Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

Science.gov (United States)

Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

2009-01-01

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

S. Jabari

2017-08-01

Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

Application of Sensor Fusion to Improve Uav Image Classification

Science.gov (United States)

Jabari, S.; Fathollahi, F.; Zhang, Y.

2017-08-01

Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

Science.gov (United States)

August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

2016-03-01

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Spectral Imaging by Upconversion

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Pedersen, Christian; Tidemand-Lichtenberg, Peter

2011-01-01

We present a method to obtain spectrally resolved images using upconversion. By this method an image is spectrally shifted from one spectral region to another wavelength. Since the process is spectrally sensitive it allows for a tailored spectral response. We believe this will allow standard...... silicon based cameras designed for visible/near infrared radiation to be used for spectral images in the mid infrared. This can lead to much lower costs for such imaging devices, and a better performance....

Snapshot spectral and polarimetric imaging; target identification with multispectral video

Science.gov (United States)

Bartlett, Brent D.; Rodriguez, Mikel D.

2013-05-01

As the number of pixels continue to grow in consumer and scientific imaging devices, it has become feasible to collect the incident light field. In this paper, an imaging device developed around light field imaging is used to collect multispectral and polarimetric imagery in a snapshot fashion. The sensor is described and a video data set is shown highlighting the advantage of snapshot spectral imaging. Several novel computer vision approaches are applied to the video cubes to perform scene characterization and target identification. It is shown how the addition of spectral and polarimetric data to the video stream allows for multi-target identification and tracking not possible with traditional RGB video collection.

Real-time detection of natural objects using AM-coded spectral matching imager

Science.gov (United States)

Kimachi, Akira

2005-01-01

This paper describes application of the amplitude-modulation (AM)-coded spectral matching imager (SMI) to real-time detection of natural objects such as human beings, animals, vegetables, or geological objects or phenomena, which are much more liable to change with time than artificial products while often exhibiting characteristic spectral functions associated with some specific activity states. The AM-SMI produces correlation between spectral functions of the object and a reference at each pixel of the correlation image sensor (CIS) in every frame, based on orthogonal amplitude modulation (AM) of each spectral channel and simultaneous demodulation of all channels on the CIS. This principle makes the SMI suitable to monitoring dynamic behavior of natural objects in real-time by looking at a particular spectral reflectance or transmittance function. A twelve-channel multispectral light source was developed with improved spatial uniformity of spectral irradiance compared to a previous one. Experimental results of spectral matching imaging of human skin and vegetable leaves are demonstrated, as well as a preliminary feasibility test of imaging a reflective object using a test color chart.

Imaging system design and image interpolation based on CMOS image sensor

Science.gov (United States)

Li, Yu-feng; Liang, Fei; Guo, Rui

2009-11-01

An image acquisition system is introduced, which consists of a color CMOS image sensor (OV9620), SRAM (CY62148), CPLD (EPM7128AE) and DSP (TMS320VC5509A). The CPLD implements the logic and timing control to the system. SRAM stores the image data, and DSP controls the image acquisition system through the SCCB (Omni Vision Serial Camera Control Bus). The timing sequence of the CMOS image sensor OV9620 is analyzed. The imaging part and the high speed image data memory unit are designed. The hardware and software design of the image acquisition and processing system is given. CMOS digital cameras use color filter arrays to sample different spectral components, such as red, green, and blue. At the location of each pixel only one color sample is taken, and the other colors must be interpolated from neighboring samples. We use the edge-oriented adaptive interpolation algorithm for the edge pixels and bilinear interpolation algorithm for the non-edge pixels to improve the visual quality of the interpolated images. This method can get high processing speed, decrease the computational complexity, and effectively preserve the image edges.

Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

Science.gov (United States)

Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

2018-06-01

Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

Evaluation of onboard hyperspectral-image compression techniques for a parallel push-broom sensor

Energy Technology Data Exchange (ETDEWEB)

Briles, S.

1996-04-01

A single hyperspectral imaging sensor can produce frames with spatially-continuous rows of differing, but adjacent, spectral wavelength. If the frame sample-rate of the sensor is such that subsequent hyperspectral frames are spatially shifted by one row, then the sensor can be thought of as a parallel (in wavelength) push-broom sensor. An examination of data compression techniques for such a sensor is presented. The compression techniques are intended to be implemented onboard a space-based platform and to have implementation speeds that match the date rate of the sensor. Data partitions examined extend from individually operating on a single hyperspectral frame to operating on a data cube comprising the two spatial axes and the spectral axis. Compression algorithms investigated utilize JPEG-based image compression, wavelet-based compression and differential pulse code modulation. Algorithm performance is quantitatively presented in terms of root-mean-squared error and root-mean-squared correlation coefficient error. Implementation issues are considered in algorithm development.

Piecewise spectrally band-pass for compressive coded aperture spectral imaging

International Nuclear Information System (INIS)

Qian Lu-Lu; Lü Qun-Bo; Huang Min; Xiang Li-Bin

2015-01-01

Coded aperture snapshot spectral imaging (CASSI) has been discussed in recent years. It has the remarkable advantages of high optical throughput, snapshot imaging, etc. The entire spatial-spectral data-cube can be reconstructed with just a single two-dimensional (2D) compressive sensing measurement. On the other hand, for less spectrally sparse scenes, the insufficiency of sparse sampling and aliasing in spatial-spectral images reduce the accuracy of reconstructed three-dimensional (3D) spectral cube. To solve this problem, this paper extends the improved CASSI. A band-pass filter array is mounted on the coded mask, and then the first image plane is divided into some continuous spectral sub-band areas. The entire 3D spectral cube could be captured by the relative movement between the object and the instrument. The principle analysis and imaging simulation are presented. Compared with peak signal-to-noise ratio (PSNR) and the information entropy of the reconstructed images at different numbers of spectral sub-band areas, the reconstructed 3D spectral cube reveals an observable improvement in the reconstruction fidelity, with an increase in the number of the sub-bands and a simultaneous decrease in the number of spectral channels of each sub-band. (paper)

[Analysis of sensitive spectral bands for burning status detection using hyper-spectral images of Tiangong-01].

Science.gov (United States)

Qin, Xian-Lin; Zhu, Xi; Yang, Fei; Zhao, Kai-Rui; Pang, Yong; Li, Zeng-Yuan; Li, Xu-Zhi; Zhang, Jiu-Xing

2013-07-01

To obtain the sensitive spectral bands for detection of information on 4 kinds of burning status, i. e. flaming, smoldering, smoke, and fire scar, with satellite data, analysis was conducted to identify suitable satellite spectral bands for detection of information on these 4 kinds of burning status by using hyper-spectrum images of Tiangong-01 (TG-01) and employing a method combining statistics and spectral analysis. The results show that: in the hyper-spectral images of TG-01, the spectral bands differ obviously for detection of these 4 kinds of burning status; in all hyper-spectral short-wave infrared channels, the reflectance of flaming is higher than that of all other 3 kinds of burning status, and the reflectance of smoke is the lowest; the reflectance of smoke is higher than that of all other 3 kinds of burning status in the channels corresponding to hyper-spectral visible near-infrared and panchromatic sensors. For spectral band selection, more suitable spectral bands for flaming detection are 1 000.0-1 956.0 and 2 020.0-2 400.0 nm; the suitable spectral bands for identifying smoldering are 930.0-1 000.0 and 1 084.0-2 400.0 nm; the suitable spectral bands for smoke detection is in 400.0-920.0 nm; for fire scar detection, it is suitable to select bands with central wavelengths of 900.0-930.0 and 1 300.0-2 400.0 nm, and then to combine them to construct a detection model.

CMOS Imaging Sensor Technology for Aerial Mapping Cameras

Science.gov (United States)

Neumann, Klaus; Welzenbach, Martin; Timm, Martin

2016-06-01

In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera. In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs. Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.

Commercial CMOS image sensors as X-ray imagers and particle beam monitors

International Nuclear Information System (INIS)

Castoldi, A.; Guazzoni, C.; Maffessanti, S.; Montemurro, G.V.; Carraresi, L.

2015-01-01

CMOS image sensors are widely used in several applications such as mobile handsets webcams and digital cameras among others. Furthermore they are available across a wide range of resolutions with excellent spectral and chromatic responses. In order to fulfill the need of cheap systems as beam monitors and high resolution image sensors for scientific applications we exploited the possibility of using commercial CMOS image sensors as X-rays and proton detectors. Two different sensors have been mounted and tested. An Aptina MT9v034, featuring 752 × 480 pixels, 6μm × 6μm pixel size has been mounted and successfully tested as bi-dimensional beam profile monitor, able to take pictures of the incoming proton bunches at the DeFEL beamline (1–6 MeV pulsed proton beam) of the LaBeC of INFN in Florence. The naked sensor is able to successfully detect the interactions of the single protons. The sensor point-spread-function (PSF) has been qualified with 1MeV protons and is equal to one pixel (6 mm) r.m.s. in both directions. A second sensor MT9M032, featuring 1472 × 1096 pixels, 2.2 × 2.2 μm pixel size has been mounted on a dedicated board as high-resolution imager to be used in X-ray imaging experiments with table-top generators. In order to ease and simplify the data transfer and the image acquisition the system is controlled by a dedicated micro-processor board (DM3730 1GHz SoC ARM Cortex-A8) on which a modified LINUX kernel has been implemented. The paper presents the architecture of the sensor systems and the results of the experimental measurements

Accuracy in mineral identification: image spectral and spatial resolutions and mineral spectral properties

Directory of Open Access Journals (Sweden)

L. Pompilio

2006-06-01

Full Text Available Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed.

Thermal infrared panoramic imaging sensor

Science.gov (United States)

Gutin, Mikhail; Tsui, Eddy K.; Gutin, Olga; Wang, Xu-Ming; Gutin, Alexey

2006-05-01

Panoramic cameras offer true real-time, 360-degree coverage of the surrounding area, valuable for a variety of defense and security applications, including force protection, asset protection, asset control, security including port security, perimeter security, video surveillance, border control, airport security, coastguard operations, search and rescue, intrusion detection, and many others. Automatic detection, location, and tracking of targets outside protected area ensures maximum protection and at the same time reduces the workload on personnel, increases reliability and confidence of target detection, and enables both man-in-the-loop and fully automated system operation. Thermal imaging provides the benefits of all-weather, 24-hour day/night operation with no downtime. In addition, thermal signatures of different target types facilitate better classification, beyond the limits set by camera's spatial resolution. The useful range of catadioptric panoramic cameras is affected by their limited resolution. In many existing systems the resolution is optics-limited. Reflectors customarily used in catadioptric imagers introduce aberrations that may become significant at large camera apertures, such as required in low-light and thermal imaging. Advantages of panoramic imagers with high image resolution include increased area coverage with fewer cameras, instantaneous full horizon detection, location and tracking of multiple targets simultaneously, extended range, and others. The Automatic Panoramic Thermal Integrated Sensor (APTIS), being jointly developed by Applied Science Innovative, Inc. (ASI) and the Armament Research, Development and Engineering Center (ARDEC) combines the strengths of improved, high-resolution panoramic optics with thermal imaging in the 8 - 14 micron spectral range, leveraged by intelligent video processing for automated detection, location, and tracking of moving targets. The work in progress supports the Future Combat Systems (FCS) and the

Imaging moving objects from multiply scattered waves and multiple sensors

International Nuclear Information System (INIS)

Miranda, Analee; Cheney, Margaret

2013-01-01

In this paper, we develop a linearized imaging theory that combines the spatial, temporal and spectral components of multiply scattered waves as they scatter from moving objects. In particular, we consider the case of multiple fixed sensors transmitting and receiving information from multiply scattered waves. We use a priori information about the multipath background. We use a simple model for multiple scattering, namely scattering from a fixed, perfectly reflecting (mirror) plane. We base our image reconstruction and velocity estimation technique on a modification of a filtered backprojection method that produces a phase-space image. We plot examples of point-spread functions for different geometries and waveforms, and from these plots, we estimate the resolution in space and velocity. Through this analysis, we are able to identify how the imaging system depends on parameters such as bandwidth and number of sensors. We ultimately show that enhanced phase-space resolution for a distribution of moving and stationary targets in a multipath environment may be achieved using multiple sensors. (paper)

Implications of sensor design for coral reef detection: Upscaling ground hyperspectral imagery in spatial and spectral scales

Science.gov (United States)

Caras, Tamir; Hedley, John; Karnieli, Arnon

2017-12-01

Remote sensing offers a potential tool for large scale environmental surveying and monitoring. However, remote observations of coral reefs are difficult especially due to the spatial and spectral complexity of the target compared to sensor specifications as well as the environmental implications of the water medium above. The development of sensors is driven by technological advances and the desired products. Currently, spaceborne systems are technologically limited to a choice between high spectral resolution and high spatial resolution, but not both. The current study explores the dilemma of whether future sensor design for marine monitoring should prioritise on improving their spatial or spectral resolution. To address this question, a spatially and spectrally resampled ground-level hyperspectral image was used to test two classification elements: (1) how the tradeoff between spatial and spectral resolutions affects classification; and (2) how a noise reduction by majority filter might improve classification accuracy. The studied reef, in the Gulf of Aqaba (Eilat), Israel, is heterogeneous and complex so the local substrate patches are generally finer than currently available imagery. Therefore, the tested spatial resolution was broadly divided into four scale categories from five millimeters to one meter. Spectral resolution resampling aimed to mimic currently available and forthcoming spaceborne sensors such as (1) Environmental Mapping and Analysis Program (EnMAP) that is characterized by 25 bands of 6.5 nm width; (2) VENμS with 12 narrow bands; and (3) the WorldView series with broadband multispectral resolution. Results suggest that spatial resolution should generally be prioritized for coral reef classification because the finer spatial scale tested (pixel size mind, while the focus in this study was on the technologically limited spaceborne design, aerial sensors may presently provide an opportunity to implement the suggested setup.

