we can still notice a change of color components in the place where a person exists. Therefore, we propose a color feature detection based probabilistic framework in order to detect people automatically. Extracted local features behave as observations of the probability density function (pdf of the people locations to be estimated. Using an adaptive kernel density estimation method, we estimate the corresponding pdf. First, we use estimated pdf to detect boundaries of dense crowds. After that, using background information of dense crowds and previously extracted local features, we detect other people in non-crowd regions automatically for each image in the sequence. We benefit from Kalman filtering to track motion of detected people. To test our algorithm, we use a stadium entrance image data set taken from airborne camera system. Our experimental results indicate possible usage of the algorithm in real-life man events. We believe that the proposed approach can also provide crucial information to police departments and crisis management teams to achieve more detailed observations of people in large open area events to prevent possible accidents or unpleasant conditions.

HIGH-PRECISION ATTITUDE ESTIMATION METHOD OF STAR SENSORS AND GYRO BASED ON COMPLEMENTARY FILTER AND UNSCENTED KALMAN FILTER

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C. Guo

2017-07-01

Full Text Available Determining the attitude of satellite at the time of imaging then establishing the mathematical relationship between image points and ground points is essential in high-resolution remote sensing image mapping. Star tracker is insensitive to the high frequency attitude variation due to the measure noise and satellite jitter, but the low frequency attitude motion can be determined with high accuracy. Gyro, as a short-term reference to the satellite’s attitude, is sensitive to high frequency attitude change, but due to the existence of gyro drift and integral error, the attitude determination error increases with time. Based on the opposite noise frequency characteristics of two kinds of attitude sensors, this paper proposes an on-orbit attitude estimation method of star sensors and gyro based on Complementary Filter (CF and Unscented Kalman Filter (UKF. In this study, the principle and implementation of the proposed method are described. First, gyro attitude quaternions are acquired based on the attitude kinematics equation. An attitude information fusion method is then introduced, which applies high-pass filtering and low-pass filtering to the gyro and star tracker, respectively. Second, the attitude fusion data based on CF are introduced as the observed values of UKF system in the process of measurement updating. The accuracy and effectiveness of the method are validated based on the simulated sensors attitude data. The obtained results indicate that the proposed method can suppress the gyro drift and measure noise of attitude sensors, improving the accuracy of the attitude determination significantly, comparing with the simulated on-orbit attitude and the attitude estimation results of the UKF defined by the same simulation parameters.

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

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.

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

[Design Method Analysis and Performance Comparison of Wall Filter for Ultrasound Color Flow Imaging].

Science.gov (United States)

Wang, Lutao; Xiao, Jun; Chai, Hua

2015-08-01

The successful suppression of clutter arising from stationary or slowly moving tissue is one of the key issues in medical ultrasound color blood imaging. Remaining clutter may cause bias in the mean blood frequency estimation and results in a potentially misleading description of blood-flow. In this paper, based on the principle of general wall-filter, the design process of three classes of filters, infinitely impulse response with projection initialization (Prj-IIR), polynomials regression (Pol-Reg), and eigen-based filters are previewed and analyzed. The performance of the filters was assessed by calculating the bias and variance of a mean blood velocity using a standard autocorrelation estimator. Simulation results show that the performance of Pol-Reg filter is similar to Prj-IIR filters. Both of them can offer accurate estimation of mean blood flow speed under steady clutter conditions, and the clutter rejection ability can be enhanced by increasing the ensemble size of Doppler vector. Eigen-based filters can effectively remove the non-stationary clutter component, and further improve the estimation accuracy for low speed blood flow signals. There is also no significant increase in computation complexity for eigen-based filters when the ensemble size is less than 10.

Sci-Thur AM: YIS – 07: Optimizing dual-energy x-ray parameters using a single filter for both high and low-energy images to enhance soft-tissue imaging

International Nuclear Information System (INIS)

Bowman, Wesley; Sattarivand, Mike

2016-01-01

Objective: To optimize dual-energy parameters of ExacTrac stereoscopic x-ray imaging system for lung SBRT patients Methods: Simulated spectra and a lung phantom were used to optimize filter material, thickness, kVps, and weighting factors to obtain bone subtracted dual-energy images. Spektr simulations were used to identify material in the atomic number (Z) range [3–83] based on a metric defined to separate spectrums of high and low energies. Both energies used the same filter due to time constraints of image acquisition in lung SBRT imaging. A lung phantom containing bone, soft tissue, and a tumor mimicking material was imaged with filter thicknesses range [0–1] mm and kVp range [60–140]. A cost function based on contrast-to-noise-ratio of bone, soft tissue, and tumor, as well as image noise content, was defined to optimize filter thickness and kVp. Using the optimized parameters, dual-energy images of anthropomorphic Rando phantom were acquired and evaluated for bone subtraction. Imaging dose was measured with dual-energy technique using tin filtering. Results: Tin was the material of choice providing the best energy separation, non-toxicity, and non-reactiveness. The best soft-tissue-only image in the lung phantom was obtained using 0.3 mm tin and [140, 80] kVp pair. Dual-energy images of the Rando phantom had noticeable bone elimination when compared to no filtration. Dose was lower with tin filtering compared to no filtration. Conclusions: Dual-energy soft-tissue imaging is feasible using ExacTrac stereoscopic imaging system utilizing a single tin filter for both high and low energies and optimized acquisition parameters.

Sci-Thur AM: YIS – 07: Optimizing dual-energy x-ray parameters using a single filter for both high and low-energy images to enhance soft-tissue imaging

Energy Technology Data Exchange (ETDEWEB)

Bowman, Wesley; Sattarivand, Mike [Department of Radiation Oncology, Dalhousie University at Nova Scotia Health Authority, Department of Radiation Oncology, Dalhousie University at Nova Scotia Health Authority (Canada)

2016-08-15

Objective: To optimize dual-energy parameters of ExacTrac stereoscopic x-ray imaging system for lung SBRT patients Methods: Simulated spectra and a lung phantom were used to optimize filter material, thickness, kVps, and weighting factors to obtain bone subtracted dual-energy images. Spektr simulations were used to identify material in the atomic number (Z) range [3–83] based on a metric defined to separate spectrums of high and low energies. Both energies used the same filter due to time constraints of image acquisition in lung SBRT imaging. A lung phantom containing bone, soft tissue, and a tumor mimicking material was imaged with filter thicknesses range [0–1] mm and kVp range [60–140]. A cost function based on contrast-to-noise-ratio of bone, soft tissue, and tumor, as well as image noise content, was defined to optimize filter thickness and kVp. Using the optimized parameters, dual-energy images of anthropomorphic Rando phantom were acquired and evaluated for bone subtraction. Imaging dose was measured with dual-energy technique using tin filtering. Results: Tin was the material of choice providing the best energy separation, non-toxicity, and non-reactiveness. The best soft-tissue-only image in the lung phantom was obtained using 0.3 mm tin and [140, 80] kVp pair. Dual-energy images of the Rando phantom had noticeable bone elimination when compared to no filtration. Dose was lower with tin filtering compared to no filtration. Conclusions: Dual-energy soft-tissue imaging is feasible using ExacTrac stereoscopic imaging system utilizing a single tin filter for both high and low energies and optimized acquisition parameters.

Perfect blind restoration of images blurred by multiple filters: theory and efficient algorithms.

Science.gov (United States)

Harikumar, G; Bresler, Y

1999-01-01

We address the problem of restoring an image from its noisy convolutions with two or more unknown finite impulse response (FIR) filters. We develop theoretical results about the existence and uniqueness of solutions, and show that under some generically true assumptions, both the filters and the image can be determined exactly in the absence of noise, and stably estimated in its presence. We present efficient algorithms to estimate the blur functions and their sizes. These algorithms are of two types, subspace-based and likelihood-based, and are extensions of techniques proposed for the solution of the multichannel blind deconvolution problem in one dimension. We present memory and computation-efficient techniques to handle the very large matrices arising in the two-dimensional (2-D) case. Once the blur functions are determined, they are used in a multichannel deconvolution step to reconstruct the unknown image. The theoretical and practical implications of edge effects, and "weakly exciting" images are examined. Finally, the algorithms are demonstrated on synthetic and real data.

First magnetic resonance imaging-guided aortic stenting and cava filter placement using a polyetheretherketone-based magnetic resonance imaging-compatible guidewire in swine: proof of concept.

Science.gov (United States)

Kos, Sebastian; Huegli, Rolf; Hofmann, Eugen; Quick, Harald H; Kuehl, Hilmar; Aker, Stephanie; Kaiser, Gernot M; Borm, Paul J A; Jacob, Augustinus L; Bilecen, Deniz

2009-05-01

The purpose of this study was to demonstrate feasibility of percutaneous transluminal aortic stenting and cava filter placement under magnetic resonance imaging (MRI) guidance exclusively using a polyetheretherketone (PEEK)-based MRI-compatible guidewire. Percutaneous transluminal aortic stenting and cava filter placement were performed in 3 domestic swine. Procedures were performed under MRI-guidance in an open-bore 1.5-T scanner. The applied 0.035-inch guidewire has a PEEK core reinforced by fibres, floppy tip, hydrophilic coating, and paramagnetic markings for passive visualization. Through an 11F sheath, the guidewire was advanced into the abdominal (swine 1) or thoracic aorta (swine 2), and the stents were deployed. The guidewire was advanced into the inferior vena cava (swine 3), and the cava filter was deployed. Postmortem autopsy was performed. Procedural success, guidewire visibility, pushability, and stent support were qualitatively assessed by consensus. Procedure times were documented. Guidewire guidance into the abdominal and thoracic aortas and the inferior vena cava was successful. Stent deployments were successful in the abdominal (swine 1) and thoracic (swine 2) segments of the descending aorta. Cava filter positioning and deployment was successful. Autopsy documented good stent and filter positioning. Guidewire visibility through applied markers was rated acceptable for aortic stenting and good for venous filter placement. Steerability, pushability, and device support were good. The PEEK-based guidewire allows either percutaneous MRI-guided aortic stenting in the thoracic and abdominal segments of the descending aorta and filter placement in the inferior vena cava with acceptable to good device visibility and offers good steerability, pushability, and device support.

First Magnetic Resonance Imaging-Guided Aortic Stenting and Cava Filter Placement Using a Polyetheretherketone-Based Magnetic Resonance Imaging-Compatible Guidewire in Swine: Proof of Concept

International Nuclear Information System (INIS)

Kos, Sebastian; Huegli, Rolf; Hofmann, Eugen; Quick, Harald H.; Kuehl, Hilmar; Aker, Stephanie; Kaiser, Gernot M.; Borm, Paul J. A.; Jacob, Augustinus L.; Bilecen, Deniz

2009-01-01

The purpose of this study was to demonstrate feasibility of percutaneous transluminal aortic stenting and cava filter placement under magnetic resonance imaging (MRI) guidance exclusively using a polyetheretherketone (PEEK)-based MRI-compatible guidewire. Percutaneous transluminal aortic stenting and cava filter placement were performed in 3 domestic swine. Procedures were performed under MRI-guidance in an open-bore 1.5-T scanner. The applied 0.035-inch guidewire has a PEEK core reinforced by fibres, floppy tip, hydrophilic coating, and paramagnetic markings for passive visualization. Through an 11F sheath, the guidewire was advanced into the abdominal (swine 1) or thoracic aorta (swine 2), and the stents were deployed. The guidewire was advanced into the inferior vena cava (swine 3), and the cava filter was deployed. Postmortem autopsy was performed. Procedural success, guidewire visibility, pushability, and stent support were qualitatively assessed by consensus. Procedure times were documented. Guidewire guidance into the abdominal and thoracic aortas and the inferior vena cava was successful. Stent deployments were successful in the abdominal (swine 1) and thoracic (swine 2) segments of the descending aorta. Cava filter positioning and deployment was successful. Autopsy documented good stent and filter positioning. Guidewire visibility through applied markers was rated acceptable for aortic stenting and good for venous filter placement. Steerability, pushability, and device support were good. The PEEK-based guidewire allows either percutaneous MRI-guided aortic stenting in the thoracic and abdominal segments of the descending aorta and filter placement in the inferior vena cava with acceptable to good device visibility and offers good steerability, pushability, and device support.

Two-dimensional restoration of single photon emission computed tomography images using the Kalman filter

International Nuclear Information System (INIS)

Boulfelfel, D.; Rangayyan, R.M.; Kuduvalli, G.R.; Hahn, L.J.; Kloiber, R.

1994-01-01

The discrete filtered backprojection (DFBP) algorithm used for the reconstruction of single photon emission computed tomography (SPECT) images affects image quality because of the operations of filtering and discretization. The discretization of the filtered backprojection process can cause the modulation transfer function (MTF) of the SPECT imaging system to be anisotropic and nonstationary, especially near the edges of the camera's field of view. The use of shift-invariant restoration techniques fails to restore large images because these techniques do not account for such variations in the MTF. This study presents the application of a two-dimensional (2-D) shift-variant Kalman filter for post-reconstruction restoration of SPECT slices. This filter was applied to SPECT images of a hollow cylinder phantom; a resolution phantom; and a large, truncated cone phantom containing two types of cold spots, a sphere, and a triangular prism. The images were acquired on an ADAC GENESYS camera. A comparison was performed between results obtained by the Kalman filter and those obtained by shift-invariant filters. Quantitative analysis of the restored images performed through measurement of root mean squared errors shows a considerable reduction in error of Kalman-filtered images over images restored using shift-invariant methods

Automated microaneurysm detection method based on double ring filter in retinal fundus images

Science.gov (United States)

Mizutani, Atsushi; Muramatsu, Chisako; Hatanaka, Yuji; Suemori, Shinsuke; Hara, Takeshi; Fujita, Hiroshi

2009-02-01

The presence of microaneurysms in the eye is one of the early signs of diabetic retinopathy, which is one of the leading causes of vision loss. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images, which were obtained from the Retinopathy Online Challenge (ROC) database. The ROC provides 50 training cases, in which "gold standard" locations of microaneurysms are provided, and 50 test cases without the gold standard locations. In this study, the computerized scheme was developed by using the training cases. Although the results for the test cases are also included, this paper mainly discusses the results for the training cases because the "gold standard" for the test cases is not known. After image preprocessing, candidate regions for microaneurysms were detected using a double-ring filter. Any potential false positives located in the regions corresponding to blood vessels were removed by automatic extraction of blood vessels from the images. Twelve image features were determined, and the candidate lesions were classified into microaneurysms or false positives using the rule-based method and an artificial neural network. The true positive fraction of the proposed method was 0.45 at 27 false positives per image. Forty-two percent of microaneurysms in the 50 training cases were considered invisible by the consensus of two co-investigators. When the method was evaluated for visible microaneurysms, the sensitivity for detecting microaneurysms was 65% at 27 false positives per image. Our computerized detection scheme could be improved for helping ophthalmologists in the early diagnosis of diabetic retinopathy.

Sealing Clay Text Segmentation Based on Radon-Like Features and Adaptive Enhancement Filters

Directory of Open Access Journals (Sweden)

Xia Zheng

2015-01-01

Full Text Available Text extraction is a key issue in sealing clay research. The traditional method based on rubbings increases the risk of sealing clay damage and is unfavorable to sealing clay protection. Therefore, using digital image of sealing clay, a new method for text segmentation based on Radon-like features and adaptive enhancement filters is proposed in this paper. First, adaptive enhancement LM filter bank is used to get the maximum energy image; second, the edge image of the maximum energy image is calculated; finally, Radon-like feature images are generated by combining maximum energy image and its edge image. The average image of Radon-like feature images is segmented by the image thresholding method. Compared with 2D Otsu, GA, and FastFCM, the experiment result shows that this method can perform better in terms of accuracy and completeness of the text.

US images encoding envelope amplitude following narrow band filtering

International Nuclear Information System (INIS)

Sommer, F.G.; Stern, R.A.; Chen, H.S.

1986-01-01

Ultrasonic waveform data from phantoms having differing scattering characteristics and from normal and cirrhotic human liver in vivo were recorded within a standardized dynamic range and filtered with narrow band filters either above or below the mean recorded ultrasonic center frequency. Images created by mapping the amplitudes of received ultrasound following such filtration permitted dramatic differentiation, not discernible in conventional US images, of phantoms having differing scattering characteristics, and of normal and cirrhotic human livers

Nonlinear image filtering within IDP++

Energy Technology Data Exchange (ETDEWEB)

Lehman, S.K.; Wieting, M.G.; Brase, J.M.

1995-02-09

IDP++, image and data processing in C++, is a set of a signal processing libraries written in C++. It is a multi-dimension (up to four dimensions), multi-data type (implemented through templates) signal processing extension to C++. IDP++ takes advantage of the object-oriented compiler technology to provide ``information hiding.`` Users need only know C, not C++. Signals or data sets are treated like any other variable with a defined set of operators and functions. We here some examples of the nonlinear filter library within IDP++. Specifically, the results of MIN, MAX median, {alpha}-trimmed mean, and edge-trimmed mean filters as applied to a real aperture radar (RR) and synthetic aperture radar (SAR) data set.

Imaging through scattering media by Fourier filtering and single-pixel detection

Science.gov (United States)

Jauregui-Sánchez, Y.; Clemente, P.; Lancis, J.; Tajahuerce, E.

2018-02-01

We present a novel imaging system that combines the principles of Fourier spatial filtering and single-pixel imaging in order to recover images of an object hidden behind a turbid medium by transillumination. We compare the performance of our single-pixel imaging setup with that of a conventional system. We conclude that the introduction of Fourier gating improves the contrast of images in both cases. Furthermore, we show that the combination of single-pixel imaging and Fourier spatial filtering techniques is particularly well adapted to provide images of objects transmitted through scattering media.

Preprocessing of PHERMEX flash radiographic images with Haar and adaptive filtering

International Nuclear Information System (INIS)

Brolley, J.E.

1978-11-01

Work on image preparation has continued with the application of high-sequency boosting via Haar filtering. This is useful in developing line or edge structures. Widrow LMS adaptive filtering has also been shown to be useful in developing edge structure in special problems. Shadow effects can be obtained with the latter which may be useful for some problems. Combined Haar and adaptive filtering is illustrated for a PHERMEX image

Artifact reduction of compressed images and video combining adaptive fuzzy filtering and directional anisotropic diffusion

DEFF Research Database (Denmark)

Nadernejad, Ehsan; Forchhammer, Søren; Korhonen, Jari

2011-01-01

and ringing artifacts, we have applied directional anisotropic diffusion. Besides that, the selection of the adaptive threshold parameter for the diffusion coefficient has also improved the performance of the algorithm. Experimental results on JPEG compressed images as well as MJPEG and H.264 compressed......Fuzzy filtering is one of the recently developed methods for reducing distortion in compressed images and video. In this paper, we combine the powerful anisotropic diffusion equations with fuzzy filtering in order to reduce the impact of artifacts. Based on the directional nature of the blocking...... videos show improvement in artifact reduction of the proposed algorithm over other directional and spatial fuzzy filters....

Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

Directory of Open Access Journals (Sweden)

HU Gensheng

2018-03-01

Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

An Extension to a Filter Implementation of Local Quadratic Surface for Image Noise Estimation

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

1999-01-01

Based on regression analysis this paper gives a description for simple image filter design. Specifically 3x3 filter implementations of a quadratic surface, residuals from this surface, gradients and the Laplacian are given. For the residual a 5x5 filter is given also. It is shown that the 3x3......) it is concluded that if striping is to be considered as a part of the noise, the residual from a 3x3 median filter seems best. If we are interested in a salt-and-pepper noise estimator the proposed extension to the 3x3 filter for the residual from a quadratic surface seems best. Simple statistics...

An image-space parallel convolution filtering algorithm based on shadow map

Science.gov (United States)

Li, Hua; Yang, Huamin; Zhao, Jianping

2017-07-01

Shadow mapping is commonly used in real-time rendering. In this paper, we presented an accurate and efficient method of soft shadows generation from planar area lights. First this method generated a depth map from light's view, and analyzed the depth-discontinuities areas as well as shadow boundaries. Then these areas were described as binary values in the texture map called binary light-visibility map, and a parallel convolution filtering algorithm based on GPU was enforced to smooth out the boundaries with a box filter. Experiments show that our algorithm is an effective shadow map based method that produces perceptually accurate soft shadows in real time with more details of shadow boundaries compared with the previous works.

A Kalman filter technique applied for medical image reconstruction

International Nuclear Information System (INIS)

Goliaei, S.; Ghorshi, S.; Manzuri, M. T.; Mortazavi, M.