[Cotton identification and extraction using near infrared sensor and object-oriented spectral segmentation technique].

Science.gov (United States)

Deng, Jin-Song; Shi, Yuan-Yuan; Chen, Li-Su; Wang, Ke; Zhu, Jin-Xia

2009-07-01

The real-time, effective and reliable method of identifying crop is the foundation of scientific management for crop in the precision agriculture. It is also one of the key techniques for the precision agriculture. However, this expectation cannot be fulfilled by the traditional pixel-based information extraction method with respect to complicated image processing and accurate objective identification. In the present study, visible-near infrared image of cotton was acquired using high-resolution sensor. Object-oriented segmentation technique was performed on the image to produce image objects and spatial/spectral features of cotton. Afterwards, nearest neighbor classifier integrated the spectral, shape and topologic information of image objects to precisely identify cotton according to various features. Finally, 300 random samples and an error matrix were applied to undertake the accuracy assessment of identification. Although errors and confusion exist, this method shows satisfying results with an overall accuracy of 96.33% and a KAPPA coefficient of 0.926 7, which can meet the demand of automatic management and decision-making in precision agriculture.

Rayleigh imaging in spectral mammography

Science.gov (United States)

Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

2016-03-01

Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

Rayleigh radiance computations for satellite remote sensing: accounting for the effect of sensor spectral response function.

Science.gov (United States)

Wang, Menghua

2016-05-30

To understand and assess the effect of the sensor spectral response function (SRF) on the accuracy of the top of the atmosphere (TOA) Rayleigh-scattering radiance computation, new TOA Rayleigh radiance lookup tables (LUTs) over global oceans and inland waters have been generated. The new Rayleigh LUTs include spectral coverage of 335-2555 nm, all possible solar-sensor geometries, and surface wind speeds of 0-30 m/s. Using the new Rayleigh LUTs, the sensor SRF effect on the accuracy of the TOA Rayleigh radiance computation has been evaluated for spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS)-1, showing some important uncertainties for VIIRS-SNPP particularly for large solar- and/or sensor-zenith angles as well as for large Rayleigh optical thicknesses (i.e., short wavelengths) and bands with broad spectral bandwidths. To accurately account for the sensor SRF effect, a new correction algorithm has been developed for VIIRS spectral bands, which improves the TOA Rayleigh radiance accuracy to ~0.01% even for the large solar-zenith angles of 70°-80°, compared with the error of ~0.7% without applying the correction for the VIIRS-SNPP 410 nm band. The same methodology that accounts for the sensor SRF effect on the Rayleigh radiance computation can be used for other satellite sensors. In addition, with the new Rayleigh LUTs, the effect of surface atmospheric pressure variation on the TOA Rayleigh radiance computation can be calculated precisely, and no specific atmospheric pressure correction algorithm is needed. There are some other important applications and advantages to using the new Rayleigh LUTs for satellite remote sensing, including an efficient and accurate TOA Rayleigh radiance computation for hyperspectral satellite remote sensing, detector-based TOA Rayleigh radiance computation, Rayleigh radiance calculations for high altitude

Precise Multi-Spectral Dermatological Imaging

DEFF Research Database (Denmark)

Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

2004-01-01

In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral dermatological images is proposed. The system is made up of an integrating sphere, light emitting diodes and a generic monochromatic camera. The system can collect up to 10 different spectral bands....... These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

The assessment of multi-sensor image fusion using wavelet transforms for mapping the Brazilian Savanna

NARCIS (Netherlands)

Weimar Acerbi, F.; Clevers, J.G.P.W.; Schaepman, M.E.

2006-01-01

Multi-sensor image fusion using the wavelet approach provides a conceptual framework for the improvement of the spatial resolution with minimal distortion of the spectral content of the source image. This paper assesses whether images with a large ratio of spatial resolution can be fused, and

Photon-counting image sensors

CERN Document Server

Teranishi, Nobukazu; Theuwissen, Albert; Stoppa, David; Charbon, Edoardo

2017-01-01

The field of photon-counting image sensors is advancing rapidly with the development of various solid-state image sensor technologies including single photon avalanche detectors (SPADs) and deep-sub-electron read noise CMOS image sensor pixels. This foundational platform technology will enable opportunities for new imaging modalities and instrumentation for science and industry, as well as new consumer applications. Papers discussing various photon-counting image sensor technologies and selected new applications are presented in this all-invited Special Issue.

SPECTRAL SMILE CORRECTION IN CRISM HYPERSPECTRAL IMAGES

Science.gov (United States)

Ceamanos, X.; Doute, S.

2009-12-01

The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) is affected by a common artifact in "push-broom" sensors, the so-called "spectral smile". As a consequence, both central wavelength and spectral width of the spectral response vary along the across-track dimension, thus giving rise to a shifting and smoothing of spectra (see Fig. 1 (left)). In fact, both effects are greater for spectra on the edges, while they are minimum for data acquired by central detectors, the so-called "sweet spot". The prior artifacts become particularly critical for Martian observations which contain steep spectra such as CO2 ice-rich polar images. Fig. 1 (right) shows the horizontal brightness gradient which appears in every band corresponding to a steep portion of spectra. The correction of CRISM spectral smile is addressed using a two-step method which aims at modifying data sensibly in order to mimic the optimal CRISM response. First, all spectra, which are previously interpolated by cubic splines, are resampled to the "sweet spot" wavelengths in order to overcome the spectra shift. Secondly, the non-uniform spectral width is overcome by mimicking an increase of spectral resolution thanks to a spectral sharpening. In order to minimize noise, only bands particularly suffering from smile are selected. First, bands corresponding to the outliers of the Minimum Noise Transformation (MNF) eigenvector, which corresponds to the MNF band related to smile (MNF-smile), are selected. Then, a spectral neighborhood Θi, which takes into account the local spectral convexity or concavity, is defined for every selected band in order to maximize spectral shape preservation. The proposed sharpening technique takes into account both the instrument parameters and the observed spectra. First, every reflectance value belonging to a Θi is reevaluated by a sharpening which depends on a ratio of the spectral width of the current detector and the "sweet spot" one. Then, the optimal degree of

System overview and applications of a panoramic imaging perimeter sensor

International Nuclear Information System (INIS)

Pritchard, D.A.

1995-01-01

This paper presents an overview of the design and potential applications of a 360-degree scanning, multi-spectral intrusion detection sensor. This moderate-resolution, true panoramic imaging sensor is intended for exterior use at ranges from 50 to 1,500 meters. This Advanced Exterior Sensor (AES) simultaneously uses three sensing technologies (infrared, visible, and radar) along with advanced data processing methods to provide low false-alarm intrusion detection, tracking, and immediate visual assessment. The images from the infrared and visible detector sets and the radar range data are updated as the sensors rotate once per second. The radar provides range data with one-meter resolution. This sensor has been designed for easy use and rapid deployment to cover wide areas beyond or in place of typical perimeters, and tactical applications around fixed or temporary high-value assets. AES prototypes are in development. Applications discussed in this paper include replacements, augmentations, or new installations at fixed sites where topological features, atmospheric conditions, environmental restrictions, ecological regulations, and archaeological features limit the use of conventional security components and systems

Semiconductor Laser Multi-Spectral Sensing and Imaging

Directory of Open Access Journals (Sweden)

Han Q. Le

2010-01-01

Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Semiconductor laser multi-spectral sensing and imaging.

Science.gov (United States)

Le, Han Q; Wang, Yang

2010-01-01

Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO). These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

Science.gov (United States)

Rendon Santillan, Jojene; Makinano-Santillan, Meriam

2018-04-01

We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

Spectral response analysis of PVDF capacitive sensors

Science.gov (United States)

Reyes-Ramírez, B.; García-Segundo, C.; García-Valenzuela, A.

2013-06-01

We investigate the spectral response to ultrasound waves in water of low-noise capacitive sensors based on PVDF polymer piezoelectric films. First, we analyze theoretically the mechanical-to-electrical transduction as a function of the frequency of ultrasonic signals and derive an analytic expression of the sensor's transfer function. Then we present experimental results of the frequency response of a home-made PDVF in water to test signals from 1 to 20 MHz induced by a commercial hydrophone powered by a signal generator and compare with our theoretical model.

Comparison of the Spectral Properties of Pansharpened Images Generated from AVNIR-2 and Prism Onboard Alos

Science.gov (United States)

Matsuoka, M.

2012-07-01

A considerable number of methods for pansharpening remote-sensing images have been developed to generate higher spatial resolution multispectral images by the fusion of lower resolution multispectral images and higher resolution panchromatic images. Because pansharpening alters the spectral properties of multispectral images, method selection is one of the key factors influencing the accuracy of subsequent analyses such as land-cover classification or change detection. In this study, seven pixel-based pansharpening methods (additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-hue-saturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio) were compared using AVNIR-2 and PRISM onboard ALOS from the viewpoint of the preservation of spectral properties of AVNIR-2. A visual comparison was made between pansharpened images generated from spatially degraded AVNIR-2 and original images over urban, agricultural, and forest areas. The similarity of the images was evaluated in terms of the image contrast, the color distinction, and the brightness of the ground objects. In the quantitative assessment, three kinds of statistical indices, correlation coefficient, ERGAS, and Q index, were calculated by band and land-cover type. These scores were relatively superior in bands 2 and 3 compared with the other two bands, especially over urban and agricultural areas. Band 4 showed a strong dependency on the land-cover type. This was attributable to the differences in the observing spectral wavelengths of the sensors and local scene variances.

ANALYSIS OF IN-SITU SPECTRAL REFLECTANCE OF SAGO AND OTHER PALMS: IMPLICATIONS FOR THEIR DETECTION IN OPTICAL SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

J. R. Santillan

2018-04-01

Full Text Available We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345–1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2. Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

Assessment of damage in composite laminates through dynamic, full-spectral interrogation of fiber Bragg grating sensors

International Nuclear Information System (INIS)

Propst, A; Peters, K; Zikry, M A; Schultz, S; Kunzler, W; Zhu, Z; Wirthlin, M; Selfridge, R

2010-01-01

In this study, we demonstrate the full-spectral interrogation of a fiber Bragg grating (FBG) sensor at 535 Hz. The sensor is embedded in a woven, graphite fiber–epoxy composite laminate subjected to multiple low-velocity impacts. The measurement of unique, time dependent spectral features from the FBG sensor permits classification of the laminate lifetime into five regimes. These damage regimes compare well with previous analysis of the same material system using combined global and local FBG sensor information. Observed transient spectral features include peak splitting, wide spectral broadening and a strong single peak at the end of the impact event. Such features could not be measured through peak wavelength interrogation of the FBG sensor. Cross-correlation of the measured spectra with the original embedded FBG spectrum permitted rapid visualization of average strains and the presence of transverse compressive strain on the optical fiber, but smeared out the details of the spectral profile

Color quality improvement of reconstructed images in color digital holography using speckle method and spectral estimation

Science.gov (United States)

Funamizu, Hideki; Onodera, Yusei; Aizu, Yoshihisa

2018-05-01

In this study, we report color quality improvement of reconstructed images in color digital holography using the speckle method and the spectral estimation. In this technique, an object is illuminated by a speckle field and then an object wave is produced, while a plane wave is used as a reference wave. For three wavelengths, the interference patterns of two coherent waves are recorded as digital holograms on an image sensor. Speckle fields are changed by moving a ground glass plate in an in-plane direction, and a number of holograms are acquired to average the reconstructed images. After the averaging process of images reconstructed from multiple holograms, we use the Wiener estimation method for obtaining spectral transmittance curves in reconstructed images. The color reproducibility in this method is demonstrated and evaluated using a Macbeth color chart film and staining cells of onion.