2011-01-01

Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image in order to provide images with better quality and contrast. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as the most popular one known as filtered back projection. In this paper we introduce a Kalman filter technique which is operated in time domain for medical image reconstruction. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of reconstructed image becomes better in terms of contract and transparency. It is also seen that as the number of projection increases the error index decreases.

Visible Wavelength Color Filters Using Dielectric Subwavelength Gratings for Backside-Illuminated CMOS Image Sensor Technologies.

Science.gov (United States)

Horie, Yu; Han, Seunghoon; Lee, Jeong-Yub; Kim, Jaekwan; Kim, Yongsung; Arbabi, Amir; Shin, Changgyun; Shi, Lilong; Arbabi, Ehsan; Kamali, Seyedeh Mahsa; Lee, Hong-Seok; Hwang, Sungwoo; Faraon, Andrei

2017-05-10

We report transmissive color filters based on subwavelength dielectric gratings that can replace conventional dye-based color filters used in backside-illuminated CMOS image sensor (BSI CIS) technologies. The filters are patterned in an 80 nm-thick poly silicon film on a 115 nm-thick SiO 2 spacer layer. They are optimized for operating at the primary RGB colors, exhibit peak transmittance of 60-80%, and have an almost insensitive response over a ± 20° angular range. This technology enables shrinking of the pixel sizes down to near a micrometer.

Weighted ensemble transform Kalman filter for image assimilation

Directory of Open Access Journals (Sweden)

Sebastien Beyou

2013-01-01

Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.

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.

Apodized RFI filtering of synthetic aperture radar images

Energy Technology Data Exchange (ETDEWEB)

Doerry, Armin Walter

2014-02-01

Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFI Filtering (ARF).

Wavelet Filter Banks for Super-Resolution SAR Imaging

Science.gov (United States)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Filtering and deconvolution for bioluminescence imaging of small animals

International Nuclear Information System (INIS)

Akkoul, S.

2010-01-01

This thesis is devoted to analysis of bioluminescence images applied to the small animal. This kind of imaging modality is used in cancerology studies. Nevertheless, some problems are related to the diffusion and the absorption of the tissues of the light of internal bioluminescent sources. In addition, system noise and the cosmic rays noise are present. This influences the quality of the images and makes it difficult to analyze. The purpose of this thesis is to overcome these disturbing effects. We first have proposed an image formation model for the bioluminescence images. The processing chain is constituted by a filtering stage followed by a deconvolution stage. We have proposed a new median filter to suppress the random value impulsive noise which corrupts the acquired images; this filter represents the first block of the proposed chain. For the deconvolution stage, we have performed a comparative study of various deconvolution algorithms. It allowed us to choose a blind deconvolution algorithm initialized with the estimated point spread function of the acquisition system. At first, we have validated our global approach by comparing our obtained results with the ground truth. Through various clinical tests, we have shown that the processing chain allows a significant improvement of the spatial resolution and a better distinction of very close tumor sources, what represents considerable contribution for the users of bioluminescence images. (author)

Learning based particle filtering object tracking for visible-light systems.

Science.gov (United States)

Sun, Wei

2015-10-01

We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

Image restoration technique using median filter combined with decision tree algorithm

International Nuclear Information System (INIS)

Sethu, D.; Assadi, H.M.; Hasson, F.N.; Hasson, N.N.

2007-01-01

Images are usually corrupted during transmission principally due to interface in the channel used for transmission. Images also be impaired by the addition of various forms of noise. Salt and pepper is commonly used to impair the image. Salt and pepper noise can be caused by errors in data transmission, malfunctioning pixel elements in camera sensors, and timing errors in the digitization process. During the filtering of noisy image, important features such as edges, lines and other fine image details embedded in the image tends to blur because of filtering operation. The enhancement of noisy data, however, is a very critical process because the sharpening operation can significantly increase the noise. In this respect, contrast enhancement is often necessary in order to highlight details that have been blurred. In this proposed approach we aim to develop image processing technique that can meet this new requirement, which are high quality and high speed. Furthermore, prevent the noise accretion during the sharpening of the image details, and compare the restored images via proposed method with other kinds of filters. (author)

A multi-stage noise adaptive switching filter for extremely corrupted images

Science.gov (United States)

Dinh, Hai; Adhami, Reza; Wang, Yi

2015-07-01

A multi-stage noise adaptive switching filter (MSNASF) is proposed for the restoration of images extremely corrupted by impulse and impulse-like noise. The filter consists of two steps: noise detection and noise removal. The proposed extrema-based noise detection scheme utilizes the false contouring effect to get better over detection rate at low noise density. It is adaptive and will detect not only impulse but also impulse-like noise. In the noise removal step, a novel multi-stage filtering scheme is proposed. It replaces corrupted pixel with the nearest uncorrupted median to preserve details. When compared with other methods, MSNASF provides better peak signal to noise ratio (PSNR) and structure similarity index (SSIM). A subjective evaluation carried out online also demonstrates that MSNASF yields higher fidelity.

CHANGE DETECTION VIA SELECTIVE GUIDED CONTRASTING FILTERS

Directory of Open Access Journals (Sweden)

Y. V. Vizilter

2017-05-01

Full Text Available Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC. The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC, mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All

Time Domain Filtering of Resolved Images of Sgr A{sup ∗}

Energy Technology Data Exchange (ETDEWEB)

Shiokawa, Hotaka; Doeleman, Sheperd S. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Gammie, Charles F. [Department of Physics, University of Illinois, 1110 West Green Street, Urbana, IL 61801 (United States)

2017-09-01

The goal of the Event Horizon Telescope (EHT) is to provide spatially resolved images of Sgr A*, the source associated with the Galactic Center black hole. Because Sgr A* varies on timescales that are short compared to an EHT observing campaign, it is interesting to ask whether variability contains information about the structure and dynamics of the accretion flow. In this paper, we introduce “time-domain filtering,” a technique to filter time fluctuating images with specific temporal frequency ranges and to demonstrate the power and usage of the technique by applying it to mock millimeter wavelength images of Sgr A*. The mock image data is generated from the General Relativistic Magnetohydrodynamic (GRMHD) simulation and the general relativistic ray-tracing method. We show that the variability on each line of sight is tightly correlated with a typical radius of emission. This is because disk emissivity fluctuates on a timescale of the order of the local orbital period. Time-domain filtered images therefore reflect the model dependent emission radius distribution, which is not accessible in time-averaged images. We show that, in principle, filtered data have the power to distinguish between models with different black-hole spins, different disk viewing angles, and different disk orientations in the sky.

Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.

Science.gov (United States)

Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H

2013-05-01

In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.

Predicting perceptual quality of images in realistic scenario using deep filter banks

Science.gov (United States)

Zhang, Weixia; Yan, Jia; Hu, Shiyong; Ma, Yang; Deng, Dexiang

2018-03-01

Classical image perceptual quality assessment models usually resort to natural scene statistic methods, which are based on an assumption that certain reliable statistical regularities hold on undistorted images and will be corrupted by introduced distortions. However, these models usually fail to accurately predict degradation severity of images in realistic scenarios since complex, multiple, and interactive authentic distortions usually appear on them. We propose a quality prediction model based on convolutional neural network. Quality-aware features extracted from filter banks of multiple convolutional layers are aggregated into the image representation. Furthermore, an easy-to-implement and effective feature selection strategy is used to further refine the image representation and finally a linear support vector regression model is trained to map image representation into images' subjective perceptual quality scores. The experimental results on benchmark databases present the effectiveness and generalizability of the proposed model.

Filters involving derivatives with application to reconstruction from scanned halftone images

DEFF Research Database (Denmark)

Forchhammer, Søren; Jensen, Kim S.

1995-01-01

This paper presents a method for designing finite impulse response (FIR) filters for samples of a 2-D signal, e.g., an image, and its gradient. The filters, which are called blended filters, are decomposable in three filters, each separable in 1-D filters on subsets of the data set. Optimality...... in the minimum mean square error sense (MMSE) of blended filtering is shown for signals with separable autocorrelation function. Relations between correlation functions for signals and their gradients are derived. Blended filters may be composed from FIR Wiener filters using these relations. Simple blended...... is achievable with blended filters...

A New Switching-Based Median Filtering Scheme and Algorithm for Removal of High-Density Salt and Pepper Noise in Images

Directory of Open Access Journals (Sweden)

Jayaraj V

2010-01-01

Full Text Available A new switching-based median filtering scheme for restoration of images that are highly corrupted by salt and pepper noise is proposed. An algorithm based on the scheme is developed. The new scheme introduces the concept of substitution of noisy pixels by linear prediction prior to estimation. A novel simplified linear predictor is developed for this purpose. The objective of the scheme and algorithm is the removal of high-density salt and pepper noise in images. The new algorithm shows significantly better image quality with good PSNR, reduced MSE, good edge preservation, and reduced streaking. The good performance is achieved with reduced computational complexity. A comparison of the performance is made with several existing algorithms in terms of visual and quantitative results. The performance of the proposed scheme and algorithm is demonstrated.

Magnetic resonance image enhancement using V-filter

International Nuclear Information System (INIS)

Yamamoto, H.; Sugita, K.; Kanzaki, N.; Johja, I.; Hiraki, Y.

1990-01-01

The purpose of this study is to present a method of boundary enhancement algorithms for magnetic resonance images using a V-filter. The boundary of the brain tumor was precisely extracted by the region segmentation techniques

Raman imaging using fixed bandpass filter

Science.gov (United States)

Landström, L.; Kullander, F.; Lundén, H.; Wästerby, P.

2017-05-01

By using fixed narrow band pass optical filtering and scanning the laser excitation wavelength, hyperspectral Raman imaging could be achieved. Experimental, proof-of-principle results from the Chemical Warfare Agent (CWA) tabun (GA) as well as the common CWA simulant tributyl phosphate (TBP) on different surfaces/substrates are presented and discussed.

Advanced microlens and color filter process technology for the high-efficiency CMOS and CCD image sensors

Science.gov (United States)

Fan, Yang-Tung; Peng, Chiou-Shian; Chu, Cheng-Yu

2000-12-01

New markets are emerging for digital electronic image device, especially in visual communications, PC camera, mobile/cell phone, security system, toys, vehicle image system and computer peripherals for document capture. To enable one-chip image system that image sensor is with a full digital interface, can make image capture devices in our daily lives. Adding a color filter to such image sensor in a pattern of mosaics pixel or wide stripes can make image more real and colorful. We can say 'color filter makes the life more colorful color filter is? Color filter means can filter image light source except the color with specific wavelength and transmittance that is same as color filter itself. Color filter process is coating and patterning green, red and blue (or cyan, magenta and yellow) mosaic resists onto matched pixel in image sensing array pixels. According to the signal caught from each pixel, we can figure out the environment image picture. Widely use of digital electronic camera and multimedia applications today makes the feature of color filter becoming bright. Although it has challenge but it is very worthy to develop the process of color filter. We provide the best service on shorter cycle time, excellent color quality, high and stable yield. The key issues of advanced color process have to be solved and implemented are planarization and micro-lens technology. Lost of key points of color filter process technology have to consider will also be described in this paper.

Two-dimensional real-time imaging system for subtraction angiography using an iodine filter

Science.gov (United States)

Umetani, Keiji; Ueda, Ken; Takeda, Tohoru; Anno, Izumi; Itai, Yuji; Akisada, Masayoshi; Nakajima, Teiichi

1992-01-01

A new type of subtraction imaging system was developed using an iodine filter and a single-energy broad bandwidth monochromatized x ray. The x-ray images of coronary arteries made after intravenous injection of a contrast agent are enhanced by an energy-subtraction technique. Filter chopping of the x-ray beam switches energies rapidly, so that a nearly simultaneous pair of filtered and nonfiltered images can be made. By using a high-speed video camera, a pair of two 512 × 512 pixel images can be obtained within 9 ms. Three hundred eighty-four images (raw data) are stored in a 144-Mbyte frame memory. After phantom studies, in vivo subtracted images of coronary arteries in dogs were obtained at a rate of 15 images/s.

Evidence-Based Evaluation of Inferior Vena Cava Filter Complications Based on Filter Type

Science.gov (United States)

Deso, Steven E.; Idakoji, Ibrahim A.; Kuo, William T.

2016-01-01

Many inferior vena cava (IVC) filter types, along with their specific risks and complications, are not recognized. The purpose of this study was to evaluate the various FDA-approved IVC filter types to determine device-specific risks, as a way to help identify patients who may benefit from ongoing follow-up versus prompt filter retrieval. An evidence-based electronic search (FDA Premarket Notification, MEDLINE, FDA MAUDE) was performed to identify all IVC filter types and device-specific complications from 1980 to 2014. Twenty-three IVC filter types (14 retrievable, 9 permanent) were identified. The devices were categorized as follows: conical (n = 14), conical with umbrella (n = 1), conical with cylindrical element (n = 2), biconical with cylindrical element (n = 2), helical (n = 1), spiral (n = 1), and complex (n = 1). Purely conical filters were associated with the highest reported risks of penetration (90–100%). Filters with cylindrical or umbrella elements were associated with the highest reported risk of IVC thrombosis (30–50%). Conical Bard filters were associated with the highest reported risks of fracture (40%). The various FDA-approved IVC filter types were evaluated for device-specific complications based on best current evidence. This information can be used to guide and optimize clinical management in patients with indwelling IVC filters. PMID:27247477

A motion-compensated image filter for low-dose fluoroscopy in a real-time tumor-tracking radiotherapy system

International Nuclear Information System (INIS)

Miyamoto, Naoki; Ishikawa, Masayori; Sutherland, Kenneth

2015-01-01

In the real-time tumor-tracking radiotherapy system, a surrogate fiducial marker inserted in or near the tumor is detected by fluoroscopy to realize respiratory-gated radiotherapy. The imaging dose caused by fluoroscopy should be minimized. In this work, an image processing technique is proposed for tracing a moving marker in low-dose imaging. The proposed tracking technique is a combination of a motion-compensated recursive filter and template pattern matching. The proposed image filter can reduce motion artifacts resulting from the recursive process based on the determination of the region of interest for the next frame according to the current marker position in the fluoroscopic images. The effectiveness of the proposed technique and the expected clinical benefit were examined by phantom experimental studies with actual tumor trajectories generated from clinical patient data. It was demonstrated that the marker motion could be traced in low-dose imaging by applying the proposed algorithm with acceptable registration error and high pattern recognition score in all trajectories, although some trajectories were not able to be tracked with the conventional spatial filters or without image filters. The positional accuracy is expected to be kept within ±2 mm. The total computation time required to determine the marker position is a few milliseconds. The proposed image processing technique is applicable for imaging dose reduction. (author)

Least median of squares filtering of locally optimal point matches for compressible flow image registration

International Nuclear Information System (INIS)

Castillo, Edward; Guerrero, Thomas; Castillo, Richard; White, Benjamin; Rojo, Javier

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. (paper)

Guided filtering for solar image/video processing

Directory of Open Access Journals (Sweden)

Long Xu

2017-06-01

Full Text Available A new image enhancement algorithm employing guided filtering is proposed in this work for enhancement of solar images and videos, so that users can easily figure out important fine structures imbedded in the recorded images/movies for solar observation. The proposed algorithm can efficiently remove image noises, including Gaussian and impulse noises. Meanwhile, it can further highlight fibrous structures on/beyond the solar disk. These fibrous structures can clearly demonstrate the progress of solar flare, prominence coronal mass emission, magnetic field, and so on. The experimental results prove that the proposed algorithm gives significant enhancement of visual quality of solar images beyond original input and several classical image enhancement algorithms, thus facilitating easier determination of interesting solar burst activities from recorded images/movies.

Biomedical bandpass filter for fluorescence microscopy imaging based on TiO2/SiO2 and TiO2/MgF2 dielectric multilayers

International Nuclear Information System (INIS)

Butt, M A; Fomchenkov, S A; Verma, P; Khonina, S N; Ullah, A

2016-01-01

We report a design for creating a multilayer dielectric optical filters based on TiO 2 and SiO 2 /MgF 2 alternating layers. We have selected Titanium dioxide (TiO 2 ) for high refractive index (2.5), Silicon dioxide (SiO 2 ) and Magnesium fluoride (MgF 2 ) as a low refractive index layer (1.45 and 1.37) respectively. Miniaturized visible spectrometers are useful for quick and mobile characterization of biological samples. Such devices can be fabricated by using Fabry-Perot (FP) filters consisting of two highly reflecting mirrors with a central cavity in between. Distributed Bragg Reflectors (DBRs) consisting of alternating high and low refractive index material pairs are the most commonly used mirrors in FP filters, due to their high reflectivity. However, DBRs have high reflectivity for a selected range of wavelengths known as the stopband of the DBR. This range is usually much smaller than the sensitivity range of the spectrometer range. Therefore a bandpass filters are required to restrict wavelength outside the stopband of the FP DBRs. The proposed filter shows a high quality with average transmission of 97.4% within the passbands and the transmission outside the passband is around 4%. Special attention has been given to keep the thickness of the filters within the economic limits. It can be suggested that these filters are exceptional choice for florescence imaging and Endoscope narrow band imaging. (paper)

Decentralized Social Filtering based on Trust

OpenAIRE

Olsson, Tomas

1998-01-01

This paper describes a decentralised approach to social filtering based on trust between agents in a multiagent system. The social filtering in the proposed approach is built on the interactions between collaborative software agents performing content-based filtering. This means that it uses a mixture of content-based and social filtering and thereby, it takes advantage of both methods.

On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained.

Science.gov (United States)

Chowdhury, Debbrota Paul; Bakshi, Sambit; Guo, Guodong; Sa, Pankaj Kumar

2017-11-27

In this paper, an overall framework has been presented for person verification using ear biometric which uses tunable filter bank as local feature extractor. The tunable filter bank, based on a half-band polynomial of 14th order, extracts distinct features from ear images maintaining its frequency selectivity property. To advocate the applicability of tunable filter bank on ear biometrics, recognition test has been performed on available constrained databases like AMI, WPUT, IITD and unconstrained database like UERC. Experiments have been conducted applying tunable filter based feature extractor on subparts of the ear. Empirical experiments have been conducted with four and six subdivisions of the ear image. Analyzing the experimental results, it has been found that tunable filter moderately succeeds to distinguish ear features at par with the state-of-the-art features used for ear recognition. Accuracies of 70.58%, 67.01%, 81.98%, and 57.75% have been achieved on AMI, WPUT, IITD, and UERC databases through considering Canberra Distance as underlying measure of separation. The performances indicate that tunable filter is a candidate for recognizing human from ear images.

A Divergence Median-based Geometric Detector with A Weighted Averaging Filter

Science.gov (United States)

Hua, Xiaoqiang; Cheng, Yongqiang; Li, Yubo; Wang, Hongqiang; Qin, Yuliang

2018-01-01

To overcome the performance degradation of the classical fast Fourier transform (FFT)-based constant false alarm rate detector with the limited sample data, a divergence median-based geometric detector on the Riemannian manifold of Heimitian positive definite matrices is proposed in this paper. In particular, an autocorrelation matrix is used to model the correlation of sample data. This method of the modeling can avoid the poor Doppler resolution as well as the energy spread of the Doppler filter banks result from the FFT. Moreover, a weighted averaging filter, conceived from the philosophy of the bilateral filtering in image denoising, is proposed and combined within the geometric detection framework. As the weighted averaging filter acts as the clutter suppression, the performance of the geometric detector is improved. Numerical experiments are given to validate the effectiveness of our proposed method.

Image restoration by Wiener filtering in the presence of signal-dependent noise.

Science.gov (United States)

Kondo, K; Ichioka, Y; Suzuki, T

1977-09-01

An optimum filter to restore the degraded image due to blurring and the signal-dependent noise is obtained on the basis of the theory of Wiener filtering. Computer simulations of image restoration using signal-dependent noise models are carried out. It becomes clear that the optimum filter, which makes use of a priori information on the signal-dependent nature of the noise and the spectral density of the signal and the noise showing significant spatial correlation, is potentially advantageous.

Improved Kalman Filter-Based Speech Enhancement with Perceptual Post-Filtering

Institute of Scientific and Technical Information of China (English)

WEIJianqiang; DULimin; YANZhaoli; ZENGHui

2004-01-01

In this paper, a Kalman filter-based speech enhancement algorithm with some improvements of previous work is presented. A new technique based on spectral subtraction is used for separation speech and noise characteristics from noisy speech and for the computation of speech and noise Autoregressive (AR) parameters. In order to obtain a Kalman filter output with high audible quality, a perceptual post-filter is placed at the output of the Kalman filter to smooth the enhanced speech spectra.Extensive experiments indicate that this newly proposed method works well.

The influence of software filtering in digital mammography image quality

Science.gov (United States)

Michail, C.; Spyropoulou, V.; Kalyvas, N.; Valais, I.; Dimitropoulos, N.; Fountos, G.; Kandarakis, I.; Panayiotakis, G.

2009-05-01

Breast cancer is one of the most frequently diagnosed cancers among women. Several techniques have been developed to help in the early detection of breast cancer such as conventional and digital x-ray mammography, positron and single-photon emission mammography, etc. A key advantage in digital mammography is that images can be manipulated as simple computer image files. Thus non-dedicated commercially available image manipulation software can be employed to process and store the images. The image processing tools of the Photoshop (CS 2) software usually incorporate digital filters which may be used to reduce image noise, enhance contrast and increase spatial resolution. However, improving an image quality parameter may result in degradation of another. The aim of this work was to investigate the influence of three sharpening filters, named hereafter sharpen, sharpen more and sharpen edges on image resolution and noise. Image resolution was assessed by means of the Modulation Transfer Function (MTF).In conclusion it was found that the correct use of commercial non-dedicated software on digital mammograms may improve some aspects of image quality.

The influence of software filtering in digital mammography image quality

International Nuclear Information System (INIS)

Michail, C; Spyropoulou, V; Valais, I; Panayiotakis, G; Kalyvas, N; Fountos, G; Kandarakis, I; Dimitropoulos, N

2009-01-01

Breast cancer is one of the most frequently diagnosed cancers among women. Several techniques have been developed to help in the early detection of breast cancer such as conventional and digital x-ray mammography, positron and single-photon emission mammography, etc. A key advantage in digital mammography is that images can be manipulated as simple computer image files. Thus non-dedicated commercially available image manipulation software can be employed to process and store the images. The image processing tools of the Photoshop (CS 2) software usually incorporate digital filters which may be used to reduce image noise, enhance contrast and increase spatial resolution. However, improving an image quality parameter may result in degradation of another. The aim of this work was to investigate the influence of three sharpening filters, named hereafter sharpen, sharpen more and sharpen edges on image resolution and noise. Image resolution was assessed by means of the Modulation Transfer Function (MTF).In conclusion it was found that the correct use of commercial non-dedicated software on digital mammograms may improve some aspects of image quality.

Supervised retinal vessel segmentation from color fundus images based on matched filtering and AdaBoost classifier.

Directory of Open Access Journals (Sweden)

Nogol Memari

Full Text Available The structure and appearance of the blood vessel network in retinal fundus images is an essential part of diagnosing various problems associated with the eyes, such as diabetes and hypertension. In this paper, an automatic retinal vessel segmentation method utilizing matched filter techniques coupled with an AdaBoost classifier is proposed. The fundus image is enhanced using morphological operations, the contrast is increased using contrast limited adaptive histogram equalization (CLAHE method and the inhomogeneity is corrected using Retinex approach. Then, the blood vessels are enhanced using a combination of B-COSFIRE and Frangi matched filters. From this preprocessed image, different statistical features are computed on a pixel-wise basis and used in an AdaBoost classifier to extract the blood vessel network inside the image. Finally, the segmented images are postprocessed to remove the misclassified pixels and regions. The proposed method was validated using publicly accessible Digital Retinal Images for Vessel Extraction (DRIVE, Structured Analysis of the Retina (STARE and Child Heart and Health Study in England (CHASE_DB1 datasets commonly used for determining the accuracy of retinal vessel segmentation methods. The accuracy of the proposed segmentation method was comparable to other state of the art methods while being very close to the manual segmentation provided by the second human observer with an average accuracy of 0.972, 0.951 and 0.948 in DRIVE, STARE and CHASE_DB1 datasets, respectively.

Field programmable gate array based hardware implementation of a gradient filter for edge detection in colour images with subpixel precision

International Nuclear Information System (INIS)

Schellhorn, M; Rosenberger, M; Correns, M; Blau, M; Goepfert, A; Rueckwardt, M; Linss, G

2010-01-01

Within the field of industrial image processing the use of colour cameras becomes ever more common. Increasingly the established black and white cameras are replaced by economical single-chip colour cameras with Bayer pattern. The use of the additional colour information is particularly important for recognition or inspection. Become interesting however also for the geometric metrology, if measuring tasks can be solved more robust or more exactly. However only few suitable algorithms are available, in order to detect edges with the necessary precision. All attempts require however additional computation expenditure. On the basis of a new filter for edge detection in colour images with subpixel precision, the implementation on a pre-processing hardware platform is presented. Hardware implemented filters offer the advantage that they can be used easily with existing measuring software, since after the filtering a single channel image is present, which unites the information of all colour channels. Advanced field programmable gate arrays represent an ideal platform for the parallel processing of multiple channels. The effective implementation presupposes however a high programming expenditure. On the example of the colour filter implementation, arising problems are analyzed and the chosen solution method is presented.

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

Science.gov (United States)

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

Improvement of QR Code Recognition Based on Pillbox Filter Analysis

Directory of Open Access Journals (Sweden)

Jia-Shing Sheu

2013-04-01

Full Text Available The objective of this paper is to perform the innovation design for improving the recognition of a captured QR code image with blur through the Pillbox filter analysis. QR code images can be captured by digital video cameras. Many factors contribute to QR code decoding failure, such as the low quality of the image. Focus is an important factor that affects the quality of the image. This study discusses the out-of-focus QR code image and aims to improve the recognition of the contents in the QR code image. Many studies have used the pillbox filter (circular averaging filter method to simulate an out-of-focus image. This method is also used in this investigation to improve the recognition of a captured QR code image. A blurred QR code image is separated into nine levels. In the experiment, four different quantitative approaches are used to reconstruct and decode an out-of-focus QR code image. These nine reconstructed QR code images using methods are then compared. The final experimental results indicate improvements in identification.

Hardware design of the median filter based on window structure and batcher′s oddeven sort network

Directory of Open Access Journals (Sweden)

SUN Kaimin

2013-06-01

Full Text Available Area and speed are two important factors to be considered in designing Median Filter with digital circuits.Area consideration requires the use of logical resources as little as possible,while speed consideration requires the system capable of working on higher clock frequencies,with as few clock cycles as possible to complete a frame filtering or real time filtering.This paper gives a new design of Median Filter,the hardware structure of which is a 3×3 window structure with two buffers.The filter function module is based on Batcher′s Odd-Even Sort network theory.Structural design is implemented in FPGA,verified by ModelSim software and realizes video image filtering.The experimental analysis shows that this new structure of Median Filter effectively decreases logical resources (merely using 741 Logic Elements,and accelerates the pixel processing speed up to 27MHz.This filter achieves realtime processing of video images of 30 frames/s.This design not only has a certain practicality,but also provides a reference for the hardware structure design ideas in digital image processing.

A novel spatiotemporal muscle activity imaging approach based on the Extended Kalman Filter.

Science.gov (United States)

Wang, Jing; Zhang, Yingchun; Zhu, Xiangjun; Zhou, Ping; Liu, Chenguang; Rymer, William Z

2012-01-01

A novel spatiotemporal muscle activity imaging (sMAI) approach has been developed using the Extended Kalman Filter (EKF) to reconstruct internal muscle activities from non-invasive multi-channel surface electromyogram (sEMG) recordings. A distributed bioelectric dipole source model is employed to describe the internal muscle activity space, and a linear relationship between the muscle activity space and the sEMG measurement space is then established. The EKF is employed to recursively solve the ill-posed inverse problem in the sMAI approach, in which the weighted minimum norm (WMN) method is utilized to calculate the initial state and a new nonlinear method is developed based on the propagating features of muscle activities to predict the recursive state. A series of computer simulations was conducted to test the performance of the proposed sMAI approach. Results show that the localization error rapidly decreases over 35% and the overlap ratio rapidly increases over 45% compared to the results achieved using the WMN method only. The present promising results demonstrate the feasibility of utilizing the proposed EKF-based sMAI approach to accurately reconstruct internal muscle activities from non-invasive sEMG recordings.

Kalman Filtered MR Temperature Imaging for Laser Induced Thermal Therapies

OpenAIRE

Fuentes, D.; Yung, J.; Hazle, J. D.; Weinberg, J. S.; Stafford, R. J.

2011-01-01

The feasibility of using a stochastic form of Pennes bioheat model within a 3D finite element based Kalman filter (KF) algorithm is critically evaluated for the ability to provide temperature field estimates in the event of magnetic resonance temperature imaging (MRTI) data loss during laser induced thermal therapy (LITT). The ability to recover missing MRTI data was analyzed by systematically removing spatiotemporal information from a clinical MR-guided LITT procedure in human brain and comp...

COMPARISON OF ULTRASOUND IMAGE FILTERING METHODS BY MEANS OF MULTIVARIABLE KURTOSIS

Directory of Open Access Journals (Sweden)

Mariusz Nieniewski

2017-06-01

Full Text Available Comparison of the quality of despeckled US medical images is complicated because there is no image of a human body that would be free of speckles and could serve as a reference. A number of various image metrics are currently used for comparison of filtering methods; however, they do not satisfactorily represent the visual quality of images and medical expert’s satisfaction with images. This paper proposes an innovative use of relative multivariate kurtosis for the evaluation of the most important edges in an image. Multivariate kurtosis allows one to introduce an order among the filtered images and can be used as one of the metrics for image quality evaluation. At present there is no method which would jointly consider individual metrics. Furthermore, these metrics are typically defined by comparing the noisy original and filtered images, which is incorrect since the noisy original cannot serve as a golden standard. In contrast to this, the proposed kurtosis is the absolute measure, which is calculated independently of any reference image and it agrees with the medical expert’s satisfaction to a large extent. The paper presents a numerical procedure for calculating kurtosis and describes results of such calculations for a computer-generated noisy image, images of a general purpose phantom and a cyst phantom, as well as real-life images of thyroid and carotid artery obtained with SonixTouch ultrasound machine. 16 different methods of image despeckling are compared via kurtosis. The paper shows that visually more satisfactory despeckling results are associated with higher kurtosis, and to a certain degree kurtosis can be used as a single metric for evaluation of image quality.

Acousto-Optic Tunable Filter Hyperspectral Microscope Imaging Method for Characterizing Spectra from Foodborne Pathogens.

Science.gov (United States)

Hyperspectral microscope imaging (HMI) method, which provides both spatial and spectral characteristics of samples, can be effective for foodborne pathogen detection. The acousto-optic tunable filter (AOTF)-based HMI method can be used to characterize spectral properties of biofilms formed by Salmon...

Evaluation of multichannel Wiener filters applied to fine resolution passive microwave images of first-year sea ice

Science.gov (United States)

Full, William E.; Eppler, Duane T.

1993-01-01

The effectivity of multichannel Wiener filters to improve images obtained with passive microwave systems was investigated by applying Wiener filters to passive microwave images of first-year sea ice. Four major parameters which define the filter were varied: the lag or pixel offset between the original and the desired scenes, filter length, the number of lines in the filter, and the weight applied to the empirical correlation functions. The effect of each variable on the image quality was assessed by visually comparing the results. It was found that the application of multichannel Wiener theory to passive microwave images of first-year sea ice resulted in visually sharper images with enhanced textural features and less high-frequency noise. However, Wiener filters induced a slight blocky grain to the image and could produce a type of ringing along scan lines traversing sharp intensity contrasts.

MRT letter: Guided filtering of image focus volume for 3D shape recovery of microscopic objects.

Science.gov (United States)

Mahmood, Muhammad Tariq

2014-12-01

In this letter, a shape from focus (SFF) method is proposed that utilizes the guided image filtering to enhance the image focus volume efficiently. First, image focus volume is computed using a conventional focus measure. Then each layer of image focus volume is filtered using guided filtering. In this work, the all-in-focus image, which can be obtained from the initial focus volume, is used as guidance image. Finally, improved depth map is obtained from the filtered image focus volume by maximizing the focus measure along the optical axis. The proposed SFF method is efficient and provides better depth maps. The improved performance is highlighted by conducting several experiments using image sequences of simulated and real microscopic objects. The comparative analysis demonstrates the effectiveness of the proposed SFF method. © 2014 Wiley Periodicals, Inc.

UV Fluorescence Photography of Works of Art : Replacing the Traditional UV Cut Filters with Interference Filters

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Luís BRAVO PEREIRA

2010-09-01

Full Text Available For many years filters like the Kodak Wratten E series, or the equivalent Schneider B+W 415, were used as standard UV cut filters, necessary to obtain good quality on UV Fluorescence photography. The only problem with the use of these filters is that, when they receive the UV radiation that they should remove, they present themselves an internal fluorescence as side effect, that usually reduce contrast and quality on the final image. This article presents the results of our experiences on using some innovative filters, that appeared available on the market in recent years, projected to adsorb UV radiation even more efficiently than with the mentioned above pigment based standard filters: the interference filters for UV rejection (and, usually, for IR rejection too manufactured using interference layers, that present better results than the pigment based filters. The only problem with interference filters type is that they are sensitive to the rays direction and, because of that, they are not adequate to wide-angle lenses. The internal fluorescence for three filters: the B+W 415 UV cut (equivalent to the Kodak Wratten 2E, pigment based, the B+W 486 UV IR cut (an interference type filter, used frequently on digital cameras to remove IR or UV and the Baader UVIR rejection filter (two versions of this interference filter were used had been tested and compared. The final quality of the UV fluorescence images seems to be of a superior quality when compared to the images obtained with classic filters.

An Efficient FPGA Implementation of Optimized Anisotropic Diffusion Filtering of Images

Directory of Open Access Journals (Sweden)

Chandrajit Pal

2016-01-01

Full Text Available Digital image processing is an exciting area of research with a variety of applications including medical, surveillance security systems, defence, and space applications. Noise removal as a preprocessing step helps to improve the performance of the signal processing algorithms, thereby enhancing image quality. Anisotropic diffusion filtering proposed by Perona and Malik can be used as an edge-preserving smoother, removing high-frequency components of images without blurring their edges. In this paper, we present the FPGA implementation of an edge-preserving anisotropic diffusion filter for digital images. The designed architecture completely replaced the convolution operation and implemented the same using simple arithmetic subtraction of the neighboring intensities within a kernel, preceded by multiple operations in parallel within the kernel. To improve the image reconstruction quality, the diffusion coefficient parameter, responsible for controlling the filtering process, has been properly analyzed. Its signal behavior has been studied by subsequently scaling and differentiating the signal. The hardware implementation of the proposed design shows better performance in terms of reconstruction quality and accelerated performance with respect to its software implementation. It also reduces computation, power consumption, and resource utilization with respect to other related works.

Image reconstruction for digital breast tomosynthesis (DBT) by using projection-angle-dependent filter functions

Energy Technology Data Exchange (ETDEWEB)

Park, Yeonok; Park, Chulkyu; Cho, Hyosung; Je, Uikyu; Hong, Daeki; Lee, Minsik; Cho, Heemoon; Choi, Sungil; Koo, Yangseo [Yonsei University, Wonju (Korea, Republic of)

2014-09-15

Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10-30 projections over a limited angle range of 15 - 60 .deg. with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.

Processing of a neutrographic image, using Bosso Filter

International Nuclear Information System (INIS)

Pereda, C.; Bustamante, M.; Henriquez, C.

2006-01-01

The following paper shows the result of the treatment of a neutron radiographic image, obtained in the RECH-1 experimental reactor, making use of the computational image treatment techniques of the IDL software, which are complemented with the Bosso filter method already tested to improve quality in medical diagnosis. These techniques possess an undeniable value as an auxiliary to neutrography, which results can be noticed through this first try with an auxiliary neutrographic image used in PGNAA. These results insinuate that this method should give all its advantages to the neutrographic analysis standards: structural images, density variations, etc

Variation of the count-dependent Metz filter with imaging system modulation transfer function

International Nuclear Information System (INIS)

King, M.A.; Schwinger, R.B.; Penney, B.C.

1986-01-01

A systematic investigation was conducted of how a number of parameters which alter the system modulation transfer function (MTF) influence the count-dependent Metz filter. Since restoration filters are most effective at those frequencies where the object power spectrum dominates that of the noise, it was observed that parameters which significantly degrade the MTF at low spatial frequencies strongly influence the formation of the Metz filter. Thus the radionuclide imaged and the depth of the source in a scattering medium had the most influence. This is because they alter the relative amount of scattered radiation being imaged. For low-energy photon emitters, the collimator employed and the distance from the collimator were found to have less of an influence but still to be significant. These cause alterations in the MTF which are more gradual, and hence are most pronounced at mid to high spatial frequencies. As long as adequate spatial sampling is employed, the Metz filter was determined to be independent of the exact size of the sampling bin width, to a first approximation. For planar and single photon emission computed tomographic (SPECT) imaging, it is shown that two-dimensional filtering with the Metz filter optimized for the imaging conditions is able to deconvolve scatter and other causes of spatial resolution loss while diminishing noise, all in a balanced manner

Mobile Phone Ratiometric Imaging Enables Highly Sensitive Fluorescence Lateral Flow Immunoassays without External Optical Filters.

Science.gov (United States)

Shah, Kamal G; Singh, Vidhi; Kauffman, Peter C; Abe, Koji; Yager, Paul

2018-05-14

Paper-based diagnostic tests based on the lateral flow immunoassay concept promise low-cost, point-of-care detection of infectious diseases, but such assays suffer from poor limits of detection. One factor that contributes to poor analytical performance is a reliance on low-contrast chromophoric optical labels such as gold nanoparticles. Previous attempts to improve the sensitivity of paper-based diagnostics include replacing chromophoric labels with enzymes, fluorophores, or phosphors at the expense of increased fluidic complexity or the need for device readers with costly optoelectronics. Several groups, including our own, have proposed mobile phones as suitable point-of-care readers due to their low cost, ease of use, and ubiquity. However, extant mobile phone fluorescence readers require costly optical filters and were typically validated with only one camera sensor module, which is inappropriate for potential point-of-care use. In response, we propose to couple low-cost ultraviolet light-emitting diodes with long Stokes-shift quantum dots to enable ratiometric mobile phone fluorescence measurements without optical filters. Ratiometric imaging with unmodified smartphone cameras improves the contrast and attenuates the impact of excitation intensity variability by 15×. Practical application was shown with a lateral flow immunoassay for influenza A with nucleoproteins spiked into simulated nasal matrix. Limits of detection of 1.5 and 2.6 fmol were attained on two mobile phones, which are comparable to a gel imager (1.9 fmol), 10× better than imaging gold nanoparticles on a scanner (18 fmol), and >2 orders of magnitude better than gold nanoparticle-labeled assays imaged with mobile phones. Use of the proposed filter-free mobile phone imaging scheme is a first step toward enabling a new generation of highly sensitive, point-of-care fluorescence assays.

Tunable thin-film optical filters for hyperspectral microscopy

Science.gov (United States)

Favreau, Peter F.; Rich, Thomas C.; Prabhat, Prashant; Leavesley, Silas J.

2013-02-01

Hyperspectral imaging was originally developed for use in remote sensing applications. More recently, it has been applied to biological imaging systems, such as fluorescence microscopes. The ability to distinguish molecules based on spectral differences has been especially advantageous for identifying fluorophores in highly autofluorescent tissues. A key component of hyperspectral imaging systems is wavelength filtering. Each filtering technology used for hyperspectral imaging has corresponding advantages and disadvantages. Recently, a new optical filtering technology has been developed that uses multi-layered thin-film optical filters that can be rotated, with respect to incident light, to control the center wavelength of the pass-band. Compared to the majority of tunable filter technologies, these filters have superior optical performance including greater than 90% transmission, steep spectral edges and high out-of-band blocking. Hence, tunable thin-film optical filters present optical characteristics that may make them well-suited for many biological spectral imaging applications. An array of tunable thin-film filters was implemented on an inverted fluorescence microscope (TE 2000, Nikon Instruments) to cover the full visible wavelength range. Images of a previously published model, GFP-expressing endothelial cells in the lung, were acquired using a charge-coupled device camera (Rolera EM-C2, Q-Imaging). This model sample presents fluorescently-labeled cells in a highly autofluorescent environment. Linear unmixing of hyperspectral images indicates that thin-film tunable filters provide equivalent spectral discrimination to our previous acousto-optic tunable filter-based approach, with increased signal-to-noise characteristics. Hence, tunable multi-layered thin film optical filters may provide greatly improved spectral filtering characteristics and therefore enable wider acceptance of hyperspectral widefield microscopy.