Focus on image sensors

NARCIS (Netherlands)

Jos Gunsing; Daniël Telgen; Johan van Althuis; Jaap van de Loosdrecht; Mark Stappers; Peter Klijn

2013-01-01

Robots need sensors to operate properly. Using a single image sensor, various aspects of a robot operating in its environment can be measured or monitored. Over the past few years, image sensors have improved a lot: frame rate and resolution have increased, while prices have fallen. As a result,

Hyperspectral small animal fluorescence imaging: spectral selection imaging

Science.gov (United States)

Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul

2008-02-01

Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

Operational calibration and validation of landsat data continuity mission (LDCM) sensors using the image assessment system (IAS)

Science.gov (United States)

Micijevic, Esad; Morfitt, Ron

2010-01-01

Systematic characterization and calibration of the Landsat sensors and the assessment of image data quality are performed using the Image Assessment System (IAS). The IAS was first introduced as an element of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) ground segment and recently extended to Landsat 4 (L4) and 5 (L5) Thematic Mappers (TM) and Multispectral Sensors (MSS) on-board the Landsat 1-5 satellites. In preparation for the Landsat Data Continuity Mission (LDCM), the IAS was developed for the Earth Observer 1 (EO-1) Advanced Land Imager (ALI) with a capability to assess pushbroom sensors. This paper describes the LDCM version of the IAS and how it relates to unique calibration and validation attributes of its on-board imaging sensors. The LDCM IAS system will have to handle a significantly larger number of detectors and the associated database than the previous IAS versions. An additional challenge is that the LDCM IAS must handle data from two sensors, as the LDCM products will combine the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) spectral bands.

Large area CMOS image sensors

International Nuclear Information System (INIS)

Turchetta, R; Guerrini, N; Sedgwick, I

2011-01-01

CMOS image sensors, also known as CMOS Active Pixel Sensors (APS) or Monolithic Active Pixel Sensors (MAPS), are today the dominant imaging devices. They are omnipresent in our daily life, as image sensors in cellular phones, web cams, digital cameras, ... In these applications, the pixels can be very small, in the micron range, and the sensors themselves tend to be limited in size. However, many scientific applications, like particle or X-ray detection, require large format, often with large pixels, as well as other specific performance, like low noise, radiation hardness or very fast readout. The sensors are also required to be sensitive to a broad spectrum of radiation: photons from the silicon cut-off in the IR down to UV and X- and gamma-rays through the visible spectrum as well as charged particles. This requirement calls for modifications to the substrate to be introduced to provide optimized sensitivity. This paper will review existing CMOS image sensors, whose size can be as large as a single CMOS wafer, and analyse the technical requirements and specific challenges of large format CMOS image sensors.

Spectral Sharpening of Color Sensors: Diagonal Color Constancy and Beyond

OpenAIRE

Vazquez-Corral, Javier; Bertalmío, Marcelo

2014-01-01

It has now been 20 years since the seminal work by Finlayson et al. on the use/nof spectral sharpening of sensors to achieve diagonal color constancy. Spectral sharpening is/nstill used today by numerous researchers for different goals unrelated to the original goal/nof diagonal color constancy e.g., multispectral processing, shadow removal, location of/nunique hues. This paper reviews the idea of spectral sharpening through the lens of what/nis known today in color constancy, describes the d...

Spectral Imaging of Portolan Charts

Science.gov (United States)

France, Fenella G.; Wilson, Meghan A.; Ghez, Anita

2018-05-01

Spectral imaging of Portolan Charts, early nautical charts, provided extensive new information about their construction and creation. The origins of the portolan chart style have been a continual source of perplexity to numerous generations of cartographic historians. The spectral imaging system utilized incorporates a 50 megapixel mono-chrome camera with light emitting diode (LED) illumination panels that cover the range from 365 nm to 1050 nm to capture visible and non-visible information. There is little known about how portolan charts evolved, and what influenced their creation. These early nautical charts began as working navigational tools of medieval mariners, initially made in the 1300s in Italy, Portugal and Spain; however the origin and development of the portolan chart remained shrouded in mystery. Questions about these early navigational charts included whether colorants were commensurate with the time period and geographical location, and if different, did that give insight into trade routes, or possible later additions to the charts? For example; spectral data showed the red pigment on both the 1320 portolan chart and the 1565 Galapagos Islands matched vermillion, an opaque red pigment used since antiquity. The construction of these charts was also of great interest. Spectral imaging with a range of illumination modes revealed the presence of a "hidden circle" often referred to in relation to their construction. This paper will present in-depth analysis of how spectral imaging of the Portolans revealed similarities and differences, new hidden information and shed new light on construction and composition.

Fluorescence spectral imaging as a tool for locating uranium deposited on surfaces - 16089

International Nuclear Information System (INIS)

Monts, David L.; Wang, Guangjun; Su, Yi; Jang, Ping-Rey; Waggoner, Charles A.

2009-01-01

In the environment, metallic uranium readily oxidizes to form uranium compounds that contain the uranyl (UO 2 +2 ) moiety. For more than a hundred and fifty years, it has been known that when illuminated with ultraviolet (UV) light, uranyl compounds exhibit characteristic fluorescence in the visible region (450-650 nm). We report our efforts to develop a transportable, quantitative Fluorescence Spectral Imaging (FSI) system as a tool for locating and quantifying uranyl compounds dispersed in soils and on other surfaces. A project is underway to develop a set of sensors to locate expended depleted uranium (DU) rounds and to process soil and debris to recover the material from domestic firing ranges. The FSI system can also be utilized to monitor excavation of DU munitions and separation of uranyl compounds from soils. FSI images are acquired by illuminating a surface with a UV light and using a narrow band pass filter on a camera, recording an image of the resulting fluorescence. The FSI image provides both spatial and spectral information. The FSI system is described and its performance characterized using field samples. (authors)

A multimodal image sensor system for identifying water stress in grapevines

Science.gov (United States)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation.

Science.gov (United States)

Urban, Philipp; Rosen, Mitchell R; Berns, Roy S

2009-08-01

Reconstruction of spectral images from camera responses is investigated using an edge preserving spatio-spectral Wiener estimation. A Wiener denoising filter and a spectral reconstruction Wiener filter are combined into a single spatio-spectral filter using local propagation of the noise covariance matrix. To preserve edges the local mean and covariance matrix of camera responses is estimated by bilateral weighting of neighboring pixels. We derive the edge-preserving spatio-spectral Wiener estimation by means of Bayesian inference and show that it fades into the standard Wiener reflectance estimation shifted by a constant reflectance in case of vanishing noise. Simulation experiments conducted on a six-channel camera system and on multispectral test images show the performance of the filter, especially for edge regions. A test implementation of the method is provided as a MATLAB script at the first author's website.

BIOME: An Ecosystem Remote Sensor Based on Imaging Interferometry

Science.gov (United States)

Peterson, David L.; Hammer, Philip; Smith, William H.; Lawless, James G. (Technical Monitor)

1994-01-01

Until recent times, optical remote sensing of ecosystem properties from space has been limited to broad band multispectral scanners such as Landsat and AVHRR. While these sensor data can be used to derive important information about ecosystem parameters, they are very limited for measuring key biogeochemical cycling parameters such as the chemical content of plant canopies. Such parameters, for example the lignin and nitrogen contents, are potentially amenable to measurements by very high spectral resolution instruments using a spectroscopic approach. Airborne sensors based on grating imaging spectrometers gave the first promise of such potential but the recent decision not to deploy the space version has left the community without many alternatives. In the past few years, advancements in high performance deep well digital sensor arrays coupled with a patented design for a two-beam interferometer has produced an entirely new design for acquiring imaging spectroscopic data at the signal to noise levels necessary for quantitatively estimating chemical composition (1000:1 at 2 microns). This design has been assembled as a laboratory instrument and the principles demonstrated for acquiring remote scenes. An airborne instrument is in production and spaceborne sensors being proposed. The instrument is extremely promising because of its low cost, lower power requirements, very low weight, simplicity (no moving parts), and high performance. For these reasons, we have called it the first instrument optimized for ecosystem studies as part of a Biological Imaging and Observation Mission to Earth (BIOME).

Calibrating spectral images using penalized likelihood

NARCIS (Netherlands)

Heijden, van der G.W.A.M.; Glasbey, C.

2003-01-01

A new method is presented for automatic correction of distortions and for spectral calibration (which band corresponds to which wavelength) of spectral images recorded by means of a spectrograph. The method consists of recording a bar-like pattern with an illumination source with spectral bands

Automatic parquet block sorting using real-time spectral classification

Science.gov (United States)

Astrom, Anders; Astrand, Erik; Johansson, Magnus

1999-03-01

This paper presents a real-time spectral classification system based on the PGP spectrograph and a smart image sensor. The PGP is a spectrograph which extracts the spectral information from a scene and projects the information on an image sensor, which is a method often referred to as Imaging Spectroscopy. The classification is based on linear models and categorizes a number of pixels along a line. Previous systems adopting this method have used standard sensors, which often resulted in poor performance. The new system, however, is based on a patented near-sensor classification method, which exploits analogue features on the smart image sensor. The method reduces the enormous amount of data to be processed at an early stage, thus making true real-time spectral classification possible. The system has been evaluated on hardwood parquet boards showing very good results. The color defects considered in the experiments were blue stain, white sapwood, yellow decay and red decay. In addition to these four defect classes, a reference class was used to indicate correct surface color. The system calculates a statistical measure for each parquet block, giving the pixel defect percentage. The patented method makes it possible to run at very high speeds with a high spectral discrimination ability. Using a powerful illuminator, the system can run with a line frequency exceeding 2000 line/s. This opens up the possibility to maintain high production speed and still measure with good resolution.

High frame rate multi-resonance imaging refractometry with distributed feedback dye laser sensor

DEFF Research Database (Denmark)

Vannahme, Christoph; Dufva, Martin; Kristensen, Anders

2015-01-01

imaging refractometry without moving parts is presented. DFB dye lasers are low-cost and highly sensitive refractive index sensors. The unique multi-wavelength DFB laser structure presented here comprises several areas with different grating periods. Imaging in two dimensions of space is enabled...... by analyzing laser light from all areas in parallel with an imaging spectrometer. With this multi-resonance imaging refractometry method, the spatial position in one direction is identified from the horizontal, i.e., spectral position of the multiple laser lines which is obtained from the spectrometer charged...

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

Science.gov (United States)

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The

Optimization of compressive 4D-spatio-spectral snapshot imaging

Science.gov (United States)

Zhao, Xia; Feng, Weiyi; Lin, Lihua; Su, Wu; Xu, Guoqing

2017-10-01

In this paper, a modified 3D computational reconstruction method in the compressive 4D-spectro-volumetric snapshot imaging system is proposed for better sensing spectral information of 3D objects. In the design of the imaging system, a microlens array (MLA) is used to obtain a set of multi-view elemental images (EIs) of the 3D scenes. Then, these elemental images with one dimensional spectral information and different perspectives are captured by the coded aperture snapshot spectral imager (CASSI) which can sense the spectral data cube onto a compressive 2D measurement image. Finally, the depth images of 3D objects at arbitrary depths, like a focal stack, are computed by inversely mapping the elemental images according to geometrical optics. With the spectral estimation algorithm, the spectral information of 3D objects is also reconstructed. Using a shifted translation matrix, the contrast of the reconstruction result is further enhanced. Numerical simulation results verify the performance of the proposed method. The system can obtain both 3D spatial information and spectral data on 3D objects using only one single snapshot, which is valuable in the agricultural harvesting robots and other 3D dynamic scenes.