Improving Image Matching by Reducing Surface Reflections Using Polarising Filter Techniques

Science.gov (United States)

Conen, N.; Hastedt, H.; Kahmen, O.; Luhmann, T.

2018-05-01

In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud. To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results. However, the filter may influence the camera's orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002) using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (Δc ≤ 4 μm) with the polarising filter in use. Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.

IMPROVING IMAGE MATCHING BY REDUCING SURFACE REFLECTIONS USING POLARISING FILTER TECHNIQUES

Directory of Open Access Journals (Sweden)

N. Conen

2018-05-01

Full Text Available In dense stereo matching applications surface reflections may lead to incorrect measurements and blunders in the resulting point cloud. To overcome the problem of disturbing reflexions polarising filters can be mounted on the camera lens and light source. Reflections in the images can be suppressed by crossing the polarising direction of the filters leading to homogeneous illuminated images and better matching results. However, the filter may influence the camera’s orientation parameters as well as the measuring accuracy. To quantify these effects, a calibration and an accuracy analysis is conducted within a spatial test arrangement according to the German guideline VDI/VDE 2634.1 (2002 using a DSLR with and without polarising filter. In a second test, the interior orientation is analysed in more detail. The results do not show significant changes of the measuring accuracy in object space and only very small changes of the interior orientation (Δc ≤ 4 μm with the polarising filter in use. Since in medical applications many tiny reflections are present and impede robust surface measurements, a prototypic trinocular endoscope is equipped with polarising technique. The interior and relative orientation is determined and analysed. The advantage of the polarising technique for medical image matching is shown in an experiment with a moistened pig kidney. The accuracy and completeness of the resulting point cloud can be improved clearly when using polarising filters. Furthermore, an accuracy analysis using a laser triangulation system is performed and the special reflection properties of metallic surfaces are presented.

Ross filter pairs for metal artefact reduction in x-ray tomography: a case study based on imaging and segmentation of metallic implants

Science.gov (United States)

Arhatari, Benedicta D.; Abbey, Brian

2018-01-01

Ross filter pairs have recently been demonstrated as a highly effective means of producing quasi-monoenergetic beams from polychromatic X-ray sources. They have found applications in both X-ray spectroscopy and for elemental separation in X-ray computed tomography (XCT). Here we explore whether they could be applied to the problem of metal artefact reduction (MAR) for applications in medical imaging. Metal artefacts are a common problem in X-ray imaging of metal implants embedded in bone and soft tissue. A number of data post-processing approaches to MAR have been proposed in the literature, however these can be time-consuming and sometimes have limited efficacy. Here we describe and demonstrate an alternative approach based on beam conditioning using Ross filter pairs. This approach obviates the need for any complex post-processing of the data and enables MAR and segmentation from the surrounding tissue by exploiting the absorption edge contrast of the implant.

An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

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Kai Hu

2013-01-01

Full Text Available A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA to decide weights in a back propagation neural network (BPN. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence.

Science.gov (United States)

Li, Sui-Xian

2018-05-07

Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI). However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ₂ norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence

Directory of Open Access Journals (Sweden)

Sui-Xian Li

2018-05-01

Full Text Available Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI. However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ2 norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

Bowtie filter and water calibration in the improvement of cone beam CT image quality

International Nuclear Information System (INIS)

Li Minghui; Dai Jianrong; Zhang Ke

2010-01-01

Objective: To evaluate the improvement of cone beam CT (CBCT) image quality by using bewtie filter (F 1 ) and water calibration. Methods: First the multi-level gain calibration of the detector panel with the method of Cal 2 calibration was performed, and the CT images of CATPHAN503 with F 0 and bowtie filter were collected, respectively. Then the detector panel using water calibration kit was calibrated, and images were acquired again. Finally, the change of image quality after using F 1 and (or) water calibration method was observed. The observed indexes included low contrast visibility, spatial uniformity, ring artifact, spatial resolution and geometric accuracy. Results: Comparing with the traditional combination of F 0 filter and Cal 2 calibration, the combination of bowtie filter F 1 and water calibration improves low contrast visibility by 13.71%, and spatial uniformity by 54. 42%. Water calibration removes ring artifacts effectively. However, none of them improves spatial resolution and geometric accuracy. Conclusions: The combination of F 1 and water calibration improves CBCT image quality effectively. This improvement is aid to the registration of CBCT images and localization images. (authors)

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

Science.gov (United States)

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Digital filtering and reconstruction of coded aperture images

International Nuclear Information System (INIS)

Tobin, K.W. Jr.

1987-01-01

The real-time neutron radiography facility at the University of Virginia has been used for both transmission radiography and computed tomography. Recently, a coded aperture system has been developed to permit the extraction of three dimensional information from a low intensity field of radiation scattered by an extended object. Short wave-length radiations (e.g. neutrons) are not easily image because of the difficulties in achieving diffraction and refraction with a conventional lens imaging system. By using a coded aperture approach, an imaging system has been developed that records and reconstructs an object from an intensity distribution. This system has a signal-to-noise ratio that is proportional to the total open area of the aperture making it ideal for imaging with a limiting intensity radiation field. The main goal of this research was to develope and implement the digital methods and theory necessary for the reconstruction process. Several real-time video systems, attached to an Intellect-100 image processor, a DEC PDP-11 micro-computer, and a Convex-1 parallel processing mainframe were employed. This system, coupled with theoretical extensions and improvements, allowed for retrieval of information previously unobtainable by earlier optical methods. The effect of thermal noise, shot noise, and aperture related artifacts were examined so that new digital filtering techniques could be constructed and implemented. Results of image data filtering prior to and following the reconstruction process are reported. Improvements related to the different signal processing methods are emphasized. The application and advantages of this imaging technique to the field of non-destructive testing are also discussed

Filtering for distributed mechanical systems using position measurements: perspectives in medical imaging

International Nuclear Information System (INIS)

Moireau, Philippe; Chapelle, Dominique; Tallec, Patrick Le

2009-01-01

We propose an effective filtering methodology designed to perform estimation in a distributed mechanical system using position measurements. As in a previously introduced method, the filter is inspired by robust control feedback, but here we take full advantage of the estimation specificity to choose a feedback law that can act on displacements instead of velocities and still retain the same kind of dissipativity property which guarantees robustness. This is very valuable in many applications for which positions are more readily available than velocities, as in medical imaging. We provide an in-depth analysis of the proposed procedure, as well as detailed numerical assessments using a test problem inspired by cardiac biomechanics, as medical diagnosis assistance is an important perspective for this approach. The method is formulated first for measurements based on Lagrangian displacements, but we then derive a nonlinear extension allowing us to instead consider segmented images, which of course is even more relevant in medical applications

The HURRA filter: An easy method to eliminate collimator artifacts in high-energy gamma camera images.

Science.gov (United States)

Perez-Garcia, H; Barquero, R

The correct determination and delineation of tumor/organ size is crucial in 2-D imaging in 131 I therapy. These images are usually obtained using a system composed of a Gamma camera and high-energy collimator, although the system can produce artifacts in the image. This article analyses these artifacts and describes a correction filter that can eliminate those collimator artifacts. Using free software, ImageJ, a central profile in the image is obtained and analyzed. Two components can be seen in the fluctuation of the profile: one associated with the stochastic nature of the radiation, plus electronic noise and the other periodically across the position in space due to the collimator. These frequencies are analytically obtained and compared with the frequencies in the Fourier transform of the profile. A specially developed filter removes the artifacts in the 2D Fourier transform of the DICOM image. This filter is tested using a 15-cm-diameter Petri dish with 131 I radioactive water (big object size) image, a 131 I clinical pill (small object size) image, and an image of the remainder of the lesion of two patients treated with 3.7GBq (100mCi), and 4.44GBq (120mCi) of 131 I, respectively, after thyroidectomy. The artifact is due to the hexagonal periodic structure of the collimator. The use of the filter on large-sized images reduces the fluctuation by 5.8-3.5%. In small-sized images, the FWHM can be determined in the filtered image, while this is impossible in the unfiltered image. The definition of tumor boundary and the visualization of the activity distribution inside patient lesions improve drastically when the filter is applied to the corresponding images obtained with HE gamma camera. The HURRA filter removes the artifact of high-energy collimator artifacts in planar images obtained with a Gamma camera without reducing the image resolution. It can be applied in any study of patient quantification because the number of counts remains invariant. The filter makes

Adaptive iterated function systems filter for images highly corrupted with fixed - Value impulse noise

Science.gov (United States)

Shanmugavadivu, P.; Eliahim Jeevaraj, P. S.

2014-06-01

The Adaptive Iterated Functions Systems (AIFS) Filter presented in this paper has an outstanding potential to attenuate the fixed-value impulse noise in images. This filter has two distinct phases namely noise detection and noise correction which uses Measure of Statistics and Iterated Function Systems (IFS) respectively. The performance of AIFS filter is assessed by three metrics namely, Peak Signal-to-Noise Ratio (PSNR), Mean Structural Similarity Index Matrix (MSSIM) and Human Visual Perception (HVP). The quantitative measures PSNR and MSSIM endorse the merit of this filter in terms of degree of noise suppression and details/edge preservation respectively, in comparison with the high performing filters reported in the recent literature. The qualitative measure HVP confirms the noise suppression ability of the devised filter. This computationally simple noise filter broadly finds application wherein the images are highly degraded by fixed-value impulse noise.

Application of digital tomosynthesis (DTS) of optimal deblurring filters for dental X-ray imaging

International Nuclear Information System (INIS)

Oh, J. E.; Cho, H. S.; Kim, D. S.; Choi, S. I.; Je, U. K.

2012-01-01

Digital tomosynthesis (DTS) is a limited-angle tomographic technique that provides some of the tomographic benefits of computed tomography (CT) but at reduced dose and cost. Thus, the potential for application of DTS to dental X-ray imaging seems promising. As a continuation of our dental radiography R and D, we developed an effective DTS reconstruction algorithm and implemented it in conjunction with a commercial dental CT system for potential use in dental implant placement. The reconstruction algorithm employed a backprojection filtering (BPF) method based upon optimal deblurring filters to suppress effectively both the blur artifacts originating from the out-focus planes and the high-frequency noise. To verify the usefulness of the reconstruction algorithm, we performed systematic simulation works and evaluated the image characteristics. We also performed experimental works in which DTS images of enhanced anatomical resolution were successfully obtained by using the algorithm and were promising to our ongoing applications to dental X-ray imaging. In this paper, our approach to the development of the DTS reconstruction algorithm and the results are described in detail.

Design and application of finite impulse response digital filters

International Nuclear Information System (INIS)

Miller, T.R.; Sampathkumaran, K.S.

1982-01-01

The finite impulse response (FIR) digital filter is a spatial domain filter with a frequency domain representation. The theory of the FIR filter is presented and techniques are described for designing FIR filters with known frequency response characteristics. Rational design principles are emphasized based on characterization of the imaging system using the modulation transfer function and physical properties of the imaged objects. Bandpass, Wiener, and low-pass filters were designed and applied to 201 Tl myocardial images. The bandpass filter eliminates low-frequency image components that represent background activity and high-frequency components due to noise. The Wiener, or minimum mean square error filter 'sharpens' the image while also reducing noise. The Wiener filter illustrates the power of the FIR technique to design filters with any desired frequency reponse. The low-pass filter, while of relative limited use, is presented to compare it with a popular elementary 'smoothing' filter. (orig.)

Pornographic image recognition and filtering using incremental learning in compressed domain

Science.gov (United States)

Zhang, Jing; Wang, Chao; Zhuo, Li; Geng, Wenhao

2015-11-01

With the rapid development and popularity of the network, the openness, anonymity, and interactivity of networks have led to the spread and proliferation of pornographic images on the Internet, which have done great harm to adolescents' physical and mental health. With the establishment of image compression standards, pornographic images are mainly stored with compressed formats. Therefore, how to efficiently filter pornographic images is one of the challenging issues for information security. A pornographic image recognition and filtering method in the compressed domain is proposed by using incremental learning, which includes the following steps: (1) low-resolution (LR) images are first reconstructed from the compressed stream of pornographic images, (2) visual words are created from the LR image to represent the pornographic image, and (3) incremental learning is adopted to continuously adjust the classification rules to recognize the new pornographic image samples after the covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic images. The experimental results show that the proposed pornographic image recognition method using incremental learning has a higher recognition rate as well as costing less recognition time in the compressed domain.

Blind Source Parameters for Performance Evaluation of Despeckling Filters

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Nagashettappa Biradar

2016-01-01

Full Text Available The speckle noise is inherent to transthoracic echocardiographic images. A standard noise-free reference echocardiographic image does not exist. The evaluation of filters based on the traditional parameters such as peak signal-to-noise ratio, mean square error, and structural similarity index may not reflect the true filter performance on echocardiographic images. Therefore, the performance of despeckling can be evaluated using blind assessment metrics like the speckle suppression index, speckle suppression and mean preservation index (SMPI, and beta metric. The need for noise-free reference image is overcome using these three parameters. This paper presents a comprehensive analysis and evaluation of eleven types of despeckling filters for echocardiographic images in terms of blind and traditional performance parameters along with clinical validation. The noise is effectively suppressed using the logarithmic neighborhood shrinkage (NeighShrink embedded with Stein’s unbiased risk estimation (SURE. The SMPI is three times more effective compared to the wavelet based generalized likelihood estimation approach. The quantitative evaluation and clinical validation reveal that the filters such as the nonlocal mean, posterior sampling based Bayesian estimation, hybrid median, and probabilistic patch based filters are acceptable whereas median, anisotropic diffusion, fuzzy, and Ripplet nonlinear approximation filters have limited applications for echocardiographic images.

Blind Source Parameters for Performance Evaluation of Despeckling Filters.

Science.gov (United States)

Biradar, Nagashettappa; Dewal, M L; Rohit, ManojKumar; Gowre, Sanjaykumar; Gundge, Yogesh

2016-01-01

The speckle noise is inherent to transthoracic echocardiographic images. A standard noise-free reference echocardiographic image does not exist. The evaluation of filters based on the traditional parameters such as peak signal-to-noise ratio, mean square error, and structural similarity index may not reflect the true filter performance on echocardiographic images. Therefore, the performance of despeckling can be evaluated using blind assessment metrics like the speckle suppression index, speckle suppression and mean preservation index (SMPI), and beta metric. The need for noise-free reference image is overcome using these three parameters. This paper presents a comprehensive analysis and evaluation of eleven types of despeckling filters for echocardiographic images in terms of blind and traditional performance parameters along with clinical validation. The noise is effectively suppressed using the logarithmic neighborhood shrinkage (NeighShrink) embedded with Stein's unbiased risk estimation (SURE). The SMPI is three times more effective compared to the wavelet based generalized likelihood estimation approach. The quantitative evaluation and clinical validation reveal that the filters such as the nonlocal mean, posterior sampling based Bayesian estimation, hybrid median, and probabilistic patch based filters are acceptable whereas median, anisotropic diffusion, fuzzy, and Ripplet nonlinear approximation filters have limited applications for echocardiographic images.

Performance tuning for CUDA-accelerated neighborhood denoising filters

Energy Technology Data Exchange (ETDEWEB)

Zheng, Ziyi; Mueller, Klaus [Stony Brook Univ., NY (United States). Center for Visual Computing, Computer Science; Xu, Wei

2011-07-01

Neighborhood denoising filters are powerful techniques in image processing and can effectively enhance the image quality in CT reconstructions. In this study, by taking the bilateral filter and the non-local mean filter as two examples, we discuss their implementations and perform fine-tuning on the targeted GPU architecture. Experimental results show that the straightforward GPU-based neighborhood filters can be further accelerated by pre-fetching. The optimized GPU-accelerated denoising filters are ready for plug-in into reconstruction framework to enable fast denoising without compromising image quality. (orig.)

Image enhancement filters significantly improve reading performance for low vision observers

Science.gov (United States)

Lawton, T. B.

1992-01-01

As people age, so do their photoreceptors; many photoreceptors in central vision stop functioning when a person reaches their late sixties or early seventies. Low vision observers with losses in central vision, those with age-related maculopathies, were studied. Low vision observers no longer see high spatial frequencies, being unable to resolve fine edge detail. We developed image enhancement filters to compensate for the low vision observer's losses in contrast sensitivity to intermediate and high spatial frequencies. The filters work by boosting the amplitude of the less visible intermediate spatial frequencies. The lower spatial frequencies. These image enhancement filters not only reduce the magnification needed for reading by up to 70 percent, but they also increase the observer's reading speed by 2-4 times. A summary of this research is presented.

A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

Directory of Open Access Journals (Sweden)

W. Lu

2017-09-01

Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

Science.gov (United States)

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Design, control, and implementation of LCL-filter-based shunt active power filters

DEFF Research Database (Denmark)

Tang, Yi; Loh, Poh Chiang; Wang, Peng

2011-01-01

This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offer......-loop control system, and active damping implemented with fewer current sensors are all addressed here. An analytical design example is finally presented, being supported with experimental results, to verify its effectiveness and practicality.......This paper concentrates on the design, control and implementation of an LCL-filter-based shunt active power filter (SAPF), which can effectively compensate harmonic currents produced by nonlinear loads in a three-phase three-wire power system. The use of LCL-filter at the output end of SAPF offers...

Relationship between pre-reconstruction filter and accuracy of registration software based on mutual-information maximization. A study of SPECT-MR brain phantom images

International Nuclear Information System (INIS)

Mito, Suzuko; Magota, Keiichi; Arai, Hiroshi; Omote, Hidehiko; Katsuura, Hidenori; Suzuki, Kotaro; Kubo Naoki

2005-01-01

Image registration technique is becoming an increasingly important tool in SPECT. Recently, software based on mutual-information maximization has been developed for automatic multimodality image registration. The accuracy of the software is important for its application to image registration. During SPECT reconstruction, the projection data are pre-filtered in order to reduce Poisson noise, commonly using a Butterworth filter. We have investigated the dependence of the absolute accuracy of MRI-SPECT registration on the cut-off frequencies of a range of Butterworth filters. This study used a 3D Hoffman phantom (Model No. 9000, Data-spectrum Co.). For the reference volume, an magnetization prepared rapid gradient echo (MPRage) sequence was performed on a Vision MRI (Siemence, 1.5 T). For the floating volumes, SPECT data of a phantom including 99m Tc 85 kBq/mL were acquired by a GCA-9300 (Toshiba Medical Systems Co.). During SPECT, the orbito-meatal (OM) line of the phantom was tilted by 5 deg and 15 deg to mimic the incline of a patient's head. The projection data were pre-filtered with Butterworth filters (cut-off frequency varying between 0.24 to 0.94 cycles/cm in 0.02 steps, order 8). The automated registrations were performed using iNRT β version software (Nihon Medi. Co.) and the rotation angles of SPECT for registration were noted. In this study, the registrations of all SPECT data were successful. Graphs of registration rotation angles against cut-off frequencies were scattered and showed no correlation between the two. The registration rotation angles ranged with changing cut-off frequency from -0.4 deg to +3.8 deg at a 5 deg tilt and from +12.7 deg to +19.6 deg at a 15 deg tilt. The registration rotation angles showed variation even for slight differences in cut-off frequencies. The absolute errors were a few degrees for any cut-off frequency. Regardless of the cut-off frequency, automatic registration using this software provides similar results. (author)

Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error.

Science.gov (United States)

Kiani, M A; Sim, K S; Nia, M E; Tso, C P

2015-05-01

A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

Science.gov (United States)

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

Science.gov (United States)

Wutsqa, D. U.; Marwah, M.

2017-06-01

In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

Use of metameric filters for future interference security image structures

Science.gov (United States)

Baloukas, Bill; Larouche, Stéphane; Martinu, Ludvik

2006-02-01

In the present work, we describe innovative approaches and properties that can be added to the already popular thin film optically variable devices (OVD) used on banknotes. We show two practical examples of OVDs, namely (i) a pair of metameric filters offering a hidden image effect as a function of the angle of observation as well as a specific spectral property permitting automatic note readability, and (ii) multi-material filters offering a side-dependent color shift. We first describe the design approach of these new devices followed by their sensitivity to deposition errors especially in the case of the metameric filters where slight thickness variations have a significant effect on the obtained colors. The performance of prototype filters prepared by dual ion beam sputtering (DIBS) is shown.

A reconstruction algorithm for coherent scatter computed tomography based on filtered back-projection

International Nuclear Information System (INIS)

Stevendaal, U. van; Schlomka, J.-P.; Harding, A.; Grass, M.

2003-01-01

Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter form factor of the investigated object. Reconstruction from coherently scattered x-rays is commonly done using algebraic reconstruction techniques (ART). In this paper, we propose an alternative approach based on filtered back-projection. For the first time, a three-dimensional (3D) filtered back-projection technique using curved 3D back-projection lines is applied to two-dimensional coherent scatter projection data. The proposed algorithm is tested with simulated projection data as well as with projection data acquired with a demonstrator setup similar to a multi-line CT scanner geometry. While yielding comparable image quality as ART reconstruction, the modified 3D filtered back-projection algorithm is about two orders of magnitude faster. In contrast to iterative reconstruction schemes, it has the advantage that subfield-of-view reconstruction becomes feasible. This allows a selective reconstruction of the coherent-scatter form factor for a region of interest. The proposed modified 3D filtered back-projection algorithm is a powerful reconstruction technique to be implemented in a CSCT scanning system. This method gives coherent scatter CT the potential of becoming a competitive modality for medical imaging or nondestructive testing

Adaptive nonlocal means filtering based on local noise level for CT denoising

International Nuclear Information System (INIS)

Li, Zhoubo; Trzasko, Joshua D.; Lake, David S.; Blezek, Daniel J.; Manduca, Armando; Yu, Lifeng; Fletcher, Joel G.; McCollough, Cynthia H.

2014-01-01

Purpose: To develop and evaluate an image-domain noise reduction method based on a modified nonlocal means (NLM) algorithm that is adaptive to local noise level of CT images and to implement this method in a time frame consistent with clinical workflow. Methods: A computationally efficient technique for local noise estimation directly from CT images was developed. A forward projection, based on a 2D fan-beam approximation, was used to generate the projection data, with a noise model incorporating the effects of the bowtie filter and automatic exposure control. The noise propagation from projection data to images was analytically derived. The analytical noise map was validated using repeated scans of a phantom. A 3D NLM denoising algorithm was modified to adapt its denoising strength locally based on this noise map. The performance of this adaptive NLM filter was evaluated in phantom studies in terms of in-plane and cross-plane high-contrast spatial resolution, noise power spectrum (NPS), subjective low-contrast spatial resolution using the American College of Radiology (ACR) accreditation phantom, and objective low-contrast spatial resolution using a channelized Hotelling model observer (CHO). Graphical processing units (GPU) implementation of this noise map calculation and the adaptive NLM filtering were developed to meet demands of clinical workflow. Adaptive NLM was piloted on lower dose scans in clinical practice. Results: The local noise level estimation matches the noise distribution determined from multiple repetitive scans of a phantom, demonstrated by small variations in the ratio map between the analytical noise map and the one calculated from repeated scans. The phantom studies demonstrated that the adaptive NLM filter can reduce noise substantially without degrading the high-contrast spatial resolution, as illustrated by modulation transfer function and slice sensitivity profile results. The NPS results show that adaptive NLM denoising preserves the

Median filters as a tool to determine dark noise thresholds in high resolution smartphone image sensors for scientific imaging

Science.gov (United States)

Igoe, Damien P.; Parisi, Alfio V.; Amar, Abdurazaq; Rummenie, Katherine J.

2018-01-01

An evaluation of the use of median filters in the reduction of dark noise in smartphone high resolution image sensors is presented. The Sony Xperia Z1 employed has a maximum image sensor resolution of 20.7 Mpixels, with each pixel having a side length of just over 1 μm. Due to the large number of photosites, this provides an image sensor with very high sensitivity but also makes them prone to noise effects such as hot-pixels. Similar to earlier research with older models of smartphone, no appreciable temperature effects were observed in the overall average pixel values for images taken in ambient temperatures between 5 °C and 25 °C. In this research, hot-pixels are defined as pixels with intensities above a specific threshold. The threshold is determined using the distribution of pixel values of a set of images with uniform statistical properties associated with the application of median-filters of increasing size. An image with uniform statistics was employed as a training set from 124 dark images, and the threshold was determined to be 9 digital numbers (DN). The threshold remained constant for multiple resolutions and did not appreciably change even after a year of extensive field use and exposure to solar ultraviolet radiation. Although the temperature effects' uniformity masked an increase in hot-pixel occurrences, the total number of occurrences represented less than 0.1% of the total image. Hot-pixels were removed by applying a median filter, with an optimum filter size of 7 × 7; similar trends were observed for four additional smartphone image sensors used for validation. Hot-pixels were also reduced by decreasing image resolution. The method outlined in this research provides a methodology to characterise the dark noise behavior of high resolution image sensors for use in scientific investigations, especially as pixel sizes decrease.

Adaptive wiener filter based on Gaussian mixture distribution model for denoising chest X-ray CT image

International Nuclear Information System (INIS)

Tabuchi, Motohiro; Yamane, Nobumoto; Morikawa, Yoshitaka

2008-01-01

In recent decades, X-ray CT imaging has become more important as a result of its high-resolution performance. However, it is well known that the X-ray dose is insufficient in the techniques that use low-dose imaging in health screening or thin-slice imaging in work-up. Therefore, the degradation of CT images caused by the streak artifact frequently becomes problematic. In this study, we applied a Wiener filter (WF) using the universal Gaussian mixture distribution model (UNI-GMM) as a statistical model to remove streak artifact. In designing the WF, it is necessary to estimate the statistical model and the precise co-variances of the original image. In the proposed method, we obtained a variety of chest X-ray CT images using a phantom simulating a chest organ, and we estimated the statistical information using the images for training. The results of simulation showed that it is possible to fit the UNI-GMM to the chest X-ray CT images and reduce the specific noise. (author)

STRUCTURE TENSOR IMAGE FILTERING USING RIEMANNIAN L1 AND L∞ CENTER-OF-MASS

Directory of Open Access Journals (Sweden)

Jesus Angulo

2014-06-01

Full Text Available Structure tensor images are obtained by a Gaussian smoothing of the dyadic product of gradient image. These images give at each pixel a n×n symmetric positive definite matrix SPD(n, representing the local orientation and the edge information. Processing such images requires appropriate algorithms working on the Riemannian manifold on the SPD(n matrices. This contribution deals with structure tensor image filtering based on Lp geometric averaging. In particular, L1 center-of-mass (Riemannian median or Fermat-Weber point and L∞ center-of-mass (Riemannian circumcenter can be obtained for structure tensors using recently proposed algorithms. Our contribution in this paper is to study the interest of L1 and L∞ Riemannian estimators for structure tensor image processing. In particular, we compare both for two image analysis tasks: (i structure tensor image denoising; (ii anomaly detection in structure tensor images.

Enhancement of noisy EDX HRSTEM spectrum-images by combination of filtering and PCA.

Science.gov (United States)

Potapov, Pavel; Longo, Paolo; Okunishi, Eiji

2017-05-01

STEM spectrum-imaging with collecting EDX signal is considered in view of the extraction of maximum information from very noisy data. It is emphasized that spectrum-images with weak EDX signal often suffer from information loss in the course of PCA treatment. The loss occurs when the level of random noise exceeds a certain threshold. Weighted PCA, though potentially helpful in isolation of meaningful variations from noise, might provoke the complete loss of information in the situation of weak EDX signal. Filtering datasets prior PCA can improve the situation and recover the lost information. In particular, Gaussian kernel filters are found to be efficient. A new filter useful in the case of sparse atomic-resolution EDX spectrum-images is suggested. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of the Kalman filter in the automated segmentation of EIT lung images

International Nuclear Information System (INIS)

Zifan, A; Chapman, B E; Liatsis, P

2013-01-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging. (paper)

The use of the Kalman filter in the automated segmentation of EIT lung images.

Science.gov (United States)

Zifan, A; Liatsis, P; Chapman, B E

2013-06-01

In this paper, we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using electrical impedance tomography (EIT). EIT is an emerging, promising, non-invasive imaging modality that produces real-time, low spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a nonlinear ill-posed inverse problem, therefore the problem is usually linearized, which produces impedance-change images, rather than static impedance ones. Such images are highly blurry and fuzzy along object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed with augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle. The proposed method has been validated by using performance statistics such as misclassified area, and false positive rate, and compared to previous approaches. The results show that the proposed automated method can be a fast and reliable segmentation tool for EIT imaging.

Gradient based filtering of digital elevation models

DEFF Research Database (Denmark)

Knudsen, Thomas; Andersen, Rune Carbuhn

We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

Image Denoising Using Interquartile Range Filter with Local Averaging

OpenAIRE

Jassim, Firas Ajil

2013-01-01

Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset. A window of size kXk was implemented to support IQR filter. Each pixel outside the IQR range of the kXk window is treated as noisy pixel. The estimation of the noisy pixels was obtained by local averaging. The essential...

Mammographic image enhancement using wavelet transform and homomorphic filter

Directory of Open Access Journals (Sweden)

F Majidi

2015-12-01

Full Text Available Mammography is the most effective method for the early diagnosis of breast cancer diseases. As mammographic images contain low signal to noise ratio and low contrast, it becomes too difficult for radiologists to analyze mammogram. To deal with the above stated problems, it is very important to enhance the mammographic images using image processing methods. This paper introduces a new image enhancement approach for mammographic images which uses the modified mathematical morphology, wavelet transform and homomorphic filter to suppress the noise of images. For performance evaluation of the proposed method, contrast improvement index (CII and edge preservation index (EPI are adopted. Experimental results on mammographic images from Pejvak Digital Imaging Center (PDIC show that the proposed algorithm improves the two indexes, thereby achieving the goal of enhancing mammographic images.

Despeckling Polsar Images Based on Relative Total Variation Model

Science.gov (United States)

Jiang, C.; He, X. F.; Yang, L. J.; Jiang, J.; Wang, D. Y.; Yuan, Y.

2018-04-01

Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

Digital notch filter based active damping for LCL filters

DEFF Research Database (Denmark)

Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin

2015-01-01

. In contrast, the active damping does not require any dissipation elements, and thus has become of increasing interest. As a result, a vast of active damping solutions have been reported, among which multi-loop control systems and additional sensors are necessary, leading to increased cost and complexity....... In this paper, a notch filter based active damping without the requirement of additional sensors is proposed, where the inverter current is employed as the feedback variable. Firstly, a design method of the notch filter for active damping is presented. The entire system stability has then been investigated...... in the z-domain. Simulations and experiments are carried out to verify the proposed active damping method. Both results have confirmed that the notch filter based active damping can ensure the entire system stability in the case of resonances with a good system performance....

Edge Detection from High Resolution Remote Sensing Images using Two-Dimensional log Gabor Filter in Frequency Domain

International Nuclear Information System (INIS)

Wang, K; Yu, T; Meng, Q Y; Wang, G K; Li, S P; Liu, S H

2014-01-01

Edges are vital features to describe the structural information of images, especially high spatial resolution remote sensing images. Edge features can be used to define the boundaries between different ground objects in high spatial resolution remote sensing images. Thus edge detection is important in the remote sensing image processing. Even though many different edge detection algorithms have been proposed, it is difficult to extract the edge features from high spatial resolution remote sensing image including complex ground objects. This paper introduces a novel method to detect edges from the high spatial resolution remote sensing image based on frequency domain. Firstly, the high spatial resolution remote sensing images are Fourier transformed to obtain the magnitude spectrum image (frequency image) by FFT. Then, the frequency spectrum is analyzed by using the radius and angle sampling. Finally, two-dimensional log Gabor filter with optimal parameters is designed according to the result of spectrum analysis. Finally, dot product between the result of Fourier transform and the log Gabor filter is inverse Fourier transformed to obtain the detections. The experimental result shows that the proposed algorithm can detect edge features from the high resolution remote sensing image commendably

Blurred image restoration using knife-edge function and optimal window Wiener filtering

Science.gov (United States)

Zhou, Shudao; Yan, Wei

2018-01-01

Motion blur in images is usually modeled as the convolution of a point spread function (PSF) and the original image represented as pixel intensities. The knife-edge function can be used to model various types of motion-blurs, and hence it allows for the construction of a PSF and accurate estimation of the degradation function without knowledge of the specific degradation model. This paper addresses the problem of image restoration using a knife-edge function and optimal window Wiener filtering. In the proposed method, we first calculate the motion-blur parameters and construct the optimal window. Then, we use the detected knife-edge function to obtain the system degradation function. Finally, we perform Wiener filtering to obtain the restored image. Experiments show that the restored image has improved resolution and contrast parameters with clear details and no discernible ringing effects. PMID:29377950

Impact of Image Filters and Observations Parameters in CBCT for Identification of Mandibular Osteolytic Lesions.

Science.gov (United States)

Monteiro, Bruna Moraes; Nobrega Filho, Denys Silveira; Lopes, Patrícia de Medeiros Loureiro; de Sales, Marcelo Augusto Oliveira

2012-01-01

The aim of this study was to analyze the influence of filters (algorithms) to improve the image of Cone Beam Computed Tomography (CBCT) in diagnosis of osteolytic lesions of the mandible, in order to establish the protocols for viewing images more suitable for CBCT diagnostics. 15 dry mandibles in which perforations were performed, simulating lesions, were submitted to CBCT examination. Two examiners analyzed the images, using filters to improve image Hard, Normal, and Very Sharp, contained in the iCAT Vision software, and protocols for assessment: axial; sagittal and coronal; and axial, sagittal and coronal planes simultaneously (MPR), on two occasions. The sensitivity and specificity (validity) of the cone beam computed tomography (CBCT) have been demonstrated as the values achieved were above 75% for sensitivity and above 85% for specificity, reaching around 95.5% of sensitivity and 99% of specificity when we used the appropriate observation protocol. It was concluded that the use of filters (algorithms) to improve the CBCT image influences the diagnosis, due to the fact that all measured values were correspondingly higher when it was used the filter Very Sharp, which justifies its use for clinical activities, followed by Hard and Normal filters, in order of decreasing values.

Impact of Image Filters and Observations Parameters in CBCT for Identification of Mandibular Osteolytic Lesions

Directory of Open Access Journals (Sweden)

Bruna Moraes Monteiro

2012-01-01

Full Text Available The aim of this study was to analyze the influence of filters (algorithms to improve the image of Cone Beam Computed Tomography (CBCT in diagnosis of osteolytic lesions of the mandible, in order to establish the protocols for viewing images more suitable for CBCT diagnostics. 15 dry mandibles in which perforations were performed, simulating lesions, were submitted to CBCT examination. Two examiners analyzed the images, using filters to improve image Hard, Normal, and Very Sharp, contained in the iCAT Vision software, and protocols for assessment: axial; sagittal and coronal; and axial, sagittal and coronal planes simultaneously (MPR, on two occasions. The sensitivity and specificity (validity of the cone beam computed tomography (CBCT have been demonstrated as the values achieved were above 75% for sensitivity and above 85% for specificity, reaching around 95.5% of sensitivity and 99% of specificity when we used the appropriate observation protocol. It was concluded that the use of filters (algorithms to improve the CBCT image influences the diagnosis, due to the fact that all measured values were correspondingly higher when it was used the filter Very Sharp, which justifies its use for clinical activities, followed by Hard and Normal filters, in order of decreasing values.

Optimization of recommendations for abdomen computerized tomography based on reconstruction filters, voltage and tube current

International Nuclear Information System (INIS)

Silveira, Vinicius da Costa

2015-01-01

The use of computed tomography has increased significantly over the past decades. In Brazil the use increased more than twofold from 2008 to 2014, in the meantime the abdomen procedures have tripled. The high frequency of this procedure combined by the increasing collective radiation dose in medical exposures, has resulted development tools to maximize the benefit in CT images. This work aimed to establish protocols optimized in abdominal CT through acquisitions parameters and reconstructions techniques based on filters kernels. A sample of patients undergoing abdominal CT in a diagnostic center of Rio de Janeiro was assessed. Had been collected patients information and acquisitions parameters. The phantoms CT image acquisitions were performed by using different voltage values by adjusting the tube current (mAs) to obtain the same value from CTDI vol patients with normal BMI. Afterwards, the CTDIvol values were reduced by 30%, 50% and 60%. All images were reconstructed with low-contrast filters (A) and standard filters (B). The CTDIvol values for patients with normal BMI were 7% higher than in patients with underweight BMI and 30%, 50% and 60% lower than the overweight, obese I and III patients, respectively. The evaluations of image quality showed that variation of the current (mA) and the reconstruction filters did not affect the Hounsfield values. When the contrast-to-noise ratio (CNR) was normalized to CTDIvol, the protocols acquired with 60% reduction of CTDIvol with 140 kV and 80 kV showed CNR 6% lower than the routine. Modifications of the acquisition parameters did not affect spatial resolution, but the post-processing with B filters reduced the spatial frequency by 16%. With reduced the dose of 30%, lesions in the spleen had the CNR higher than 10% routine protocols with 140 kV acquired and post-processed to filter A. The image post-processing with a filter A with a 80kV voltage provided CNR values equal to the routine for the liver lesions with a 30

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

Energy Technology Data Exchange (ETDEWEB)

Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L [Southern Medical University, Guangzhou, Guangdong (China)

2016-06-15

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

International Nuclear Information System (INIS)

Yuan, C; Qi, H; Chen, Z; Wu, S; Xu, Y; Zhou, L

2016-01-01

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.

Impulse Noise Cancellation of Medical Images Using Wavelet Networks and Median Filters

Science.gov (United States)

Sadri, Amir Reza; Zekri, Maryam; Sadri, Saeid; Gheissari, Niloofar

2012-01-01

This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a preprocessing for the second stage. The second step is removing impulse noise with a median filter. The wavelet network presented here is a fixed one without learning. Experimental results show that our method acts on impulse noise effectively, and at the same time preserves chromaticity and image details very well. PMID:23493998

Fast single image dehazing based on image fusion

Science.gov (United States)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

Effect of Post-Reconstruction Gaussian Filtering on Image Quality and Myocardial Blood Flow Measurement with N-13 Ammonia PET

Directory of Open Access Journals (Sweden)

Hyeon Sik Kim

2014-10-01

Full Text Available Objective(s: In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF measurement by dynamic N-13 ammonia positron emission tomography (PET, we compared various reconstruction and filtering methods with image characteristics. Methods: Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; age: 57, 53, and 76 years were reconstructed, using filtered back projection (FBP and ordered subset expectation maximization (OSEM methods. OSEM reconstruction consisted of OSEM_2I, OSEM_4I, and OSEM_6I with 2, 4, and 6 iterations, respectively. The images, reconstructed and filtered by Gaussian filters of 5, 10, and 15 mm, were obtained, as well as non-filtered images. Visual analysis of image quality (IQ was performed using a 3-grade scoring system by 2 independent readers, blinded to the reconstruction and filtering methods of stress images. Then, signal-to-noise ratio (SNR was calculated by noise and contrast recovery (CR. Stress and rest MBF and coronary flow reserve (CFR were obtained for each method. IQ scores, stress and rest MBF, and CFR were compared between the methods, using Chi-square and Kruskal-Wallis tests. Results: In the visual analysis, IQ was significantly higher by 10 mm Gaussian filtering, compared to other sizes of filter (PP=0.923 and 0.855 for readers 1 and 2, respectively. SNR was significantly higher in 10 mm Gaussian filter. There was a significant difference in stress and rest MBF between several vascular territories. However CFR was not significantly different according to various filtering methods. Conclusion: Post-reconstruction Gaussian filtering with a filter size of 10 mm significantly enhances the IQ of N-13 ammonia PET-CT, without changing the results of CFR calculation. .