An Approach for Unsupervised Change Detection in Multitemporal VHR Images Acquired by Different Multispectral Sensors

Directory of Open Access Journals (Sweden)

Yady Tatiana Solano-Correa

2018-03-01

Full Text Available This paper proposes an approach for the detection of changes in multitemporal Very High Resolution (VHR optical images acquired by different multispectral sensors. The proposed approach, which is inspired by a recent framework developed to support the design of change-detection systems for single-sensor VHR remote sensing images, addresses and integrates in the general approach a strategy to effectively deal with multisensor information, i.e., to perform change detection between VHR images acquired by different multispectral sensors on two dates. This is achieved by the definition of procedures for the homogenization of radiometric, spectral and geometric image properties. These procedures map images into a common feature space where the information acquired by different multispectral sensors becomes comparable across time. Although the approach is general, here we optimize it for the detection of changes in vegetation and urban areas by employing features based on linear transformations (Tasseled Caps and Orthogonal Equations, which are shown to be effective for representing the multisensor information in a homogeneous physical way irrespectively of the considered sensor. Experiments on multitemporal images acquired by different VHR satellite systems (i.e., QuickBird, WorldView-2 and GeoEye-1 confirm the effectiveness of the proposed approach.

Visual Image Sensor Organ Replacement

Science.gov (United States)

Maluf, David A.

2014-01-01

This innovation is a system that augments human vision through a technique called "Sensing Super-position" using a Visual Instrument Sensory Organ Replacement (VISOR) device. The VISOR device translates visual and other sensors (i.e., thermal) into sounds to enable very difficult sensing tasks. Three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. Because the human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns, the translation of images into sounds reduces the risk of accidentally filtering out important clues. The VISOR device was developed to augment the current state-of-the-art head-mounted (helmet) display systems. It provides the ability to sense beyond the human visible light range, to increase human sensing resolution, to use wider angle visual perception, and to improve the ability to sense distances. It also allows compensation for movement by the human or changes in the scene being viewed.

Remote spectral measurements of the blood volume pulse with applications for imaging photoplethysmography

Science.gov (United States)

Blackford, Ethan B.; Estepp, Justin R.; McDuff, Daniel J.

2018-02-01

Imaging photoplethysmography uses camera image sensors to measure variations in light absorption related to the delivery of the blood volume pulse to peripheral tissues. The characteristics of the measured BVP waveform depends on the spectral absorption of various tissue components including melanin, hemoglobin, water, and yellow pigments. Signal quality and artifact rejection can be enhanced by taking into account the spectral properties of the BVP waveform and surrounding tissue. The current literature regarding the spectral relationships of remote PPG is limited. To supplement this fundamental data, we present an analysis of remotely-measured, visible and near-infrared spectroscopy to better understand the spectral signature of remotely measured BVP signals. To do so, spectra were measured from the right cheek of 25, stationary participants whose heads were stabilized by a chinrest. A collimating lens was used to collect reflected light from a region of 3 cm in diameter. The spectrometer provided 3 nm resolution measurements from 500-1000 nm. Measurements were acquired at a rate of 50 complete spectra per second for a period of five minutes. Reference physiology, including electrocardiography was simultaneously and synchronously acquired. The spectral data were analyzed to determine the relationship between light wavelength and the resulting remote-BVP signal-to-noise ratio and to identify those bands best suited for pulse rate measurement. To our knowledge this is the most comprehensive dataset of remotely-measured spectral iPPG data. In due course, we plan to release this dataset for research purposes.

Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

Science.gov (United States)

Awumah, Anna; Mahanti, Prasun; Robinson, Mark

2016-10-01

Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

Radiometric inter-sensor cross-calibration uncertainty using a traceable high accuracy reference hyperspectral imager

Science.gov (United States)

Gorroño, Javier; Banks, Andrew C.; Fox, Nigel P.; Underwood, Craig

2017-08-01

Optical earth observation (EO) satellite sensors generally suffer from drifts and biases relative to their pre-launch calibration, caused by launch and/or time in the space environment. This places a severe limitation on the fundamental reliability and accuracy that can be assigned to satellite derived information, and is particularly critical for long time base studies for climate change and enabling interoperability and Analysis Ready Data. The proposed TRUTHS (Traceable Radiometry Underpinning Terrestrial and Helio-Studies) mission is explicitly designed to address this issue through re-calibrating itself directly to a primary standard of the international system of units (SI) in-orbit and then through the extension of this SI-traceability to other sensors through in-flight cross-calibration using a selection of Committee on Earth Observation Satellites (CEOS) recommended test sites. Where the characteristics of the sensor under test allows, this will result in a significant improvement in accuracy. This paper describes a set of tools, algorithms and methodologies that have been developed and used in order to estimate the radiometric uncertainty achievable for an indicative target sensor through in-flight cross-calibration using a well-calibrated hyperspectral SI-traceable reference sensor with observational characteristics such as TRUTHS. In this study, Multi-Spectral Imager (MSI) of Sentinel-2 and Landsat-8 Operational Land Imager (OLI) is evaluated as an example, however the analysis is readily translatable to larger-footprint sensors such as Sentinel-3 Ocean and Land Colour Instrument (OLCI) and Visible Infrared Imaging Radiometer Suite (VIIRS). This study considers the criticality of the instrumental and observational characteristics on pixel level reflectance factors, within a defined spatial region of interest (ROI) within the target site. It quantifies the main uncertainty contributors in the spectral, spatial, and temporal domains. The resultant tool

Temperature Sensors Integrated into a CMOS Image Sensor

NARCIS (Netherlands)

Abarca Prouza, A.N.; Xie, S.; Markenhof, Jules; Theuwissen, A.J.P.

2017-01-01

In this work, a novel approach is presented for measuring relative temperature variations inside the pixel array of a CMOS image sensor itself. This approach can give important information when compensation for dark (current) fixed pattern noise (FPN) is needed. The test image sensor consists of

Determining fast orientation changes of multi-spectral line cameras from the primary images

Science.gov (United States)

Wohlfeil, Jürgen

2012-01-01

Fast orientation changes of airborne and spaceborne line cameras cannot always be avoided. In such cases it is essential to measure them with high accuracy to ensure a good quality of the resulting imagery products. Several approaches exist to support the orientation measurement by using optical information received through the main objective/telescope. In this article an approach is proposed that allows the determination of non-systematic orientation changes between every captured line. It does not require any additional camera hardware or onboard processing capabilities but the payload images and a rough estimate of the camera's trajectory. The approach takes advantage of the typical geometry of multi-spectral line cameras with a set of linear sensor arrays for different spectral bands on the focal plane. First, homologous points are detected within the heavily distorted images of different spectral bands. With their help a connected network of geometrical correspondences can be built up. This network is used to calculate the orientation changes of the camera with the temporal and angular resolution of the camera. The approach was tested with an extensive set of aerial surveys covering a wide range of different conditions and achieved precise and reliable results.

SPECTRAL FILTRATION OF IMAGES BY MEANS OF DISPERSIVE SYSTEMS

Directory of Open Access Journals (Sweden)

I. M. Gulis

2016-01-01

Full Text Available Instruments for spectral filtration of images are an important element of the systems used in remote sensing, medical diagnostics, in-process measurements. The aim of this study is analysis of the functional features and characteristics of the proposed two image monochromator versions which are based on dispersive spectral filtering. The first is based on the use of a dispersive monochromator, where collimating and camera lenses form a telescopic system, the dispersive element of which is within the intermediate image plane. The second version is based on an imaging double monochromator with dispersion subtraction by back propagation. For the telescopic system version, the spectral and spatial resolutions are estimated, the latter being limited by aberrations and diffraction from the entrance slit. The device has been numerically simulated and prototyped. It is shown that for the spectral bandwidth 10 nm (visible spectral range, the aberration-limited spot size is from 10–20 μm at the image center to about 30 μm at the image periphery for the image size 23–27 mm. The monochromator with dispersion subtraction enables one to vary the spectral resolution (up to 1 nm and higher by changing the intermediate slit width. But the distinctive feature is a significant change in the selected central wavelength over the image field. The considered designs of dispersive image monochromators look very promising due to the particular advantages over the systems based on tunable filters as regards the spectral resolution, fast tuning, and the spectral contrast. The monochromator based on a telescopic system has a simple design and a rather large image field but it also has a limited light throughput due to small aperture size. The monochromator with dispersion subtraction has higher light throughput, can provide high spectral resolution when recording a full data cube in a series of measuring acts for different dispersive element positions. 

Biomarkers and Biological Spectral Imaging

Science.gov (United States)

2001-01-23

G. Sowa, H. H. Mantsch, National Research Council Canada; S. L. Zhang, Unilever Research (USA) 85 Brain tissue charcterization using spectral imaging...image registration and of the expert staff of Hill Top Research in Winnipeg for hosting the hydration study. Financial assistance from Unilever Research

Hyperspectral image classifier based on beach spectral feature

International Nuclear Information System (INIS)

Liang, Zhang; Lianru, Gao; Bing, Zhang

2014-01-01

The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches

Spectral and dual-energy X-ray imaging for medical applications

Science.gov (United States)

Fredenberg, Erik

2018-01-01

Spectral imaging is an umbrella term for energy-resolved X-ray imaging in medicine. The technique makes use of the energy dependence of X-ray attenuation to either increase the contrast-to-noise ratio, or to provide quantitative image data and reduce image artefacts by so-called material decomposition. Spectral imaging is not new, but has gained interest in recent years because of rapidly increasing availability of spectral and dual-energy CT and the dawn of energy-resolved photon-counting detectors. This review examines the current technological status of spectral and dual-energy imaging and a number of practical applications of the technology in medicine.

PCA-based spatially adaptive denoising of CFA images for single-sensor digital cameras.

Science.gov (United States)

Zheng, Lei; Lukac, Rastislav; Wu, Xiaolin; Zhang, David

2009-04-01

Single-sensor digital color cameras use a process called color demosiacking to produce full color images from the data captured by a color filter array (CAF). The quality of demosiacked images is degraded due to the sensor noise introduced during the image acquisition process. The conventional solution to combating CFA sensor noise is demosiacking first, followed by a separate denoising processing. This strategy will generate many noise-caused color artifacts in the demosiacking process, which are hard to remove in the denoising process. Few denoising schemes that work directly on the CFA images have been presented because of the difficulties arisen from the red, green and blue interlaced mosaic pattern, yet a well-designed "denoising first and demosiacking later" scheme can have advantages such as less noise-caused color artifacts and cost-effective implementation. This paper presents a principle component analysis (PCA)-based spatially-adaptive denoising algorithm, which works directly on the CFA data using a supporting window to analyze the local image statistics. By exploiting the spatial and spectral correlations existing in the CFA image, the proposed method can effectively suppress noise while preserving color edges and details. Experiments using both simulated and real CFA images indicate that the proposed scheme outperforms many existing approaches, including those sophisticated demosiacking and denoising schemes, in terms of both objective measurement and visual evaluation.

Active spectral imaging nondestructive evaluation (SINDE) camera

Energy Technology Data Exchange (ETDEWEB)

Simova, E.; Rochefort, P.A., E-mail: eli.simova@cnl.ca [Canadian Nuclear Laboratories, Chalk River, Ontario (Canada)

2016-06-15

A proof-of-concept video camera for active spectral imaging nondestructive evaluation has been demonstrated. An active multispectral imaging technique has been implemented in the visible and near infrared by using light emitting diodes with wavelengths spanning from 400 to 970 nm. This shows how the camera can be used in nondestructive evaluation to inspect surfaces and spectrally identify materials and corrosion. (author)

Real-time DNA Amplification and Detection System Based on a CMOS Image Sensor.

Science.gov (United States)

Wang, Tiantian; Devadhasan, Jasmine Pramila; Lee, Do Young; Kim, Sanghyo

2016-01-01

In the present study, we developed a polypropylene well-integrated complementary metal oxide semiconductor (CMOS) platform to perform the loop mediated isothermal amplification (LAMP) technique for real-time DNA amplification and detection simultaneously. An amplification-coupled detection system directly measures the photon number changes based on the generation of magnesium pyrophosphate and color changes. The photon number decreases during the amplification process. The CMOS image sensor observes the photons and converts into digital units with the aid of an analog-to-digital converter (ADC). In addition, UV-spectral studies, optical color intensity detection, pH analysis, and electrophoresis detection were carried out to prove the efficiency of the CMOS sensor based the LAMP system. Moreover, Clostridium perfringens was utilized as proof-of-concept detection for the new system. We anticipate that this CMOS image sensor-based LAMP method will enable the creation of cost-effective, label-free, optical, real-time and portable molecular diagnostic devices.