Effect of Post-Reconstruction Gaussian Filtering on Image Quality and Myocardial Blood Flow Measurement with N-13 Ammonia PET

International Nuclear Information System (INIS)

Kim, Hyeon Sik; Cho, Sang-Geon; Kim, Ju Han; Kwon, Seong Young; Lee, Byeong-il; Bom, Hee-Seung

2014-01-01

In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF) measurement by dynamic N-13 ammonia positron emission tomography (PET), we compared various reconstruction and filtering methods with image characteristics. Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; age: 57, 53, and 76 years) were reconstructed, using filtered back projection (FBP) and ordered subset expectation maximization (OSEM) methods. OSEM reconstruction consisted of OSEM-2I, OSEM-4I, and OSEM-6I with 2, 4, and 6 iterations, respectively. The images, reconstructed and filtered by Gaussian filters of 5, 10, and 15 mm, were obtained, as well as non-filtered images. Visual analysis of image quality (IQ) was performed using a 3-grade scoring system by 2 independent readers, blinded to the reconstruction and filtering methods of stress images. Then, signal-to-noise ratio (SNR) was calculated by noise and contrast recovery (CR). Stress and rest MBF and coronary flow reserve (CFR) were obtained for each method. IQ scores, stress and rest MBF, and CFR were compared between the methods, using Chi-square and Kruskal-Wallis tests. In the visual analysis, IQ was significantly higher by 10 mm Gaussian filtering, compared to other sizes of filter (P<0.001 for both readers). However, no significant difference of IQ was found between FBP and various numbers of iteration in OSEM (P=0.923 and 0.855 for readers 1 and 2, respectively). SNR was significantly higher in 10 mm Gaussian filter. There was a significant difference in stress and rest MBF between several vascular territories. However CFR was not significantly different according to various filtering methods. Post-reconstruction Gaussian filtering with a filter size of 10 mm significantly enhances the IQ of N-13 ammonia PET-CT, without changing the results of CFR calculation

Detection of retinal nerve fiber layer defects in retinal fundus images using Gabor filtering

Science.gov (United States)

Hayashi, Yoshinori; Nakagawa, Toshiaki; Hatanaka, Yuji; Aoyama, Akira; Kakogawa, Masakatsu; Hara, Takeshi; Fujita, Hiroshi; Yamamoto, Tetsuya

2007-03-01

Retinal nerve fiber layer defect (NFLD) is one of the most important findings for the diagnosis of glaucoma reported by ophthalmologists. However, such changes could be overlooked, especially in mass screenings, because ophthalmologists have limited time to search for a number of different changes for the diagnosis of various diseases such as diabetes, hypertension and glaucoma. Therefore, the use of a computer-aided detection (CAD) system can improve the results of diagnosis. In this work, a technique for the detection of NFLDs in retinal fundus images is proposed. In the preprocessing step, blood vessels are "erased" from the original retinal fundus image by using morphological filtering. The preprocessed image is then transformed into a rectangular array. NFLD regions are observed as vertical dark bands in the transformed image. Gabor filtering is then applied to enhance the vertical dark bands. False positives (FPs) are reduced by a rule-based method which uses the information of the location and the width of each candidate region. The detected regions are back-transformed into the original configuration. In this preliminary study, 71% of NFLD regions are detected with average number of FPs of 3.2 per image. In conclusion, we have developed a technique for the detection of NFLDs in retinal fundus images. Promising results have been obtained in this initial study.

An effective coded excitation scheme based on a predistorted FM signal and an optimized digital filter

DEFF Research Database (Denmark)

Misaridis, Thanasis; Jensen, Jørgen Arendt

1999-01-01

This paper presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression filter designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, optimal Chebyshev windows efficiently weight a nearly...... as with pulse excitation (about 1.5 lambda), depending on the filter design criteria. The axial sidelobes are below -40 dB, which is the noise level of the measuring imaging system. The proposed excitation/compression scheme shows good overall performance and stability to the frequency shift due to attenuation...... be removed by weighting. We show that by using a predistorted chirp with amplitude or phase shaping for amplitude ripple reduction and a correlation filter that accounts for the transducer's natural frequency weighting, output sidelobe levels of -35 to -40 dB are directly obtained. When an optimized filter...

基于人体关键部位检测的敏感图像过滤方法%PORNOGRAPHIC IMAGE FILTERING METHOD BASED ON EROTOGENIC-ZONE DETECTION

Institute of Scientific and Technical Information of China (English)

陆蓓; 巩玉旺; 姚金良; 周建政

2011-01-01

目前多数敏感图像过滤方法对皮肤裸露较多或类肤色区域较多的图像容易产生误检.为降低对这类图像的误检率,提出一种基于人体关键部位检测的敏感图像过滤方法.该方法提取肤色特征、表征局部对象外观和形状的HOG(Histograms of Orien-ted Gradient)特征、空间分布特征及描述区域灰度分布的Haar-like等特征,利用Adaboost学习算法,训练得到人体关键部位的分类器,通过此分类器实现敏感图像的过滤.实验表明,该方法能够准确地检测关键部位,可以有效地降低敏感图像的误检率.%At present, many non-pornographic images containing larger exposure of skin area or approximate skin-colour area are often prone to be detected as the pornographic images by most of the pornographic image filtering methods. In order to decrease the false detection rate, a new pornographic image filtering method based on erotogenic-zone detection is proposed in the paper. The method extracts main features, including skin-colour features, HOG features which describe the shape and appearance of local objects, spatial distribution based features and Haar-like features which describe local grayscale distribution, trains and obtains the classifier of erotogenic-zone recognition with Adaboost learning algorithm, and achieves the pornographic image filtering through the classifier. Results gained from the experiments confirmed that this method can precisely detect erotogenic-zone in an image, and can effectively reduce the fault detection rate against nonpornographic images.

Performance evaluation of 3-D enhancement filters for detection of lung cancer from 3-D chest X-ray CT images

International Nuclear Information System (INIS)

Shimizu, Akinobu; Hagai, Makoto; Toriwaki, Jun-ichiro; Hasegawa, Jun-ichi.

1995-01-01

This paper evaluates the performance of several three dimensional enhancement filters used in procedures for detecting lung cancer shadows from three dimensional (3D) chest X-ray CT images. Two dimensional enhancement filters such as Min-DD filter, Contrast filter and N-Quoit filter have been proposed for enhancing cancer shadows in conventional 2D X-ray images. In this paper, we extend each of these 2D filters to a 3D filter and evaluate its performance experimentally by using CT images with artificial and true lung cancer shadows. As a result, we find that these 3D filters are effective for determining the position of a lung cancer shadow in a 3D chest CT image, as compared with the simple procedure such as smoothing filter, and that the performance of these filters become lower in the hilar area due to the influence of the vessel shadows. (author)

Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Sihem SLATNIA

2011-01-01

Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks,extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

Evolutionary Cellular Automata for Image Segmentation and Noise Filtering Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Okba Kazar

2011-01-01

Full Text Available We use an evolutionary process to seek a specialized set of rules among a wide range of rules to be used by Cellular Automata (CA for a range of tasks, extracting edges in a given gray or colour image, noise filtering applied to black-white image. This is the best set of local rules determine the future state of CA in an asynchronous way. The Genetic Algorithm (GA is applied to search the best CA rules that can realize the best edge detection and noise filtering.

Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

Science.gov (United States)

Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

2017-05-01

Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

Linear Regression Based Real-Time Filtering

Directory of Open Access Journals (Sweden)

Misel Batmend

2013-01-01

Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

Comparison of the diagnostic accuracy of direct digital radiography system, filtered images, and subtraction radiography

Directory of Open Access Journals (Sweden)

Wilton Mitsunari Takeshita

2013-01-01

Full Text Available Background: To compare the diagnostic accuracy of three different imaging systems: Direct digital radiography system (DDR-CMOS, four types of filtered images, and a priori and a posteriori registration of digital subtraction radiography (DSR in the diagnosis of proximal defects. Materials and Methods: The teeth were arranged in pairs in 10 blocks of vinyl polysiloxane, and proximal defects were performed with drills of 0.25, 0.5, and 1 mm diameter. Kodak RVG 6100 sensor was used to capture the images. A posteriori DSR registrations were done with Regeemy 0.2.43 and subtraction with Image Tool 3.0. Filtered images were obtained with Kodak Dental Imaging 6.1 software. Images (n = 360 were evaluated by three raters, all experts in dental radiology. Results: Sensitivity and specificity of the area under the receiver operator characteristic (ROC curve (Az were higher for DSR images with all three drills (Az = 0.896, 0.979, and 1.000 for drills 0.25, 0.5, and 1 mm, respectively. The highest values were found for 1-mm drills and the lowest for 0.25-mm drills, with negative filter having the lowest values of all (Az = 0.631. Conclusion: The best method of diagnosis was by using a DSR. The negative filter obtained the worst results. Larger drills showed the highest sensitivity and specificity values of the area under the ROC curve.

Filtered region of interest cone-beam rotational angiography

International Nuclear Information System (INIS)

Schafer, Sebastian; Noeel, Peter B.; Walczak, Alan M.; Hoffmann, Kenneth R.

2010-01-01

Purpose: Cone-beam rotational angiography (CBRA) is widely used in the modern clinical settings. In a number of procedures, the area of interest is often considerably smaller than the field of view (FOV) of the detector, subjecting the patient to potentially unnecessary x-ray dose. The authors therefore propose a filter-based method to reduce the dose in the regions of low interest, while supplying high image quality in the region of interest (ROI). Methods: For such procedures, the authors propose a method of filtered region of interest (FROI)-CBRA. In the authors' approach, a gadolinium filter with a circular central opening is placed into the x-ray beam during image acquisition. The central region is imaged with high contrast, while peripheral regions are subjected to a substantial lower intensity and dose through beam filtering. The resulting images contain a high contrast/intensity ROI, as well as a low contrast/intensity peripheral region, and a transition region in between. To equalize the two regions' intensities, the first projection of the acquisition is performed with and without the filter in place. The equalization relationship, based on Beer's law, is established through linear regression using corresponding filtered and nonfiltered data. The transition region is equalized based on radial profiles. Results: Evaluations in 2D and 3D show no visible difference between conventional FROI-CBRA projection images and reconstructions in the ROI. CNR evaluations show similar image quality in the ROI, with a reduced CNR in the reconstructed peripheral region. In all filtered projection images, the scatter fraction inside the ROI was reduced. Theoretical and experimental dose evaluations show a considerable dose reduction; using a ROI half the original FOV reduces the dose by 60% for the filter thickness of 1.29 mm. Conclusions: These results indicate the potential of FROI-CBRA to reduce the dose to the patient while supplying the physician with the desired

Filtered region of interest cone-beam rotational angiography

Energy Technology Data Exchange (ETDEWEB)

Schafer, Sebastian; Noeel, Peter B.; Walczak, Alan M.; Hoffmann, Kenneth R. [Department of Mechanical Engineering, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Neurosurgery, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States) and Toshiba Stroke Research Center, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Neurosurgery, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Computer Science, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States) and Toshiba Stroke Research Center, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Neurosurgery, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 and Toshiba Stroke Research Center, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Mechanical Engineering, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Neurosurgery, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States); Department of Computer Science, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States) and Toshiba Stroke Research Center, SUNY at Buffalo, 3435 Main Street, Buffalo, New York 14214 (United States)

2010-02-15

Purpose: Cone-beam rotational angiography (CBRA) is widely used in the modern clinical settings. In a number of procedures, the area of interest is often considerably smaller than the field of view (FOV) of the detector, subjecting the patient to potentially unnecessary x-ray dose. The authors therefore propose a filter-based method to reduce the dose in the regions of low interest, while supplying high image quality in the region of interest (ROI). Methods: For such procedures, the authors propose a method of filtered region of interest (FROI)-CBRA. In the authors' approach, a gadolinium filter with a circular central opening is placed into the x-ray beam during image acquisition. The central region is imaged with high contrast, while peripheral regions are subjected to a substantial lower intensity and dose through beam filtering. The resulting images contain a high contrast/intensity ROI, as well as a low contrast/intensity peripheral region, and a transition region in between. To equalize the two regions' intensities, the first projection of the acquisition is performed with and without the filter in place. The equalization relationship, based on Beer's law, is established through linear regression using corresponding filtered and nonfiltered data. The transition region is equalized based on radial profiles. Results: Evaluations in 2D and 3D show no visible difference between conventional FROI-CBRA projection images and reconstructions in the ROI. CNR evaluations show similar image quality in the ROI, with a reduced CNR in the reconstructed peripheral region. In all filtered projection images, the scatter fraction inside the ROI was reduced. Theoretical and experimental dose evaluations show a considerable dose reduction; using a ROI half the original FOV reduces the dose by 60% for the filter thickness of 1.29 mm. Conclusions: These results indicate the potential of FROI-CBRA to reduce the dose to the patient while supplying the physician with

Characteristics of Quoit filter, a digital filter developed for the extraction of circumscribed shadows, and its applications to mammograms

International Nuclear Information System (INIS)

Isobe, Yoshiaki; Ohkubo, Natsumi; Yamamoto, Shinji; Toriwaki, Jun-ichiro; Kobatake, Hidefumi.

1993-01-01

This paper presents a newly developed filter called Quoit filter, which detects circumscribed shadows (concentric circular isolated image), like typical cancer regions. This Quoit filter is based on the mathematical morphology and is found to have interesting facts as follows. (1) Output of this filter can be analytically expressible when an input image is assumed to be a concentric circular model (output is expectable for typical inputs). (2) This filter has an ability to reconstruct original isolated models mentioned in (1) selectively, when this filter is applied sequentially twice. This filter was tested on the detection of cancer regions in X-ray mammograms, and for 12 cancer mammograms, this filter achieved a true-positive cancer detection rate of 100 %. (author)

Despeckle filtering for ultrasound imaging and video II selected applications

CERN Document Server

Loizou, Christos P

2015-01-01

In ultrasound imaging and video visual perception is hindered by speckle multiplicative noise that degrades the quality. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image/video segmentation, texture analysis and encoding in ultrasound imaging and video. The goal of the first book (book 1 of 2 books) was to introduce the problem of speckle in ultrasound image and video as well as the theoretical background, algorithmic steps, and the MatlabTM for the following group of despeckle filters:

Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

Directory of Open Access Journals (Sweden)

Jaakko T. Astola

2005-05-01

Full Text Available Textural features are one of the most important types of useful information contained in images. In practice, these features are commonly masked by noise. Relatively little attention has been paid to texture preserving properties of noise attenuation methods. This stimulates solving the following tasks: (1 to analyze the texture preservation properties of various filters; and (2 to design image processing methods capable to preserve texture features well and to effectively reduce noise. This paper deals with examining texture feature preserving properties of different filters. The study is performed for a set of texture samples and different noise variances. The locally adaptive three-state schemes are proposed for which texture is considered as a particular class. For “detection” of texture regions, several classifiers are proposed and analyzed. As shown, an appropriate trade-off of the designed filter properties is provided. This is demonstrated quantitatively for artificial test images and is confirmed visually for real-life images.

Compressive Sampling based Image Coding for Resource-deficient Visual Communication.

Science.gov (United States)

Liu, Xianming; Zhai, Deming; Zhou, Jiantao; Zhang, Xinfeng; Zhao, Debin; Gao, Wen

2016-04-14

In this paper, a new compressive sampling based image coding scheme is developed to achieve competitive coding efficiency at lower encoder computational complexity, while supporting error resilience. This technique is particularly suitable for visual communication with resource-deficient devices. At the encoder, compact image representation is produced, which is a polyphase down-sampled version of the input image; but the conventional low-pass filter prior to down-sampling is replaced by a local random binary convolution kernel. The pixels of the resulting down-sampled pre-filtered image are local random measurements and placed in the original spatial configuration. The advantages of local random measurements are two folds: 1) preserve high-frequency image features that are otherwise discarded by low-pass filtering; 2) remain a conventional image and can therefore be coded by any standardized codec to remove statistical redundancy of larger scales. Moreover, measurements generated by different kernels can be considered as multiple descriptions of the original image and therefore the proposed scheme has the advantage of multiple description coding. At the decoder, a unified sparsity-based soft-decoding technique is developed to recover the original image from received measurements in a framework of compressive sensing. Experimental results demonstrate that the proposed scheme is competitive compared with existing methods, with a unique strength of recovering fine details and sharp edges at low bit-rates.

Context-based adaptive filtering of interest points in image retrieval

DEFF Research Database (Denmark)

Nguyen, Phuong Giang; Andersen, Hans Jørgen

2009-01-01

Interest points have been used as local features with success in many computer vision applications such as image/video retrieval and object recognition. However, a major issue when using this approach is a large number of interest points detected from each image and created a dense feature space...... a subset of features. Our approach differs from others in a fact that selected feature is based on the context of the given image. Our experimental results show a significant reduction rate of features while preserving the retrieval performance....

Polarization-Insensitive Tunable Optical Filters based on Liquid Crystal Polarization Gratings

Science.gov (United States)

Nicolescu, Elena

Tunable optical filters are widely used for a variety of applications including spectroscopy, optical communication networks, remote sensing, and biomedical imaging and diagnostics. All of these application areas can greatly benefit from improvements in the key characteristics of the tunable optical filters embedded in them. Some of these key parameters include peak transmittance, bandwidth, tuning range, and transition width. In recent years research efforts have also focused on miniaturizing tunable optical filters into physically small packages for compact portable spectroscopy and hyperspectral imaging applications such as real-time medical diagnostics and defense applications. However, it is important that miniaturization not have a detrimental effect on filter performance. The overarching theme of this dissertation is to explore novel configurations of Polarization Gratings (PGs) as simple, low-cost, polarization-insensitive alternatives to conventional optical filtering technologies for applications including hyperspectral imaging and telecommunications. We approach this goal from several directions with a combination of theory and experimental demonstration leading to, in our opinion, a significant contribution to the field. We present three classes of tunable optical filters, the first of which is an angle-filtering scheme where the stop-band wavelengths are redirected off axis and the passband is transmitted on-axis. This is achieved using a stacked configuration of polarization gratings of various thicknesses. To improve this class of filter, we also introduce a novel optical element, the Bilayer Polarization Grating, exhibiting unique optical properties and demonstrating complex anchoring conditions with high quality. The second class of optical filter is analogous to a Lyot filter, utilizing stacks of static or tunable waveplates sandwiched with polarizing elements. However, we introduce a new configuration using PGs and static waveplates to replace

Switching non-local median filter

Science.gov (United States)

Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

2015-06-01

This paper describes a novel image filtering method for removal of random-valued impulse noise superimposed on grayscale images. Generally, it is well known that switching-type median filters are effective for impulse noise removal. In this paper, we propose a more sophisticated switching-type impulse noise removal method in terms of detail-preserving performance. Specifically, the noise detector of the proposed method finds out noise-corrupted pixels by focusing attention on the difference between the value of a pixel of interest (POI) and the median of its neighboring pixel values, and on the POI's isolation tendency from the surrounding pixels. Furthermore, the removal of the detected noise is performed by the newly proposed median filter based on non-local processing, which has superior detail-preservation capability compared to the conventional median filter. The effectiveness and the validity of the proposed method are verified by some experiments using natural grayscale images.

Unsupervised Retinal Vessel Segmentation Using Combined Filters.

Directory of Open Access Journals (Sweden)

Wendeson S Oliveira

Full Text Available Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.

Characterization of the Edges and Contrasts in a digital image with the variation of the Parameters of the High-pass Filters used in the Estimation of Atmospheric Visibility

Directory of Open Access Journals (Sweden)

Martha C. Guzmán-Zapata

2013-11-01

Full Text Available This paper considers the edges and contrasts obtained with high-pass filters used in the estimation of daytime atmospheric visibility from digital images, and the behavior of these edges and contrasts is characterized by varying the parameters of high-pass filters such as the Ideal, Gaussian, and Homomorphic-Gaussian. A synthetic image of regions with different contrasts is used to apply different filters, then, we define an index to measure the quality of the edges obtained in the filtered image and it is used to analyze the results. The results show that both, the filter selection and the selection of its parameters: affects the characteristics and quality of the detected edges in the filtered image, also determine the amount of noise that the filter added to the image (artifacts that were not present in the original image, and also establish if achieved, or not, the edge detection. The results also show that the edge quality index reaches maximum values at certain combinations of the filters parameters, which means that some combinations of parameters reduce situations distorting the edges and distorting atmospheric visibility measures based on the Fourier transform. So these parameters which provide maximum quality edges are established as suitable for use in visibility measurement.

Application of a novel Kalman filter based block matching method to ultrasound images for hand tendon displacement estimation.