Tomographic spectral imaging: microanalysis in 3D

International Nuclear Information System (INIS)

Kotula, P.G.; Keenan, M.R.; Michael, J.R.

2003-01-01

Full text: Spectral imaging, where a series of complete x-ray spectra are typically collected from a 2D area, holds great promise for comprehensive near-surface microanalysis. There are however numerous microanalysis problems where 3D chemical information is needed as well. In the SEM, some sort of sectioning (either mechanical or with a focused ion beam (FIB) tool) followed by x-ray mapping has, in the past, been utilized in an attempt to perform 3D microanalysis. Reliance on simple mapping has the potential to miss important chemical features as well as misidentify others. In this paper we will describe the acquisition of serial-section tomographic spectral images (TSI) with a dual-beam FIB/SEM equipped with an EDS system. We will also describe the application of a modified version of our multivariate statistical analysis algorithms to TSIs. Serial sectioning was performed with a FEI DB-235 FIB/SEM. Firstly, the specimen normal was tilted to the optic axis of the FIB column and a trench was milled into the surface of the specimen. A second trench was then milled perpendicular to the first to provide visibility of the entire analysis surface to the x-ray detector. In addition, several fiducial markers were milled into the surface to allow for alignment from slice to slice. The electron column is at an angle of 52 deg to the ion column so the electron beam can 'see' the analysis surface milled by the FIB with no additional specimen tilting or rotation. Likewise the x-ray detector is at a radial angle of 45 deg to the plane of the electron and ion columns (about the electron column) and a take-off-angle of 35 deg with respect to an untilted specimen so it can 'see' the analysis surface as well with no additional sample tilting or rotation. Spectral images were acquired from regions 40 μm wide and 20μm deep for each slice. Approximately 1μm/slice was milled and 10-12 total slices were cut. Spectral images were acquired with a Thermo NORAN Vantage (Digital imaging

Multi-spectral confocal microendoscope for in-vivo imaging

Science.gov (United States)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data

Directory of Open Access Journals (Sweden)

Daniel Scheffler

2017-07-01

Full Text Available Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal data. In recent decades, many algorithms have been developed to enable manual, semi- or fully automatic displacement correction. Especially in the context of big data processing and the development of automated processing chains that aim to be applicable to different remote sensing systems, there is a strong need for efficient, accurate and generally usable co-registration. Here, we present AROSICS (Automated and Robust Open-Source Image Co-Registration Software, a Python-based open-source software including an easy-to-use user interface for automatic detection and correction of sub-pixel misalignments between various remote sensing datasets. It is independent of spatial or spectral characteristics and robust against high degrees of cloud coverage and spectral and temporal land cover dynamics. The co-registration is based on phase correlation for sub-pixel shift estimation in the frequency domain utilizing the Fourier shift theorem in a moving-window manner. A dense grid of spatial shift vectors can be created and automatically filtered by combining various validation and quality estimation metrics. Additionally, the software supports the masking of, e.g., clouds and cloud shadows to exclude such areas from spatial shift detection. The software has been tested on more than 9000 satellite images acquired by different sensors. The results are evaluated exemplarily for two inter-sensoral and two intra-sensoral use cases and show registration results in the sub-pixel range with root mean square error fits around 0.3 pixels and better.

Recent progress of push-broom infrared hyper-spectral imager in SITP

Science.gov (United States)

Wang, Yueming; Hu, Weida; Shu, Rong; Li, Chunlai; Yuan, Liyin; Wang, Jianyu

2017-02-01

In the past decades, hyper-spectral imaging technologies were well developed in SITP, CAS. Many innovations for system design and key parts of hyper-spectral imager were finished. First airborne hyper-spectral imager operating from VNIR to TIR in the world was emerged in SITP. It is well known as OMIS(Operational Modular Imaging Spectrometer). Some new technologies were introduced to improve the performance of hyper-spectral imaging system in these years. A high spatial space-borne hyper-spectral imager aboard Tiangong-1 spacecraft was launched on Sep.29, 2011. Thanks for ground motion compensation and high optical efficiency prismatic spectrometer, a large amount of hyper-spectral imagery with high sensitivity and good quality were acquired in the past years. Some important phenomena were observed. To diminish spectral distortion and expand field of view, new type of prismatic imaging spectrometer based curved prism were proposed by SITP. A prototype of hyper-spectral imager based spherical fused silica prism were manufactured, which can operate from 400nm 2500nm. We also made progress in the development of LWIR hyper-spectral imaging technology. Compact and low F number LWIR imaging spectrometer was designed, manufactured and integrated. The spectrometer operated in a cryogenically-cooled vacuum box for background radiation restraint. The system performed well during flight experiment in an airborne platform. Thanks high sensitivity FPA and high performance optics, spatial resolution and spectral resolution and SNR of system are improved enormously. However, more work should be done for high radiometric accuracy in the future.

Multivariate statistical analysis for x-ray photoelectron spectroscopy spectral imaging: Effect of image acquisition time

International Nuclear Information System (INIS)

Peebles, D.E.; Ohlhausen, J.A.; Kotula, P.G.; Hutton, S.; Blomfield, C.

2004-01-01

The acquisition of spectral images for x-ray photoelectron spectroscopy (XPS) is a relatively new approach, although it has been used with other analytical spectroscopy tools for some time. This technique provides full spectral information at every pixel of an image, in order to provide a complete chemical mapping of the imaged surface area. Multivariate statistical analysis techniques applied to the spectral image data allow the determination of chemical component species, and their distribution and concentrations, with minimal data acquisition and processing times. Some of these statistical techniques have proven to be very robust and efficient methods for deriving physically realistic chemical components without input by the user other than the spectral matrix itself. The benefits of multivariate analysis of the spectral image data include significantly improved signal to noise, improved image contrast and intensity uniformity, and improved spatial resolution - which are achieved due to the effective statistical aggregation of the large number of often noisy data points in the image. This work demonstrates the improvements in chemical component determination and contrast, signal-to-noise level, and spatial resolution that can be obtained by the application of multivariate statistical analysis to XPS spectral images

Multi-layer imager design for mega-voltage spectral imaging

Science.gov (United States)

Myronakis, Marios; Hu, Yue-Houng; Fueglistaller, Rony; Wang, Adam; Baturin, Paul; Huber, Pascal; Morf, Daniel; Star-Lack, Josh; Berbeco, Ross

2018-05-01

The architecture of multi-layer imagers (MLIs) can be exploited to provide megavoltage spectral imaging (MVSPI) for specific imaging tasks. In the current work, we investigated bone suppression and gold fiducial contrast enhancement as two clinical tasks which could be improved with spectral imaging. A method based on analytical calculations that enables rapid investigation of MLI component materials and thicknesses was developed and validated against Monte Carlo computations. The figure of merit for task-specific imaging performance was the contrast-to-noise ratio (CNR) of the gold fiducial when the CNR of bone was equal to zero after a weighted subtraction of the signals obtained from each MLI layer. Results demonstrated a sharp increase in the CNR of gold when the build-up component or scintillation materials and thicknesses were modified. The potential for low-cost, prompt implementation of specific modifications (e.g. composition of the build-up component) could accelerate clinical translation of MVSPI.

Cost effective spectral sensor solutions for hand held and field applications

Science.gov (United States)

Reetz, Edgar; Correns, Martin; Notni, Gunther

2015-05-01

Optical spectroscopy is without doubt one of the most important non-contact measurement principles. It is used in a wide range of applications from bio-medical to industrial fields. One recent trend is to miniaturize spectral sensors to address new areas of application. The most common spectral sensor type is based on diffraction gratings, while other types are based on micro mechanical systems (MEMS) or filter technologies. The authors represent the opinion that there is a potentially wide spread field of applications for spectrometers, but the market limits the range of applications since they cannot keep up with targeted cost requirements for consumer products. The present article explains an alternative approach for miniature multichannel spectrometer to enhance robustness for hand held field applications at a cost efficient price point.

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

Science.gov (United States)

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

Acquisition and visualization techniques for narrow spectral color imaging.

Science.gov (United States)

Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

2013-06-01

This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

Automated Registration Of Images From Multiple Sensors

Science.gov (United States)

Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.; Pang, Shirley S. N.

1994-01-01

Images of terrain scanned in common by multiple Earth-orbiting remote sensors registered automatically with each other and, where possible, on geographic coordinate grid. Simulated image of terrain viewed by sensor computed from ancillary data, viewing geometry, and mathematical model of physics of imaging. In proposed registration algorithm, simulated and actual sensor images matched by area-correlation technique.

[Research on Spectral Polarization Imaging System Based on Static Modulation].

Science.gov (United States)

Zhao, Hai-bo; Li, Huan; Lin, Xu-ling; Wang, Zheng

2015-04-01

The main disadvantages of traditional spectral polarization imaging system are: complex structure, with moving parts, low throughput. A novel method of spectral polarization imaging system is discussed, which is based on static polarization intensity modulation combined with Savart polariscope interference imaging. The imaging system can obtain real-time information of spectral and four Stokes polarization messages. Compared with the conventional methods, the advantages of the imaging system are compactness, low mass and no moving parts, no electrical control, no slit and big throughput. The system structure and the basic theory are introduced. The experimental system is established in the laboratory. The experimental system consists of reimaging optics, polarization intensity module, interference imaging module, and CCD data collecting and processing module. The spectral range is visible and near-infrared (480-950 nm). The white board and the plane toy are imaged by using the experimental system. The ability of obtaining spectral polarization imaging information is verified. The calibration system of static polarization modulation is set up. The statistical error of polarization degree detection is less than 5%. The validity and feasibility of the basic principle is proved by the experimental result. The spectral polarization data captured by the system can be applied to object identification, object classification and remote sensing detection.

OPTICAL FIBRES AND FIBREOPTIC SENSORS: Fibreoptic distributed temperature sensor with spectral filtration by directional fibre couplers

Science.gov (United States)

Kuznetsov, A. G.; Babin, Sergei A.; Shelemba, Ivan S.

2009-11-01

We demonstrate a Raman-based all-fibre temperature sensor utilising a pulsed erbium fibre laser. The sensor is made of a standard single-mode telecom fibre, SMF-28, and includes a number of directional couplers as band-pass filters. The temperature profile along a 7-km fibreoptic line is measured with an accuracy of 2oC and a spatial resolution of 10 m. In data processing, we take into account the difference in attenuation between the spectral components of the backscatter signal.

Remote Sensing of Landscapes with Spectral Images

Science.gov (United States)

Adams, John B.; Gillespie, Alan R.

2006-05-01

Remote Sensing of Landscapes with Spectral Images describes how to process and interpret spectral images using physical models to bridge the gap between the engineering and theoretical sides of remote-sensing and the world that we encounter when we venture outdoors. The emphasis is on the practical use of images rather than on theory and mathematical derivations. Examples are drawn from a variety of landscapes and interpretations are tested against the reality seen on the ground. The reader is led through analysis of real images (using figures and explanations); the examples are chosen to illustrate important aspects of the analytic framework. This textbook will form a valuable reference for graduate students and professionals in a variety of disciplines including ecology, forestry, geology, geography, urban planning, archeology and civil engineering. It is supplemented by a web-site hosting digital color versions of figures in the book as well as ancillary images (www.cambridge.org/9780521662214). Presents a coherent view of practical remote sensing, leading from imaging and field work to the generation of useful thematic maps Explains how to apply physical models to help interpret spectral images Supplemented by a website hosting digital colour versions of figures in the book, as well as additional colour figures

Regularized image denoising based on spectral gradient optimization

International Nuclear Information System (INIS)

Lukić, Tibor; Lindblad, Joakim; Sladoje, Nataša

2011-01-01

Image restoration methods, such as denoising, deblurring, inpainting, etc, are often based on the minimization of an appropriately defined energy function. We consider energy functions for image denoising which combine a quadratic data-fidelity term and a regularization term, where the properties of the latter are determined by a used potential function. Many potential functions are suggested for different purposes in the literature. We compare the denoising performance achieved by ten different potential functions. Several methods for efficient minimization of regularized energy functions exist. Most are only applicable to particular choices of potential functions, however. To enable a comparison of all the observed potential functions, we propose to minimize the objective function using a spectral gradient approach; spectral gradient methods put very weak restrictions on the used potential function. We present and evaluate the performance of one spectral conjugate gradient and one cyclic spectral gradient algorithm, and conclude from experiments that both are well suited for the task. We compare the performance with three total variation-based state-of-the-art methods for image denoising. From the empirical evaluation, we conclude that denoising using the Huber potential (for images degraded by higher levels of noise; signal-to-noise ratio below 10 dB) and the Geman and McClure potential (for less noisy images), in combination with the spectral conjugate gradient minimization algorithm, shows the overall best performance

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

Science.gov (United States)

Lu, Liang; Qi, Lin; Luo, Yisong; Jiao, Hengchao; Dong, Junyu

2018-01-01

Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN) instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods. PMID:29498703

Three-Dimensional Reconstruction from Single Image Base on Combination of CNN and Multi-Spectral Photometric Stereo

Directory of Open Access Journals (Sweden)

Liang Lu

2018-03-01

Full Text Available Multi-spectral photometric stereo can recover pixel-wise surface normal from a single RGB image. The difficulty lies in that the intensity in each channel is the tangle of illumination, albedo and camera response; thus, an initial estimate of the normal is required in optimization-based solutions. In this paper, we propose to make a rough depth estimation using the deep convolutional neural network (CNN instead of using depth sensors or binocular stereo devices. Since high-resolution ground-truth data is expensive to obtain, we designed a network and trained it with rendered images of synthetic 3D objects. We use the model to predict initial normal of real-world objects and iteratively optimize the fine-scale geometry in the multi-spectral photometric stereo framework. The experimental results illustrate the improvement of the proposed method compared with existing methods.

Canny Edge Detection in Cross-Spectral Fused Images

Directory of Open Access Journals (Sweden)

Patricia Suárez

2017-02-01

Full Text Available Considering that the images of different spectra provide an ample information that helps a lo in the process of identification and distinction of objects that have unique spectral signatures. In this paper, the use of cross-spectral images in the process of edge detection is evaluated. This study aims to assess the Canny edge detector with two variants. The first relates to the use of merged cross-spectral images and the second the inclusion of morphological filters. To ensure the quality of the data used in this study the GQM (Goal-Question- Metrics, framework, was applied to reduce noise and increase the entropy on images. The metrics obtained in the experiments confirm that the quantity and quality of the detected edges increases significantly after the inclusion of a morphological filter and a channel of near infrared spectrum in the merged images.

GALILEO NIMS SPECTRAL IMAGE CUBES: JUPITER OPERATIONS

Data.gov (United States)

National Aeronautics and Space Administration — The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images'...

GALILEO NIMS SPECTRAL IMAGE TUBES: JUPITER OPERATIONS

Data.gov (United States)

National Aeronautics and Space Administration — The natural form of imaging spectrometer data is the spectral image cube. It is normally in band sequential format, but has a dual nature. It is a series of 'images'...

The spectral imaging facility: Setup characterization

Energy Technology Data Exchange (ETDEWEB)

De Angelis, Simone, E-mail: simone.deangelis@iaps.inaf.it; De Sanctis, Maria Cristina; Manzari, Paola Olga [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Ammannito, Eleonora [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, Los Angeles, California 90095-1567 (United States); Di Iorio, Tatiana [ENEA, UTMEA-TER, Rome (Italy); Liberati, Fabrizio [Opto Service SrL, Campagnano di Roma (RM) (Italy); Tarchi, Fabio; Dami, Michele; Olivieri, Monica; Pompei, Carlo [Selex ES, Campi Bisenzio (Italy); Mugnuolo, Raffaele [Italian Space Agency, ASI, Spatial Geodesy Center, Matera (Italy)

2015-09-15

The SPectral IMager (SPIM) facility is a laboratory visible infrared spectrometer developed to support space borne observations of rocky bodies of the solar system. Currently, this laboratory setup is used to support the DAWN mission, which is in its journey towards the asteroid 1-Ceres, and to support the 2018 Exo-Mars mission in the spectral investigation of the Martian subsurface. The main part of this setup is an imaging spectrometer that is a spare of the DAWN visible infrared spectrometer. The spectrometer has been assembled and calibrated at Selex ES and then installed in the facility developed at the INAF-IAPS laboratory in Rome. The goal of SPIM is to collect data to build spectral libraries for the interpretation of the space borne and in situ hyperspectral measurements of planetary materials. Given its very high spatial resolution combined with the imaging capability, this instrument can also help in the detailed study of minerals and rocks. In this paper, the instrument setup is first described, and then a series of test measurements, aimed to the characterization of the main subsystems, are reported. In particular, laboratory tests have been performed concerning (i) the radiation sources, (ii) the reference targets, and (iii) linearity of detector response; the instrumental imaging artifacts have also been investigated.

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

Science.gov (United States)

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Self-training-based spectral image reconstruction for art paintings with multispectral imaging.

Science.gov (United States)

Xu, Peng; Xu, Haisong; Diao, Changyu; Ye, Zhengnan

2017-10-20

A self-training-based spectral reflectance recovery method was developed to accurately reconstruct the spectral images of art paintings with multispectral imaging. By partitioning the multispectral images with the k-means clustering algorithm, the training samples are directly extracted from the art painting itself to restrain the deterioration of spectral estimation caused by the material inconsistency between the training samples and the art painting. Coordinate paper is used to locate the extracted training samples. The spectral reflectances of the extracted training samples are acquired indirectly with a spectroradiometer, and the circle Hough transform is adopted to detect the circle measuring area of the spectroradiometer. Through simulation and a practical experiment, the implementation of the proposed method is explained in detail, and it is verified to have better reflectance recovery performance than that using the commercial target and is comparable to the approach using a painted color target.

Image-based occupancy sensor

Science.gov (United States)

Polese, Luigi Gentile; Brackney, Larry

2015-05-19

An image-based occupancy sensor includes a motion detection module that receives and processes an image signal to generate a motion detection signal, a people detection module that receives the image signal and processes the image signal to generate a people detection signal, a face detection module that receives the image signal and processes the image signal to generate a face detection signal, and a sensor integration module that receives the motion detection signal from the motion detection module, receives the people detection signal from the people detection module, receives the face detection signal from the face detection module, and generates an occupancy signal using the motion detection signal, the people detection signal, and the face detection signal, with the occupancy signal indicating vacancy or occupancy, with an occupancy indication specifying that one or more people are detected within the monitored volume.

Improving image quality in portal venography with spectral CT imaging

International Nuclear Information System (INIS)

Zhao, Li-qin; He, Wen; Li, Jian-ying; Chen, Jiang-hong; Wang, Ke-yang; Tan, Li

2012-01-01

Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

Improving image quality in portal venography with spectral CT imaging

Energy Technology Data Exchange (ETDEWEB)

Zhao, Li-qin, E-mail: zhaolqzr@sohu.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); He, Wen, E-mail: hewen1724@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Li, Jian-ying, E-mail: jianying.li@med.ge.com [CT Advanced Application and Research, GE Healthcare, 100176 China (China); Chen, Jiang-hong, E-mail: chenjianghong1973@hotmail.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Wang, Ke-yang, E-mail: ke7ke@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Tan, Li, E-mail: Litan@ge.com [CT product, GE Healthcare, 100176 China (China)

2012-08-15

Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

A New Multichannel Spectral Imaging Laser Scanning Confocal Microscope

Directory of Open Access Journals (Sweden)

Yunhai Zhang

2013-01-01

Full Text Available We have developed a new multichannel spectral imaging laser scanning confocal microscope for effective detection of multiple fluorescent labeling in the research of biological tissues. In this paper, the design and key technologies of the system are introduced. Representative results on confocal imaging, 3-dimensional sectioning imaging, and spectral imaging are demonstrated. The results indicated that the system is applicable to multiple fluorescent labeling in biological experiments.

A Method of Particle Swarm Optimized SVM Hyper-spectral Remote Sensing Image Classification

International Nuclear Information System (INIS)

Liu, Q J; Jing, L H; Wang, L M; Lin, Q Z

2014-01-01

Support Vector Machine (SVM) has been proved to be suitable for classification of remote sensing image and proposed to overcome the Hughes phenomenon. Hyper-spectral sensors are intrinsically designed to discriminate among a broad range of land cover classes which may lead to high computational time in SVM mutil-class algorithms. Model selection for SVM involving kernel and the margin parameter values selection which is usually time-consuming, impacts training efficiency of SVM model and final classification accuracies of SVM hyper-spectral remote sensing image classifier greatly. Firstly, based on combinatorial optimization theory and cross-validation method, particle swarm algorithm is introduced to the optimal selection of SVM (PSSVM) kernel parameter σ and margin parameter C to improve the modelling efficiency of SVM model. Then an experiment of classifying AVIRIS in India Pine site of USA was performed for evaluating the novel PSSVM, as well as traditional SVM classifier with general Grid-Search cross-validation method (GSSVM). And then, evaluation indexes including SVM model training time, classification Overall Accuracy (OA) and Kappa index of both PSSVM and GSSVM are all analyzed quantitatively. It is demonstrated that OA of PSSVM on test samples and whole image are 85% and 82%, the differences with that of GSSVM are both within 0.08% respectively. And Kappa indexes reach 0.82 and 0.77, the differences with that of GSSVM are both within 0.001. While the modelling time of PSSVM can be only 1/10 of that of GSSVM, and the modelling. Therefore, PSSVM is an fast and accurate algorithm for hyper-spectral image classification and is superior to GSSVM

CMOS foveal image sensor chip

Science.gov (United States)

Bandera, Cesar (Inventor); Scott, Peter (Inventor); Sridhar, Ramalingam (Inventor); Xia, Shu (Inventor)

2002-01-01

A foveal image sensor integrated circuit comprising a plurality of CMOS active pixel sensors arranged both within and about a central fovea region of the chip. The pixels in the central fovea region have a smaller size than the pixels arranged in peripheral rings about the central region. A new photocharge normalization scheme and associated circuitry normalizes the output signals from the different size pixels in the array. The pixels are assembled into a multi-resolution rectilinear foveal image sensor chip using a novel access scheme to reduce the number of analog RAM cells needed. Localized spatial resolution declines monotonically with offset from the imager's optical axis, analogous to biological foveal vision.

CMOS image sensor-based implantable glucose sensor using glucose-responsive fluorescent hydrogel.

Science.gov (United States)

Tokuda, Takashi; Takahashi, Masayuki; Uejima, Kazuhiro; Masuda, Keita; Kawamura, Toshikazu; Ohta, Yasumi; Motoyama, Mayumi; Noda, Toshihiko; Sasagawa, Kiyotaka; Okitsu, Teru; Takeuchi, Shoji; Ohta, Jun

2014-11-01

A CMOS image sensor-based implantable glucose sensor based on an optical-sensing scheme is proposed and experimentally verified. A glucose-responsive fluorescent hydrogel is used as the mediator in the measurement scheme. The wired implantable glucose sensor was realized by integrating a CMOS image sensor, hydrogel, UV light emitting diodes, and an optical filter on a flexible polyimide substrate. Feasibility of the glucose sensor was verified by both in vitro and in vivo experiments.

Image enhancement by spectral-error correction for dual-energy computed tomography.

Science.gov (United States)

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Multi-spectral endogenous fluorescence imaging for bacterial differentiation

Science.gov (United States)

Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

2017-07-01

In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

Spectral Imaging for Intracranial Stents and Stent Lumen.

Science.gov (United States)

Weng, Chi-Lun; Tseng, Ying-Chi; Chen, David Yen-Ting; Chen, Chi-Jen; Hsu, Hui-Ling

2016-01-01

Application of computed tomography for monitoring intracranial stents is limited because of stent-related artifacts. Our purpose was to evaluate the effect of gemstone spectral imaging on the intracranial stent and stent lumen. In vitro, we scanned Enterprise stent phantom and a stent-cheese complex using the gemstone spectral imaging protocol. Follow-up gemstone spectral images of 15 consecutive patients with placement of Enterprise from January 2013 to September 2014 were also retrospectively reviewed. We used 70-keV, 140-keV, iodine (water), iodine (calcium), and iodine (hydroxyapatite) images to evaluate their effect on the intracranial stent and stent lumen. Two regions of interest were individually placed in stent lumen and adjacent brain tissue. Contrast-to-noise ratio was measured to determine image quality. The maximal diameter of stent markers was also measured to evaluate stent-related artifact. Two radiologists independently graded the visibility of the lumen at the maker location by using a 4-point scale. The mean of grading score, contrast/noise ratio and maximal diameter of stent markers were compared among all modes. All results were analyzed by SPSS version 20. In vitro, iodine (water) images decreased metallic artifact of stent makers to the greatest degree. The most areas of cheese were observed on iodine (water) images. In vivo, iodine (water) images had the smallest average diameter of stent markers (0.33 ± 0.17mm; P stent lumen (160.03 ±37.79; P stent-related artifacts of Enterprise and enhance contrast of in-stent lumen. Spectral imaging may be considered a noninvasive modality for following-up patients with in-stent stenosis.