Science.gov (United States)

Lai, Ting-Yu; Chen, Hsiao-I; Shih, Cho-Chiang; Kuo, Li-Chieh; Hsu, Hsiu-Yun; Huang, Chih-Chung

2016-01-01

Information about tendon displacement is important for allowing clinicians to not only quantify preoperative tendon injuries but also to identify any adhesive scaring between tendon and adjacent tissue. The Fisher-Tippett (FT) similarity measure has recently been shown to be more accurate than the Laplacian sum of absolute differences (SAD) and Gaussian sum of squared differences (SSD) similarity measures for tracking tendon displacement in ultrasound B-mode images. However, all of these similarity measures can easily be influenced by the quality of the ultrasound image, particularly its signal-to-noise ratio. Ultrasound images of injured hands are unfortunately often of poor quality due to the presence of adhesive scars. The present study investigated a novel Kalman-filter scheme for overcoming this problem. Three state-of-the-art tracking methods (FT, SAD, and SSD) were used to track the displacements of phantom and cadaver tendons, while FT was used to track human tendons. These three tracking methods were combined individually with the proposed Kalman-filter (K1) scheme and another Kalman-filter scheme used in a previous study to optimize the displacement trajectories of the phantom and cadaver tendons. The motion of the human extensor digitorum communis tendon was measured in the present study using the FT-K1 scheme. The experimental results indicated that SSD exhibited better accuracy in the phantom experiments, whereas FT exhibited better performance for tracking real tendon motion in the cadaver experiments. All three tracking methods were influenced by the signal-to-noise ratio of the images. On the other hand, the K1 scheme was able to optimize the tracking trajectory of displacement in all experiments, even from a location with a poor image quality. The human experimental data indicated that the normal tendons were displaced more than the injured tendons, and that the motion ability of the injured tendon was restored after appropriate rehabilitation

Graphic filter library implemented in CUDA language

OpenAIRE

Peroutková, Hedvika

2009-01-01

This thesis deals with the problem of reducing computation time of raster image processing by parallel computing on graphics processing unit. Raster image processing thereby refers to the application of graphic filters, which can be applied in sequence with different settings. This thesis evaluates the suitability of using parallelization on graphic card for raster image adjustments based on multicriterial choice. Filters are implemented for graphics processing unit in CUDA language. Opacity ...

Cross-correlated imaging of distributed mode filtering rod fiber

DEFF Research Database (Denmark)

Laurila, Marko; Barankov, Roman; Jørgensen, Mette Marie

2013-01-01

We analyze the modal properties of an 85μm core distributed mode filtering rod fiber using cross-correlated (C2) imaging. We evaluate suppression of higher-order modes (HOMs) under severely misaligned mode excitation and identify a single-mode regime where HOMs are suppressed by more than 20dB....

Kalman filtered MR temperature imaging for laser induced thermal therapies.

Science.gov (United States)

Fuentes, D; Yung, J; Hazle, J D; Weinberg, J S; Stafford, R J

2012-04-01

The feasibility of using a stochastic form of Pennes bioheat model within a 3-D finite element based Kalman filter (KF) algorithm is critically evaluated for the ability to provide temperature field estimates in the event of magnetic resonance temperature imaging (MRTI) data loss during laser induced thermal therapy (LITT). The ability to recover missing MRTI data was analyzed by systematically removing spatiotemporal information from a clinical MR-guided LITT procedure in human brain and comparing predictions in these regions to the original measurements. Performance was quantitatively evaluated in terms of a dimensionless L(2) (RMS) norm of the temperature error weighted by acquisition uncertainty. During periods of no data corruption, observed error histories demonstrate that the Kalman algorithm does not alter the high quality temperature measurement provided by MR thermal imaging. The KF-MRTI implementation considered is seen to predict the bioheat transfer with RMS error 10 sec.

Applying Enhancement Filters in the Pre-processing of Images of Lymphoma

International Nuclear Information System (INIS)

Silva, Sérgio Henrique; Do Nascimento, Marcelo Zanchetta; Neves, Leandro Alves; Batista, Valério Ramos

2015-01-01

Lymphoma is a type of cancer that affects the immune system, and is classified as Hodgkin or non-Hodgkin. It is one of the ten types of cancer that are the most common on earth. Among all malignant neoplasms diagnosed in the world, lymphoma ranges from three to four percent of them. Our work presents a study of some filters devoted to enhancing images of lymphoma at the pre-processing step. Here the enhancement is useful for removing noise from the digital images. We have analysed the noise caused by different sources like room vibration, scraps and defocusing, and in the following classes of lymphoma: follicular, mantle cell and B-cell chronic lymphocytic leukemia. The filters Gaussian, Median and Mean-Shift were applied to different colour models (RGB, Lab and HSV). Afterwards, we performed a quantitative analysis of the images by means of the Structural Similarity Index. This was done in order to evaluate the similarity between the images. In all cases we have obtained a certainty of at least 75%, which rises to 99% if one considers only HSV. Namely, we have concluded that HSV is an important choice of colour model at pre-processing histological images of lymphoma, because in this case the resulting image will get the best enhancement

SU-D-207-07: Implementation of Full/half Bowtie Filter Model in a Commercial Treatment Planning System for Kilovoltage X-Ray Imaging Dose Estimation

International Nuclear Information System (INIS)

Kim, S; Alaei, P

2015-01-01

Purpose: To implement full/half bowtie filter models in a commercial treatment planning system (TPS) to calculate kilovoltage (kV) x-ray imaging dose of Varian On-Board Imager (OBI) cone beam CT (CBCT) system. Methods: Full/half bowtie filters of Varian OBI were created as compensator models in Pinnacle TPS (version 9.6) using Matlab software (version 2011a). The profiles of both bowtie filters were acquired from the manufacturer, imported into the Matlab system and hard coded in binary file format. A Pinnacle script was written to import each bowtie filter data into a Pinnacle treatment plan as a compensator. A kV x-ray beam model without including the compensator model was commissioned per each bowtie filter setting based on percent depth dose and lateral profile data acquired from Monte Carlo simulations. To validate the bowtie filter models, a rectangular water phantom was generated in the planning system and an anterior/posterior beam with each bowtie filter was created. Using the Pinnacle script, each bowtie filter compensator was added to the treatment plan. Lateral profile at the depth of 3cm and percent depth dose were measured using an ion chamber and compared with the data extracted from the treatment plans. Results: The kV x-ray beams for both full and half bowtie filter have been modeled in a commercial TPS. The difference of lateral and depth dose profiles between dose calculations and ion chamber measurements were within 6%. Conclusion: Both full/half bowtie filter models provide reasonable results in kV x-ray dose calculations in the water phantom. This study demonstrates the possibility of using a model-based treatment planning system to calculate the kV imaging dose for both full and half bowtie filter modes. Further study is to be performed to evaluate the models in clinical situations

Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

Institute of Scientific and Technical Information of China (English)

Zhaoxia PU; Joshua HACKER

2009-01-01

This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

FLOWING BILATERAL FILTER: DEFINITION AND IMPLEMENTATIONS

Directory of Open Access Journals (Sweden)

Maxime Moreaud

2015-06-01

Full Text Available The bilateral filter plays a key role in image processing applications due to its intuitive parameterization and its high quality filter result, smoothing homogeneous regions while preserving the edges of the objects. Considering the image as a topological relief, seeing pixel intensities as peaks and valleys, we introduce a way to control the tonal weighting coefficients, the flowing bilateral filter, reducing "halo" artifacts typically produced by the regular bilateral filter around a large peak surrounded by two valleys of lower values. In this paper we propose to investigate exact and approximated versions of CPU and parallel GPU (Graphical Processing Unit based implementations of the regular and flowing bilateral filter using the NVidia CUDA API. Fast implementations of these filters are important for the processing of large 3D volumes up to several GB acquired by x-ray or electron tomography.

A mobile and web application-based recommendation system using color quantization and collaborative filtering

OpenAIRE

KAYA, FİDAN; YILDIZ, GÜREL; KAVAK, ADNAN

2015-01-01

In this paper, a recommendation system based on a mobile and web application is proposed for indoor decoration. The main contribution of this work is to apply two-stage filtering using linear matching and collaborative filtering to make recommendations. In the mobile application part, the image of the medium captured by a mobile phone is analyzed using color quantization methods, and these color analysis results along with other user-defined parameters such as height, width, and type of the p...

Image processing based detection of lung cancer on CT scan images

Science.gov (United States)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

DAF: differential ACE filtering image quality assessment by automatic color equalization

Science.gov (United States)

Ouni, S.; Chambah, M.; Saint-Jean, C.; Rizzi, A.

2008-01-01

Ideally, a quality assessment system would perceive and measure image or video impairments just like a human being. But in reality, objective quality metrics do not necessarily correlate well with perceived quality [1]. Plus, some measures assume that there exists a reference in the form of an "original" to compare to, which prevents their usage in digital restoration field, where often there is no reference to compare to. That is why subjective evaluation is the most used and most efficient approach up to now. But subjective assessment is expensive, time consuming and does not respond, hence, to the economic requirements [2,3]. Thus, reliable automatic methods for visual quality assessment are needed in the field of digital film restoration. The ACE method, for Automatic Color Equalization [4,6], is an algorithm for digital images unsupervised enhancement. It is based on a new computational approach that tries to model the perceptual response of our vision system merging the Gray World and White Patch equalization mechanisms in a global and local way. Like our vision system ACE is able to adapt to widely varying lighting conditions, and to extract visual information from the environment efficaciously. Moreover ACE can be run in an unsupervised manner. Hence it is very useful as a digital film restoration tool since no a priori information is available. In this paper we deepen the investigation of using the ACE algorithm as a basis for a reference free image quality evaluation. This new metric called DAF for Differential ACE Filtering [7] is an objective quality measure that can be used in several image restoration and image quality assessment systems. In this paper, we compare on different image databases, the results obtained with DAF and with some subjective image quality assessments (Mean Opinion Score MOS as measure of perceived image quality). We study also the correlation between objective measure and MOS. In our experiments, we have used for the first image

Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

Noninvasive mapping of water diffusional exchange in the human brain using filter-exchange imaging.

Science.gov (United States)

Nilsson, Markus; Lätt, Jimmy; van Westen, Danielle; Brockstedt, Sara; Lasič, Samo; Ståhlberg, Freddy; Topgaard, Daniel

2013-06-01

We present the first in vivo application of the filter-exchange imaging protocol for diffusion MRI. The protocol allows noninvasive mapping of the rate of water exchange between microenvironments with different self-diffusivities, such as the intracellular and extracellular spaces in tissue. Since diffusional water exchange across the cell membrane is a fundamental process in human physiology and pathophysiology, clinically feasible and noninvasive imaging of the water exchange rate would offer new means to diagnose disease and monitor treatment response in conditions such as cancer and edema. The in vivo use of filter-exchange imaging was demonstrated by studying the brain of five healthy volunteers and one intracranial tumor (meningioma). Apparent exchange rates in white matter range from 0.8±0.08 s(-1) in the internal capsule, to 1.6±0.11 s(-1) for frontal white matter, indicating that low values are associated with high myelination. Solid tumor displayed values of up to 2.9±0.8 s(-1). In white matter, the apparent exchange rate values suggest intra-axonal exchange times in the order of seconds, confirming the slow exchange assumption in the analysis of diffusion MRI data. We propose that filter-exchange imaging could be used clinically to map the water exchange rate in pathologies. Filter-exchange imaging may also be valuable for evaluating novel therapies targeting the function of aquaporins. Copyright © 2012 Wiley Periodicals, Inc.

Spatio-spectral color filter array design for optimal image recovery.

Science.gov (United States)

Hirakawa, Keigo; Wolfe, Patrick J

2008-10-01

In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array-a physical construction whereby only a single color value is measured at each pixel location. Owing to the growing ubiquity of color imaging and display devices, much recent work has focused on the implications of such arrays for subsequent digital processing, including in particular the canonical demosaicking task of reconstructing a full color image from spatially subsampled and incomplete color data acquired under a particular choice of array pattern. In contrast to the majority of the demosaicking literature, we consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and-after proving sub-optimality of a wide class of existing array patterns-provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Scattering angle-based filtering via extension in velocity

KAUST Repository

Kazei, Vladimir; Tessmer, Ekkehart; Alkhalifah, Tariq

2016-01-01

The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

Scattering angle-based filtering via extension in velocity

KAUST Repository

Kazei, Vladimir

2016-09-06

The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

Real-time MR diffusion tensor and Q-ball imaging using Kalman filtering

International Nuclear Information System (INIS)

Poupon, C.; Roche, A.; Dubois, J.; Mangin, J.F.; Poupon, F.

2008-01-01

Diffusion magnetic resonance imaging (dMRI) has become an established research tool for the investigation of tissue structure and orientation. In this paper, we present a method for real-time processing of diffusion tensor and Q-ball imaging. The basic idea is to use Kalman filtering framework to fit either the linear tensor or Q-ball model. Because the Kalman filter is designed to be an incremental algorithm, it naturally enables updating the model estimate after the acquisition of any new diffusion-weighted volume. Processing diffusion models and maps during ongoing scans provides a new useful tool for clinicians, especially when it is not possible to predict how long a subject may remain still in the magnet. First, we introduce the general linear models corresponding to the two diffusion tensor and analytical Q-ball models of interest. Then, we present the Kalman filtering framework and we focus on the optimization of the diffusion orientation sets in order to speed up the convergence of the online processing. Last, we give some results on a healthy volunteer for the online tensor and the Q-ball model, and we make some comparisons with the conventional offline techniques used in the literature. We could achieve full real-time for diffusion tensor imaging and deferred time for Q-ball imaging, using a single workstation. (authors)

Video-based noncooperative iris image segmentation.

Science.gov (United States)

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

Evaluation of non-linear adaptive smoothing filter by digital phantom

International Nuclear Information System (INIS)

Sato, Kazuhiro; Ishiya, Hiroki; Oshita, Ryosuke; Yanagawa, Isao; Goto, Mitsunori; Mori, Issei

2008-01-01

As a result of the development of multi-slice CT, diagnoses based on three-dimensional reconstruction images and multi-planar reconstruction have spread. For these applications, which require high z-resolution, thin slice imaging is essential. However, because z-resolution is always based on a trade-off with image noise, thin slice imaging is necessarily accompanied by an increase in noise level. To improve the quality of thin slice images, a non-linear adaptive smoothing filter has been developed, and is being widely applied to clinical use. We developed a digital bar pattern phantom for the purpose of evaluating the effect of this filter and attempted evaluation from an addition image of the bar pattern phantom and the image of the water phantom. The effect of this filter was changed in a complex manner by the contrast and spatial frequency of the original image. We have confirmed the reduced effect of image noise in the low frequency component of the image, but decreased contrast or increased quantity of noise in the image of the high frequency component. This result represents the effect of change in the adaptation of this filter. The digital phantom was useful for this evaluation, but to understand the total effect of filtering, much improvement of the shape of the digital phantom is required. (author)

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

Directory of Open Access Journals (Sweden)

Yaozhong Luo

2017-01-01

Full Text Available Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%, the second highest TPVF (85.34%, and the second lowest FPVF (4.48%.

Filtered Rayleigh Scattering Measurements in a Buoyant Flow Field

National Research Council Canada - National Science Library

Meents, Steven M

2008-01-01

Filtered Rayleigh Scattering (FRS) is a non-intrusive, laser-based flow characterization technique that consists of a narrow linewidth laser, a molecular absorption filter, and a high resolution camera behind the filter to record images...

Identifying city PV roof resource based on Gabor filter

Science.gov (United States)

Ruhang, Xu; Zhilin, Liu; Yong, Huang; Xiaoyu, Zhang

2017-06-01

To identify a city’s PV roof resources, the area and ownership distribution of residential buildings in an urban district should be assessed. To achieve this assessment, remote sensing data analysing is a promising approach. Urban building roof area estimation is a major topic for remote sensing image information extraction. There are normally three ways to solve this problem. The first way is pixel-based analysis, which is based on mathematical morphology or statistical methods; the second way is object-based analysis, which is able to combine semantic information and expert knowledge; the third way is signal-processing view method. This paper presented a Gabor filter based method. This result shows that the method is fast and with proper accuracy.

A Filtering Approach for Image-Guided Surgery With a Highly Articulated Surgical Snake Robot.

Science.gov (United States)

Tully, Stephen; Choset, Howie

2016-02-01

The objective of this paper is to introduce a probabilistic filtering approach to estimate the pose and internal shape of a highly flexible surgical snake robot during minimally invasive surgery. Our approach renders a depiction of the robot that is registered to preoperatively reconstructed organ models to produce a 3-D visualization that can be used for surgical feedback. Our filtering method estimates the robot shape using an extended Kalman filter that fuses magnetic tracker data with kinematic models that define the motion of the robot. Using Lie derivative analysis, we show that this estimation problem is observable, and thus, the shape and configuration of the robot can be successfully recovered with a sufficient number of magnetic tracker measurements. We validate this study with benchtop and in-vivo image-guidance experiments in which the surgical robot was driven along the epicardial surface of a porcine heart. This paper introduces a filtering approach for shape estimation that can be used for image guidance during minimally invasive surgery. The methods being introduced in this paper enable informative image guidance for highly articulated surgical robots, which benefits the advancement of robotic surgery.

Correlation study of effect of additional filter on radiation dose and image quality in digital mammography

International Nuclear Information System (INIS)

Liu Jie; Liu Peifang; Wang Hongbin; Zhang Shuping; Liu Xueou

2012-01-01

Objective: To explore the effect of different additional filters on radiation dose and image quality in digital mammography. Methods: Hologic company's Selenia digital mammography machine and the post-processing workstations and 5 M high resolution medical monitor were used in this study. Mammography phantoms with the thickness from 1.6 cm to 8.6 cm were used to simulate human breast tissue. The same exposure conditions, pressure, compression thickness, the anode were employed with the additional filters of Mo and Rh under the automatic and manual exposure mode. The image kV, mAs, pressure, filter, average glandular dose (AGD), entrance surface dose (ESD), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and image score according to ACR criteria were recorded for the two additional filters. Paired sample t test was performed to compare the indices of Mo and Rh groups by using SPSS 17.0. Results: AGD and ESD of Rh and Mo group were both higher with the increase of the thickness of all the phantoms. AGD, ESD and their increased value of Rh filter(1.484 ± 1.041, 7.969 ± 7.633, 0.423 ± 0.190 and 3.057 ± 2.139) were lower than those of Mo filter (1.915 ± 1.301, 12.516 ± 11.632, 0.539 ±0.246 and 4.731 ± 3.294), in all the phantoms with different thickness (t values were 4.614, 3.209, 3.396 and 3.605, P<0.05). SNR, CNR, and image score of Rh and Mo group both decreased with the increase of the thickness of all the phantoms. There were no statistical difference (P>0.05). Conclusions: Compared with Mo filter, Rh filter could reduce the radiation dose, and this advantage is more obvious in the thicker phantom when the same image quality is required. (authors)

CLASSIFICATION OF HYPERSPECTRAL DATA BASED ON GUIDED FILTERING AND RANDOM FOREST

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H. Ma

2017-09-01

Full Text Available Hyperspectral images usually consist of more than one hundred spectral bands, which have potentials to provide rich spatial and spectral information. However, the application of hyperspectral data is still challengeable due to “the curse of dimensionality”. In this context, many techniques, which aim to make full use of both the spatial and spectral information, are investigated. In order to preserve the geometrical information, meanwhile, with less spectral bands, we propose a novel method, which combines principal components analysis (PCA, guided image filtering and the random forest classifier (RF. In detail, PCA is firstly employed to reduce the dimension of spectral bands. Secondly, the guided image filtering technique is introduced to smooth land object, meanwhile preserving the edge of objects. Finally, the features are fed into RF classifier. To illustrate the effectiveness of the method, we carry out experiments over the popular Indian Pines data set, which is collected by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS sensor. By comparing the proposed method with the method of only using PCA or guided image filter, we find that effect of the proposed method is better.

Kernel-based noise filtering of neutron detector signals

International Nuclear Information System (INIS)

Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

2007-01-01

This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

Precision of quantitative computed tomography texture analysis using image filtering: A phantom study for scanner variability.