A 128 x 128 CMOS Active Pixel Image Sensor for Highly Integrated Imaging Systems

Science.gov (United States)

Mendis, Sunetra K.; Kemeny, Sabrina E.; Fossum, Eric R.

1993-01-01

A new CMOS-based image sensor that is intrinsically compatible with on-chip CMOS circuitry is reported. The new CMOS active pixel image sensor achieves low noise, high sensitivity, X-Y addressability, and has simple timing requirements. The image sensor was fabricated using a 2 micrometer p-well CMOS process, and consists of a 128 x 128 array of 40 micrometer x 40 micrometer pixels. The CMOS image sensor technology enables highly integrated smart image sensors, and makes the design, incorporation and fabrication of such sensors widely accessible to the integrated circuit community.

Ultrahigh sensitivity endoscopic camera using a new CMOS image sensor: providing with clear images under low illumination in addition to fluorescent images.

Science.gov (United States)

Aoki, Hisae; Yamashita, Hiromasa; Mori, Toshiyuki; Fukuyo, Tsuneo; Chiba, Toshio

2014-11-01

We developed a new ultrahigh-sensitive CMOS camera using a specific sensor that has a wide range of spectral sensitivity characteristics. The objective of this study is to present our updated endoscopic technology that has successfully integrated two innovative functions; ultrasensitive imaging as well as advanced fluorescent viewing. Two different experiments were conducted. One was carried out to evaluate the function of the ultrahigh-sensitive camera. The other was to test the availability of the newly developed sensor and its performance as a fluorescence endoscope. In both studies, the distance from the endoscopic tip to the target was varied and those endoscopic images in each setting were taken for further comparison. In the first experiment, the 3-CCD camera failed to display the clear images under low illumination, and the target was hardly seen. In contrast, the CMOS camera was able to display the targets regardless of the camera-target distance under low illumination. Under high illumination, imaging quality given by both cameras was quite alike. In the second experiment as a fluorescence endoscope, the CMOS camera was capable of clearly showing the fluorescent-activated organs. The ultrahigh sensitivity CMOS HD endoscopic camera is expected to provide us with clear images under low illumination in addition to the fluorescent images under high illumination in the field of laparoscopic surgery.

CMOS Image Sensors: Electronic Camera On A Chip

Science.gov (United States)

Fossum, E. R.

1995-01-01

Recent advancements in CMOS image sensor technology are reviewed, including both passive pixel sensors and active pixel sensors. On- chip analog to digital converters and on-chip timing and control circuits permit realization of an electronic camera-on-a-chip. Highly miniaturized imaging systems based on CMOS image sensor technology are emerging as a competitor to charge-coupled devices for low cost uses.

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

A Wide Spectral Range Reflectance and Luminescence Imaging System

Directory of Open Access Journals (Sweden)

Tapani Hirvonen

2013-10-01

Full Text Available In this study, we introduce a wide spectral range (200–2500 nm imaging system with a 250 μm minimum spatial resolution, which can be freely modified for a wide range of resolutions and measurement geometries. The system has been tested for reflectance and luminescence measurements, but can also be customized for transmittance measurements. This study includes the performance results of the developed system, as well as examples of spectral images. Discussion of the system relates it to existing systems and methods. The wide range spectral imaging system that has been developed is however highly customizable and has great potential in many practical applications.

EVALUATION OF VARIOUS SPECTRAL INPUTS FOR ESTIMATION OF FOREST BIOCHEMICAL AND STRUCTURAL PROPERTIES FROM AIRBORNE IMAGING SPECTROSCOPY DATA

Directory of Open Access Journals (Sweden)

L. Homolová

2016-06-01

Full Text Available In this study we evaluated various spectral inputs for retrieval of forest chlorophyll content (Cab and leaf area index (LAI from high spectral and spatial resolution airborne imaging spectroscopy data collected for two forest study sites in the Czech Republic (beech forest at Štítná nad Vláří and spruce forest at Bílý Kříž. The retrieval algorithm was based on a machine learning method – support vector regression (SVR. Performance of the four spectral inputs used to train SVR was evaluated: a all available hyperspectral bands, b continuum removal (CR 645 – 710 nm, c CR 705 – 780 nm, and d CR 680 – 800 nm. Spectral inputs and corresponding SVR models were first assessed at the level of spectral databases simulated by combined leaf-canopy radiative transfer models PROSPECT and DART. At this stage, SVR models using all spectral inputs provided good performance (RMSE for Cab −2 and for LAI < 1.5, with consistently better performance for beech over spruce site. Since application of trained SVRs on airborne hyperspectral images of the spruce site produced unacceptably overestimated values, only the beech site results were analysed. The best performance for the Cab estimation was found for CR bands in range of 645 – 710 nm, whereas CR bands in range of 680 – 800 nm were the most suitable for LAI retrieval. The CR transformation reduced the across-track bidirectional reflectance effect present in airborne images due to large sensor field of view.

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.

Image Sensor

OpenAIRE

Jerram, Paul; Stefanov, Konstantin

2017-01-01

An image sensor of the type for providing charge multiplication by impact ionisation has plurality of multiplication elements. Each element is arranged to receive charge from photosensitive elements of an image area and each element comprises a sequence of electrodes to move charge along a transport path. Each of the electrodes has an edge defining a boundary with a first electrode, a maximum width across the charge transport path and a leading edge that defines a boundary with a second elect...

Priority image transmission in wireless sensor networks

International Nuclear Information System (INIS)

Nasri, M.; Helali, A.; Sghaier, H.; Maaref, H.

2011-01-01

The emerging technology during the last years allowed the development of new sensors equipped with wireless communication which can be organized into a cooperative autonomous network. Some application areas for wireless sensor networks (WSNs) are home automations, health care services, military domain, and environment monitoring. The required constraints are limited capacity of processing, limited storage capability, and especially these nodes are limited in energy. In addition, such networks are tiny battery powered which their lifetime is very limited. During image processing and transmission to the destination, the lifetime of sensor network is decreased quickly due to battery and processing power constraints. Therefore, digital image transmissions are a significant challenge for image sensor based Wireless Sensor Networks (WSNs). Based on a wavelet image compression, we propose a novel, robust and energy-efficient scheme, called Priority Image Transmission (PIT) in WSN by providing various priority levels during image transmissions. Different priorities in the compressed image are considered. The information for the significant wavelet coeffcients are transmitted with higher quality assurance, whereas relatively less important coefficients are transmitted with lower overhead. Simulation results show that the proposed scheme prolongs the system lifetime and achieves higher energy efficiency in WSN with an acceptable compromise on the image quality.

Imaging in scattering media using correlation image sensors and sparse convolutional coding

KAUST Repository

Heide, Felix; Xiao, Lei; Kolb, Andreas; Hullin, Matthias B.; Heidrich, Wolfgang

2014-01-01

Correlation image sensors have recently become popular low-cost devices for time-of-flight, or range cameras. They usually operate under the assumption of a single light path contributing to each pixel. We show that a more thorough analysis of the sensor data from correlation sensors can be used can be used to analyze the light transport in much more complex environments, including applications for imaging through scattering and turbid media. The key of our method is a new convolutional sparse coding approach for recovering transient (light-in-flight) images from correlation image sensors. This approach is enabled by an analysis of sparsity in complex transient images, and the derivation of a new physically-motivated model for transient images with drastically improved sparsity.

Imaging in scattering media using correlation image sensors and sparse convolutional coding

KAUST Repository

Heide, Felix

2014-10-17

Correlation image sensors have recently become popular low-cost devices for time-of-flight, or range cameras. They usually operate under the assumption of a single light path contributing to each pixel. We show that a more thorough analysis of the sensor data from correlation sensors can be used can be used to analyze the light transport in much more complex environments, including applications for imaging through scattering and turbid media. The key of our method is a new convolutional sparse coding approach for recovering transient (light-in-flight) images from correlation image sensors. This approach is enabled by an analysis of sparsity in complex transient images, and the derivation of a new physically-motivated model for transient images with drastically improved sparsity.

Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale

Directory of Open Access Journals (Sweden)

Anne Clasen

2015-11-01

Full Text Available Forest biochemical and biophysical variables and their spatial and temporal distribution are essential inputs to process-orientated ecosystem models. To provide this information, imaging spectroscopy appears to be a promising tool. In this context, the present study investigates the potential of spectral unmixing to derive sub-pixel crown component fractions in a temperate deciduous forest ecosystem. However, the high proportion of foliage in this complex vegetation structure leads to the problem of saturation effects, when applying broadband vegetation indices. This study illustrates that multiple endmember spectral mixture analysis (MESMA can contribute to overcoming this challenge. Reference fractional abundances, as well as spectral measurements of the canopy components, could be precisely determined from a crane measurement platform situated in a deciduous forest in North-East Germany. In contrast to most other studies, which only use leaf and soil endmembers, this experimental setup allowed for the inclusion of a bark endmember for the unmixing of components within the canopy. This study demonstrates that the inclusion of additional endmembers markedly improves the accuracy. A mean absolute error of 7.9% could be achieved for the fractional occurrence of the leaf endmember and 5.9% for the bark endmember. In order to evaluate the results of this field-based study for airborne and satellite-based remote sensing applications, a transfer to Airborne Imaging Spectrometer for Applications (AISA and simulated Environmental Mapping and Analysis Program (EnMAP and Sentinel-2 imagery was carried out. All sensors were capable of unmixing crown components with a mean absolute error ranging between 3% and 21%.

Technology for detecting spectral radiance by a snapshot multi-imaging spectroradiometer

Science.gov (United States)

Zuber, Ralf; Stührmann, Ansgar; Gugg-Helminger, Anton; Seckmeyer, Gunther

2017-12-01

Technologies to determine spectral sky radiance distributions have evolved in recent years and have enabled new applications in remote sensing, for sky radiance measurements, in biological/diagnostic applications and luminance measurements. Most classical spectral imaging radiance technologies are based on mechanical and/or spectral scans. However, these methods require scanning time in which the spectral radiance distribution might change. To overcome this limitation, different so-called snapshot spectral imaging technologies have been developed that enable spectral and spatial non-scanning measurements. We present a new setup based on a facet mirror that is already used in imaging slicing spectrometers. By duplicating the input image instead of slicing it and using a specially designed entrance slit, we are able to select nearly 200 (14 × 14) channels within the field of view (FOV) for detecting spectral radiance in different directions. In addition, a megapixel image of the FOV is captured by an additional RGB camera. This image can be mapped onto the snapshot spectral image. In this paper, the mechanical setup, technical design considerations and first measurement results of a prototype are presented. For a proof of concept, the device is radiometrically calibrated and a 10 mm × 10 mm test pattern measured within a spectral range of 380 nm-800 nm with an optical bandwidth of 10 nm (full width at half maximum or FWHM). To show its potential in the UV spectral region, zenith sky radiance measurements in the UV of a clear sky were performed. Hence, the prototype was equipped with an entrance optic with a FOV of 0.5° and modified to obtain a radiometrically calibrated spectral range of 280 nm-470 nm with a FWHM of 3 nm. The measurement results have been compared to modeled data processed by UVSPEC, which showed deviations of less than 30%. This is far from being ideal, but an acceptable result with respect to available state

A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

Directory of Open Access Journals (Sweden)

Yi Wang

2016-11-01

Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

Development of Fluorescence Spectral Imaging for Location of Uranium Deposited on Surfaces

International Nuclear Information System (INIS)

Monts, D.L.; Wang, G.; Su, Y.; Jang, P.R.; Waggoner, Ch.A.