Science.gov (United States)

Yasaka, Koichiro; Akai, Hiroyuki; Mackin, Dennis; Court, Laurence; Moros, Eduardo; Ohtomo, Kuni; Kiryu, Shigeru

2017-05-01

Quantitative computed tomography (CT) texture analyses for images with and without filtration are gaining attention to capture the heterogeneity of tumors. The aim of this study was to investigate how quantitative texture parameters using image filtering vary among different computed tomography (CT) scanners using a phantom developed for radiomics studies.A phantom, consisting of 10 different cartridges with various textures, was scanned under 6 different scanning protocols using four CT scanners from four different vendors. CT texture analyses were performed for both unfiltered images and filtered images (using a Laplacian of Gaussian spatial band-pass filter) featuring fine, medium, and coarse textures. Forty-five regions of interest were placed for each cartridge (x) in a specific scan image set (y), and the average of the texture values (T(x,y)) was calculated. The interquartile range (IQR) of T(x,y) among the 6 scans was calculated for a specific cartridge (IQR(x)), while the IQR of T(x,y) among the 10 cartridges was calculated for a specific scan (IQR(y)), and the median IQR(y) was then calculated for the 6 scans (as the control IQR, IQRc). The median of their quotient (IQR(x)/IQRc) among the 10 cartridges was defined as the variability index (VI).The VI was relatively small for the mean in unfiltered images (0.011) and for standard deviation (0.020-0.044) and entropy (0.040-0.044) in filtered images. Skewness and kurtosis in filtered images featuring medium and coarse textures were relatively variable across different CT scanners, with VIs of 0.638-0.692 and 0.430-0.437, respectively.Various quantitative CT texture parameters are robust and variable among different scanners, and the behavior of these parameters should be taken into consideration.

Block-Based Compressed Sensing for Neutron Radiation Image Using WDFB

Directory of Open Access Journals (Sweden)

Wei Jin

2015-01-01

Full Text Available An ideal compression method for neutron radiation image should have high compression ratio while keeping more details of the original image. Compressed sensing (CS, which can break through the restrictions of sampling theorem, is likely to offer an efficient compression scheme for the neutron radiation image. Combining wavelet transform with directional filter banks, a novel nonredundant multiscale geometry analysis transform named Wavelet Directional Filter Banks (WDFB is constructed and applied to represent neutron radiation image sparsely. Then, the block-based CS technique is introduced and a high performance CS scheme for neutron radiation image is proposed. By performing two-step iterative shrinkage algorithm the problem of L1 norm minimization is solved to reconstruct neutron radiation image from random measurements. The experiment results demonstrate that the scheme not only improves the quality of reconstructed image obviously but also retains more details of original image.

Perception-Based Filtering for MMOGs

Directory of Open Access Journals (Sweden)

Souad El Merhebi

2008-01-01

Full Text Available Online games have exploded in the last few years. These games face several problems linked to scalability and interactivity. In fact, online games should provide a quick feedback of users' interactions as well as a coherent view of the shared world. However, the search for enhanced scalability dramatically increases message exchange. Such an increase consumes processing power and bandwidth, and thus limits interactivity, consistency, and scalability. To reduce the rate of message exchange, distributed virtual environment systems use filtering techniques such as interest management that filters messages according to users' interests in the world. These interests are influenced by perceptual facts which we study in this paper in order to build upon them a perception-based filtering technique. This technique satisfies users' needs by precisely providing an exact filtering which is more efficient than other techniques.

A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising.

Directory of Open Access Journals (Sweden)

Khan Bahadar Khan

Full Text Available The exploration of retinal vessel structure is colossally important on account of numerous diseases including stroke, Diabetic Retinopathy (DR and coronary heart diseases, which can damage the retinal vessel structure. The retinal vascular network is very hard to be extracted due to its spreading and diminishing geometry and contrast variation in an image. The proposed technique consists of unique parallel processes for denoising and extraction of blood vessels in retinal images. In the preprocessing section, an adaptive histogram equalization enhances dissimilarity between the vessels and the background and morphological top-hat filters are employed to eliminate macula and optic disc, etc. To remove local noise, the difference of images is computed from the top-hat filtered image and the high-boost filtered image. Frangi filter is applied at multi scale for the enhancement of vessels possessing diverse widths. Segmentation is performed by using improved Otsu thresholding on the high-boost filtered image and Frangi's enhanced image, separately. In the postprocessing steps, a Vessel Location Map (VLM is extracted by using raster to vector transformation. Postprocessing steps are employed in a novel way to reject misclassified vessel pixels. The final segmented image is obtained by using pixel-by-pixel AND operation between VLM and Frangi output image. The method has been rigorously analyzed on the STARE, DRIVE and HRF datasets.

Bayesian target tracking based on particle filter

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

GPU Accelerated Vector Median Filter

Science.gov (United States)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Influence of different anode/filter combination on radiation dose and image quality in digital mammography

International Nuclear Information System (INIS)

Liu Jie; Liu Peifang; Zhang Lianlian; Ma Wenjuan

2013-01-01

Objective: To explore the effect of different anode/filter combination on radiation dose and image quality in digital mammography, so as to choose optimal anode/filter combination to reduce radiation injury without scarifying image quality. Methods: Mammography accredition phantoms with the thickness from 1.6 cm to 8.6 cm were used to simulate human breast tissue. The same exposure conditions, pressure, compression thickness. and different anode/filter combination were employed under the automatic and manual exposure modes. The image kV, mAs, pressure, filter, average glandular dose (ACD), contrast to noise ratio (CNR) were recorded and the figure of merit (FOM) was calculated. SPSS 17.0 and one-way analysis of variance were used in the statistical analysis. Results: As the phantom thickness increase, the ACD values which were acquired with Mo/Mo, Mo/Rh, and W/Ag three different anode/filter combinations were increased, but CNR and FOM values were decreased, ACD, CNR, and FOM values which were acquired in the phantom with different thickness, and three different anode/filter combinations were statistically different (P=0.000, respectively). The ACD values of Mo/Mo were lowest. For 1.6 cm-2.6 cm phantom thicknesses, the FOMs of Mo/Rh were lowest, and for 3.6 cm-8.6 cm phantom thicknesses, the FOMs of W/Ag were lowest. Conclusion: Phantom thickness in 1.6 cm-2.6 cm and 3.6 cm-8.6 cm. Mo/Rh combination and W/Ag combination respectively can achieve the highest FOM, and can provide the best imaging quality with low radiation dose. (authors)

Automatic detection of solar features in HSOS full-disk solar images using guided filter

Science.gov (United States)

Yuan, Fei; Lin, Jiaben; Guo, Jingjing; Wang, Gang; Tong, Liyue; Zhang, Xinwei; Wang, Bingxiang

2018-02-01

A procedure is introduced for the automatic detection of solar features using full-disk solar images from Huairou Solar Observing Station (HSOS), National Astronomical Observatories of China. In image preprocessing, median filter is applied to remove the noises. Guided filter is adopted to enhance the edges of solar features and restrain the solar limb darkening, which is first introduced into the astronomical target detection. Then specific features are detected by Otsu algorithm and further threshold processing technique. Compared with other automatic detection procedures, our procedure has some advantages such as real time and reliability as well as no need of local threshold. Also, it reduces the amount of computation largely, which is benefited from the efficient guided filter algorithm. The procedure has been tested on one month sequences (December 2013) of HSOS full-disk solar images and the result shows that the number of features detected by our procedure is well consistent with the manual one.

Demosaicing and Superresolution for Color Filter Array via Residual Image Reconstruction and Sparse Representation

OpenAIRE

Sun, Guangling

2012-01-01

A framework of demosaicing and superresolution for color filter array (CFA) via residual image reconstruction and sparse representation is presented.Given the intermediate image produced by certain demosaicing and interpolation technique, a residual image between the final reconstruction image and the intermediate image is reconstructed using sparse representation.The final reconstruction image has richer edges and details than that of the intermediate image. Specifically, a generic dictionar...

Single-Phase LLCL-Filter-based Grid-Tied Inverter with Low-Pass Filter Based Capacitor Current Feedback Active damper

DEFF Research Database (Denmark)

Liu, Yuan; Wu, Weimin; Li, Yun

2016-01-01

The capacitor-current-feedback active damping method is attractive for high-order-filter-based high power grid-tied inverter when the grid impedance varies within a wide range. In order to improve the system control bandwidth and attenuate the high order grid background harmonics by using the quasi....... In this paper, a low pass filter is proposed to be inserted in the capacitor current feedback loop op LLCL-filter based grid-tied inverter together with a digital proportional and differential compensator. The detailed theoretical analysis is given. For verification, simulations on a 2kW/220V/10kHz LLCL...

A nowcasting technique based on application of the particle filter blending algorithm

Science.gov (United States)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

SU-F-J-28: Development of a New Imaging Filter to Remove the Shadows From the Carbon Fiber Grid Table Top

Energy Technology Data Exchange (ETDEWEB)

Maehana, W [Kanagawa Cancer Center, Yokohama, Kanagawa (Japan); Yokohama National University, Yokohama, kanagawa (Japan); Nagao, T [Yokohama National University, Yokohama, kanagawa (Japan)

2016-06-15

Purpose: For the image guided radiation therapy (IGRT), the shadows caused by the construction of the treatment couch top adversely affect the visual evaluation. Therefore, we developed the new imaging filter in order to remove the shadows. The performance of the new filter was evaluated using the clinical images. Methods: The new filter was composed of the band-pass filter (BPF) weighted by the k factor and the low-pass filter (LPF). In the frequency region, the stop bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the BPF, and the pass bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the LPF. After adding the filter, the shadows from the carbon fiber grid table top (CFGTT, Varian) on the kV-image was removed. To check the filter effect, we compared the clinical images, which are thorax and thoracoabdominal region, with to without the filter. The subjective evaluation tests was performed by adapting a three-point scale (agree, neither agree nor disagree, disagree) about the 15 persons in the department of radiation oncology. Results: We succeeded in removing all shadows of CFGTT using the new filter. This filter is very useful shown by the results of the subjective evaluation having the 23/30 persons agreed to the filtered clinical images. Conclusion: We concluded that the proposed method was useful tool for the IGRT and the new filter leads to improvement of the accuracy of radiation therapy.

Tin-filter enhanced dual-energy-CT: image quality and accuracy of CT numbers in virtual noncontrast imaging.

Science.gov (United States)

Kaufmann, Sascha; Sauter, Alexander; Spira, Daniel; Gatidis, Sergios; Ketelsen, Dominik; Heuschmid, Martin; Claussen, Claus D; Thomas, Christoph

2013-05-01

To measure and compare the objective image quality of true noncontrast (TNC) images with virtual noncontrast (VNC) images acquired by tin-filter-enhanced, dual-source, dual-energy computed tomography (DECT) of upper abdomen. Sixty-three patients received unenhanced abdominal CT and enhanced abdominal DECT (100/140 kV with tin filter) in portal-venous phase. VNC images were calculated from the DECT datasets using commercially available software. The mean attenuation of relevant tissues and image quality were compared between the TNC and VNC images. Image quality was rated objectively by measuring image noise and the sharpness of object edges using custom-designed software. Measurements were compared using Student two-tailed t-test. Correlation coefficients for tissue attenuation measurements between TNC and VNC were calculated and the relative deviations were illustrated using Bland-Altman plots. Mean attenuation differences between TNC and VNC (HUTNC - HUVNC) image sets were as follows: right liver lobe -4.94 Hounsfield units (HU), left liver lobe -3.29 HU, vena cava -2.19 HU, spleen -7.46 HU, pancreas 1.29 HU, fat -11.14 HU, aorta 1.29 HU, bone marrow 36.83 HU (all P VNC and TNC series were observed for liver, vena portae, kidneys, pancreas, muscle and bone marrow (Pearson's correlation coefficient ≥0.75). Mean image noise was significantly higher in TNC images (P VNC and TNC images (P = .19). The Hounsfield units in VNC images closely resemble TNC images in the majority of the organs of the upper abdomen (kidneys, liver, pancreas). In spleen and fat, Hounsfield numbers in VNC images are tend to be higher than in TNC images. VNC images show a low image noise and satisfactory edge sharpness. Other criteria of image quality and the depiction of certain lesions need to be evaluated additionally. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

Avoiding the Use of Exhausted Drinking Water Filters: A Filter-Clock Based on Rusting Iron

Directory of Open Access Journals (Sweden)

Arnaud Igor Ndé-Tchoupé

2018-05-01

Full Text Available Efficient but affordable water treatment technologies are currently sought to solve the prevalent shortage of safe drinking water. Adsorption-based technologies are in the front-line of these efforts. Upon proper design, universally applied materials (e.g., activated carbons, bone chars, metal oxides are able to quantitatively remove inorganic and organic pollutants as well as pathogens from water. Each water filter has a defined removal capacity and must be replaced when this capacity is exhausted. Operational experience has shown that it may be difficult to convince some low-skilled users to buy new filters after a predicted service life. This communication describes the quest to develop a filter-clock to encourage all users to change their filters after the designed service life. A brief discussion on such a filter-clock based on rusting of metallic iron (Fe0 is presented. Integrating such filter-clocks in the design of water filters is regarded as essential for safeguarding public health.

Autonomous Navigation for Autonomous Underwater Vehicles Based on Information Filters and Active Sensing

Directory of Open Access Journals (Sweden)

Tianhong Yan

2011-11-01

Full Text Available This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM, and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China. Weak links in the information matrix in an extended information filter (EIF can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM. All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Autonomous navigation for autonomous underwater vehicles based on information filters and active sensing.

Science.gov (United States)

He, Bo; Zhang, Hongjin; Li, Chao; Zhang, Shujing; Liang, Yan; Yan, Tianhong

2011-01-01

This paper addresses an autonomous navigation method for the autonomous underwater vehicle (AUV) C-Ranger applying information-filter-based simultaneous localization and mapping (SLAM), and its sea trial experiments in Tuandao Bay (Shangdong Province, P.R. China). Weak links in the information matrix in an extended information filter (EIF) can be pruned to achieve an efficient approach-sparse EIF algorithm (SEIF-SLAM). All the basic update formulae can be implemented in constant time irrespective of the size of the map; hence the computational complexity is significantly reduced. The mechanical scanning imaging sonar is chosen as the active sensing device for the underwater vehicle, and a compensation method based on feedback of the AUV pose is presented to overcome distortion of the acoustic images due to the vehicle motion. In order to verify the feasibility of the navigation methods proposed for the C-Ranger, a sea trial was conducted in Tuandao Bay. Experimental results and analysis show that the proposed navigation approach based on SEIF-SLAM improves the accuracy of the navigation compared with conventional method; moreover the algorithm has a low computational cost when compared with EKF-SLAM.

Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

Science.gov (United States)

Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

2018-01-01

The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

Image Vector Quantization codec indexes filtering

Directory of Open Access Journals (Sweden)

Lakhdar Moulay Abdelmounaim

2012-01-01

Full Text Available Vector Quantisation (VQ is an efficient coding algorithm that has been widely used in the field of video and image coding, due to its fast decoding efficiency. However, the indexes of VQ are sometimes lost because of signal interference during the transmission. In this paper, we propose an efficient estimation method to conceal and recover the lost indexes on the decoder side, to avoid re-transmitting the whole image again. If the image or video has the limitation of a period of validity, re-transmitting the data wastes the resources of time and network bandwidth. Therefore, using the originally received correct data to estimate and recover the lost data is efficient in time-constrained situations, such as network conferencing or mobile transmissions. In nature images, the pixels are correlated with their neighbours and VQ partitions the image into sub-blocks and quantises them to the indexes that are transmitted; the correlation between adjacent indexes is very strong. There are two parts of the proposed method. The first is pre-processing and the second is an estimation process. In pre-processing, we modify the order of codevectors in the VQ codebook to increase the correlation among the neighbouring vectors. We then use a special filtering method in the estimation process. Using conventional VQ to compress the Lena image and transmit it without any loss of index can achieve a PSNR of 30.429 dB on the decoder. The simulation results demonstrate that our method can estimate the indexes to achieve PSNR values of 29.084 and 28.327 dB when the loss rate is 0.5% and 1%, respectively.

Photoacoustic imaging in scattering media by combining a correlation matrix filter with a time reversal operator.

Science.gov (United States)

Rui, Wei; Tao, Chao; Liu, Xiaojun

2017-09-18

Acoustic scattering medium is a fundamental challenge for photoacoustic imaging. In this study, we reveal the different coherent properties of the scattering photoacoustic waves and the direct photoacoustic waves in a matrix form. Direct waves show a particular coherence on the antidiagonals of the matrix, whereas scattering waves do not. Based on this property, a correlation matrix filter combining with a time reversal operator is proposed to preserve the direct waves and recover the image behind a scattering layer. Both numerical simulations and photoacoustic imaging experiments demonstrate that the proposed approach effectively increases the image contrast and decreases the background speckles in a scattering medium. This study might improve the quality of photoacoustic imaging in an acoustic scattering environment and extend its applications.

A family of quantization based piecewise linear filter networks

DEFF Research Database (Denmark)

Sørensen, John Aasted

1992-01-01

A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization...... of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization......). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting...

Regularized Fractional Power Parameters for Image Denoising Based on Convex Solution of Fractional Heat Equation

Directory of Open Access Journals (Sweden)

Hamid A. Jalab

2014-01-01

Full Text Available The interest in using fractional mask operators based on fractional calculus operators has grown for image denoising. Denoising is one of the most fundamental image restoration problems in computer vision and image processing. This paper proposes an image denoising algorithm based on convex solution of fractional heat equation with regularized fractional power parameters. The performances of the proposed algorithms were evaluated by computing the PSNR, using different types of images. Experiments according to visual perception and the peak signal to noise ratio values show that the improvements in the denoising process are competent with the standard Gaussian filter and Wiener filter.

Switching non-local vector median filter

Science.gov (United States)

Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

2016-04-01

This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.

Mapping accuracy via spectrally and structurally based filtering techniques: comparisons through visual observations

Science.gov (United States)

Chockalingam, Letchumanan

2005-01-01

The data of Gunung Ledang region of Malaysia acquired through LANDSAT are considered to map certain hydrogeolocial features. To map these significant features, image-processing tools such as contrast enhancement, edge detection techniques are employed. The advantages of these techniques over the other methods are evaluated from the point of their validity in properly isolating features of hydrogeolocial interest are discussed. As these techniques take the advantage of spectral aspects of the images, these techniques have several limitations to meet the objectives. To discuss these limitations, a morphological transformation, which generally considers the structural aspects rather than spectral aspects from the image, are applied to provide comparisons between the results derived from spectral based and the structural based filtering techniques.

[Testing method research for key performance indicator of imaging acousto-optic tunable filter (AOTF)].

Science.gov (United States)

Hu, Shan-Zhou; Chen, Fen-Fei; Zeng, Li-Bo; Wu, Qiong-Shui

2013-01-01

Imaging AOTF is an important optical filter component for new spectral imaging instruments developed in recent years. The principle of imaging AOTF component was demonstrated, and a set of testing methods for some key performances were studied, such as diffraction efficiency, wavelength shift with temperature, homogeneity in space for diffraction efficiency, imaging shift, etc.

OTRA-Based Multi-Function Inverse Filter Configuration

Directory of Open Access Journals (Sweden)

Abdhesh Kumar Singh

2017-01-01

Full Text Available A new OTRA-based multifunction Inverse filter configuration is presented which is capable of realizing low pass, high pass and band pass filters using only two OTRAs and five to six passive elements. To the best knowledge of the authors, any inverse filter configuration using OTRAs has not been reported in the literature earlier. The effect of the major parasitics of the OTRAs and their effect on the performance filter have been investigated and measured through simulation results and Monte-Carlo analysis. The workability of the proposed circuits has been confirmed by SPICE simulations using CMOS-based-OTRA realizable in 0.18 µm CMOS technology. The proposed circuits are the only ones which provide simultaneously the following features: use of reasonable number of active elements (only 2, realizability of all the three basic filter functions, employment of all virtually grounded resistors and capacitors and tunability of all filter parameters (except gain factor, H_0 for inverse high pass. The centre/cut-off frequency of the various filter circuits lying in the vicinity of 1 MHz have been found to be realizable, which has been verified through SPICE simulation results and have been found to be in good agreement with the theoretical results.

A center-median filtering method for detection of temporal variation in coronal images

Directory of Open Access Journals (Sweden)

Plowman Joseph

2016-01-01

Full Text Available Events in the solar corona are often widely separated in their timescales, which can allow them to be identified when they would otherwise be confused with emission from other sources in the corona. Methods for cleanly separating such events based on their timescales are thus desirable for research in the field. This paper develops a technique for identifying time-varying signals in solar coronal image sequences which is based on a per-pixel running median filter and an understanding of photon-counting statistics. Example applications to “EIT waves” (named after EIT, the EUV Imaging Telescope on the Solar and Heliospheric Observatory and small-scale dynamics are shown, both using 193 Å data from the Atmospheric Imaging Assembly (AIA on the Solar Dynamics Observatory. The technique is found to discriminate EIT waves more cleanly than the running and base difference techniques most commonly used. It is also demonstrated that there is more signal in the data than is commonly appreciated, finding that the waves can be traced to the edge of the AIA field of view when the data are rebinned to increase the signal-to-noise ratio.