2009-01-01

Since the 1980's, depleted uranium (DU) has been the primary material used by the US military in armor-piercing rounds. Domestic firing ranges that have been used for DU munitions training purposes are located around the country and have varying extents of contamination by other types of projectiles. A project is underway to develop a set of sensors to locate expended DU rounds and to process soil and debris to recover the material. In the environment, metallic DU readily oxidizes to form uranium compounds that contain the uranyl (UO 2 +2 ) moiety. For more than a hundred and fifty years, it has been known that when illuminated with ultraviolet (UV) light, uranyl compounds exhibit characteristic fluorescence in the visible region (450 - 650 nm). We report our efforts to develop a transportable, quantitative Fluorescence Spectral Imaging (FSI) system to locate and quantify uranyl compounds dispersed in soils and on other surfaces on domestic firing ranges; this system can also be utilized to monitor excavation of DU munitions and separation of uranyl compounds from soils. FSI images are acquired by illuminating a surface with a UV light and using a narrow band pass filter on a camera, recording an image of the resulting fluorescence. FSI images provide both spatial and spectral information. The FSI system is described and its performance characterized in the field and also by using field samples. The development and characterization of an improved transportable FSI system is presented. The applicability of this system for detection of uranium compounds deposited on surfaces for Decontaminating and Decommissioning (D and D) activities is discussed. We have successfully demonstrated in situ a first-generation, transportable Fluorescence Spectral Imaging (FSI) system for locating uranyl compounds dispersed in soils and on other surfaces of a domestic firing range. FSI images provide both spatial and spectral information. FSI images are acquired by illuminating a

Multi-material decomposition of spectral CT images

Science.gov (United States)

Mendonça, Paulo R. S.; Bhotika, Rahul; Maddah, Mahnaz; Thomsen, Brian; Dutta, Sandeep; Licato, Paul E.; Joshi, Mukta C.

2010-04-01

Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

Beam imaging sensor and method for using same

Energy Technology Data Exchange (ETDEWEB)

McAninch, Michael D.; Root, Jeffrey J.

2017-01-03

The present invention relates generally to the field of sensors for beam imaging and, in particular, to a new and useful beam imaging sensor for use in determining, for example, the power density distribution of a beam including, but not limited to, an electron beam or an ion beam. In one embodiment, the beam imaging sensor of the present invention comprises, among other items, a circumferential slit that is either circular, elliptical or polygonal in nature. In another embodiment, the beam imaging sensor of the present invention comprises, among other things, a discontinuous partially circumferential slit. Also disclosed is a method for using the various beams sensor embodiments of the present invention.

Biologically-inspired data decorrelation for hyper-spectral imaging

Directory of Open Access Journals (Sweden)

Ghita Ovidiu

2011-01-01

Full Text Available Abstract Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA, linear discriminant analysis (LDA, wavelet decomposition (WD, or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Image-based environmental monitoring sensor application using an embedded wireless sensor network.

Science.gov (United States)

Paek, Jeongyeup; Hicks, John; Coe, Sharon; Govindan, Ramesh

2014-08-28

This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet's built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Cannot Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions.

Image-Based Environmental Monitoring Sensor Application Using an Embedded Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Jeongyeup Paek

2014-08-01

Full Text Available This article discusses the experiences from the development and deployment of two image-based environmental monitoring sensor applications using an embedded wireless sensor network. Our system uses low-power image sensors and the Tenet general purpose sensing system for tiered embedded wireless sensor networks. It leverages Tenet’s built-in support for reliable delivery of high rate sensing data, scalability and its flexible scripting language, which enables mote-side image compression and the ease of deployment. Our first deployment of a pitfall trap monitoring application at the James San Jacinto Mountain Reserve provided us with insights and lessons learned into the deployment of and compression schemes for these embedded wireless imaging systems. Our three month-long deployment of a bird nest monitoring application resulted in over 100,000 images collected from a 19-camera node network deployed over an area of 0.05 square miles, despite highly variable environmental conditions. Our biologists found the on-line, near-real-time access to images to be useful for obtaining data on answering their biological questions.

Multispectral Imaging in Cultural Heritage Conservation

Science.gov (United States)

Del Pozo, S.; Rodríguez-Gonzálvez, P.; Sánchez-Aparicio, L. J.; Muñoz-Nieto, A.; Hernández-López, D.; Felipe-García, B.; González-Aguilera, D.

2017-08-01

This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum). In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

MULTISPECTRAL IMAGING IN CULTURAL HERITAGE CONSERVATION

Directory of Open Access Journals (Sweden)

S. Del Pozo

2017-08-01

Full Text Available This paper sums up the main contribution derived from the thesis entitled "Multispectral imaging for the analysis of materials and pathologies in civil engineering, constructions and natural spaces" awarded by CIPA-ICOMOS for its connection with the preservation of Cultural Heritage. This thesis is framed within close-range remote sensing approaches by the fusion of sensors operating in the optical domain (visible to shortwave infrared spectrum. In the field of heritage preservation, multispectral imaging is a suitable technique due to its non-destructive nature and its versatility. It combines imaging and spectroscopy to analyse materials and land covers and enables the use of a variety of different geomatic sensors for this purpose. These sensors collect both spatial and spectral information for a given scenario and a specific spectral range, so that, their smaller storage units save the spectral properties of the radiation reflected by the surface of interest. The main goal of this research work is to characterise different construction materials as well as the main pathologies of Cultural Heritage elements by combining active and passive sensors recording data in different ranges. Conclusions about the suitability of each type of sensor and spectral range are drawn in relation to each particular case study and damage. It should be emphasised that results are not limited to images, since 3D intensity data from laser scanners can be integrated with 2D data from passive sensors obtaining high quality products due to the added value that metric brings to multispectral images.

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

Science.gov (United States)

Itoh, Kazuyoshi

2015-12-01

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

Design of a modified endoscope illuminator for spectral imaging of colorectal tissues

Science.gov (United States)

Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

2017-02-01

The gold standard for locating colonic polyps is a white light endoscope in a colonoscopy, however, polyps smaller than 5 mm can be easily missed. Modified procedures such as narrow band imaging have shown only marginal increases in detection rates. Spectral imaging is a potential solution to improve the sensitivity and specificity of colonoscopies by providing the ability to distinguish molecular fluorescence differences in tissues. The goal of this work is to implement a spectral endoscopic light source to acquire spectral image data of colorectal tissues. A beta-version endoscope light source was developed, by retrofitting a white light endoscope light source (Olympus, CLK-4) with 16 narrow band LEDs. This redesigned, beta-prototype uses high-power LEDs with a minimum output of 500 mW to provide sufficient spectral output (0.5 mW) through the endoscope. A mounting apparatus was designed to provide sufficient heat dissipation. Here, we report recent results of our tests to characterize the intensity output through the light source and endoscope to determine the flat spectral output for imaging and intensity losses through the endoscope. We also report preliminary spectral imaging data from transverse pig colon that demonstrates the ability to result in working practical spectral data. Preliminary results of this revised prototype spectral endoscope system demonstrate that there is sufficient power to allow the imaging process to continue and potentially determine spectral differences in cancerous and normal tissue from imaging ex vivo pairs. Future work will focus on building a spectral library for the colorectal region and refining the user interface the system for in vivo use.

A novel and compact spectral imaging system based on two curved prisms

Science.gov (United States)

Nie, Yunfeng; Bin, Xiangli; Zhou, Jinsong; Li, Yang

2013-09-01

As a novel detection approach which simultaneously acquires two-dimensional visual picture and one-dimensional spectral information, spectral imaging offers promising applications on biomedical imaging, conservation and identification of artworks, surveillance of food safety, and so forth. A novel moderate-resolution spectral imaging system consisting of merely two optical elements is illustrated in this paper. It can realize the function of a relay imaging system as well as a 10nm spectral resolution spectroscopy. Compared to conventional prismatic imaging spectrometers, this design is compact and concise with only two special curved prisms by utilizing two reflective surfaces. In contrast to spectral imagers based on diffractive grating, the usage of compound-prism possesses characteristics of higher energy utilization and wider free spectral range. The seidel aberration theory and dispersive principle of this special prism are analyzed at first. According to the results, the optical system of this design is simulated, and the performance evaluation including spot diagram, MTF and distortion, is presented. In the end, considering the difficulty and particularity of manufacture and alignment, an available method for fabrication and measurement is proposed.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

Science.gov (United States)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

Upconversion based spectral imaging in 6 to 8 μm spectral regime

DEFF Research Database (Denmark)

Junaid, Saher; Tidemand-Lichtenberg, Peter; Pedersen, Christian

2017-01-01

Spectral imaging in the 6 to 8μm range has great potential for medical diagnostics. Here a novel technique based on frequency upconversion of the infrared images to the near visible for subsequent acquisition using a Si-CCD camera is investigated. The upconversion unit consists of an AgGaS2 crystal...

Dynamic Post-Earthquake Image Segmentation with an Adaptive Spectral-Spatial Descriptor

Directory of Open Access Journals (Sweden)

Genyun Sun

2017-08-01

Full Text Available The region merging algorithm is a widely used segmentation technique for very high resolution (VHR remote sensing images. However, the segmentation of post-earthquake VHR images is more difficult due to the complexity of these images, especially high intra-class and low inter-class variability among damage objects. Herein two key issues must be resolved: the first is to find an appropriate descriptor to measure the similarity of two adjacent regions since they exhibit high complexity among the diverse damage objects, such as landslides, debris flow, and collapsed buildings. The other is how to solve over-segmentation and under-segmentation problems, which are commonly encountered with conventional merging strategies due to their strong dependence on local information. To tackle these two issues, an adaptive dynamic region merging approach (ADRM is introduced, which combines an adaptive spectral-spatial descriptor and a dynamic merging strategy to adapt to the changes of merging regions for successfully detecting objects scattered globally in a post-earthquake image. In the new descriptor, the spectral similarity and spatial similarity of any two adjacent regions are automatically combined to measure their similarity. Accordingly, the new descriptor offers adaptive semantic descriptions for geo-objects and thus is capable of characterizing different damage objects. Besides, in the dynamic region merging strategy, the adaptive spectral-spatial descriptor is embedded in the defined testing order and combined with graph models to construct a dynamic merging strategy. The new strategy can find the global optimal merging order and ensures that the most similar regions are merged at first. With combination of the two strategies, ADRM can identify spatially scattered objects and alleviates the phenomenon of over-segmentation and under-segmentation. The performance of ADRM has been evaluated by comparing with four state-of-the-art segmentation methods

Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

Science.gov (United States)

Bautista, Pinky A; Yagi, Yukako

2011-01-01

In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes

Directory of Open Access Journals (Sweden)

Dilip K. Prasad

2016-03-01

Full Text Available We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds. The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS, moderate-resolution imaging spectroradiometer (MODIS, sea-viewing wide field-of-view sensor (SeaWiFS, coastal zone color scanner (CZCS, ocean and land colour instrument (OLCI, and visible infrared imaging radiometer suite (VIIRS sensors. Results are also shown for CIMEL’s SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

The Possibility of Passive Whale Tracking With the Use of An Hyperspectral Sensor

National Research Council Canada - National Science Library

Barnes, Christina

1999-01-01

...) Sensor to detect and recognize whales. This paper gives a detailed discussion of the sensor, describes the spectral image processing used to detect and enhance the whale images, provides sample imagery products, and finally discusses...

Detection of Fusarium in single wheat kernels using spectral Imaging

NARCIS (Netherlands)

Polder, G.; Heijden, van der G.W.A.M.; Waalwijk, C.; Young, I.T.

2005-01-01

Fusarium head blight (FHB) is a harmful fungal disease that occurs in small grains. Non-destructive detection of this disease is traditionally done using spectroscopy or image processing. In this paper the combination of these two in the form of spectral imaging is evaluated. Transmission spectral

Micro-digital sun sensor: an imaging sensor for space applications

NARCIS (Netherlands)

Xie, N.; Theuwissen, A.J.P.; Büttgen, B.; Hakkesteegt, H.C.; Jasen, H.; Leijtens, J.A.P.

2010-01-01

Micro-Digital Sun Sensor is an attitude sensor which senses relative position of micro-satellites to the sun in space. It is composed of a solar cell power supply, a RF communication block and an imaging chip which is called APS+. The APS+ integrates a CMOS Active Pixel Sensor (APS) of 512×512

A multi-object spectral imaging instrument

OpenAIRE

Gibson, G.M.; Dienerowitz, M.; Kelleher, P.A.; Harvey, A.R.; Padgett, M.J.

2013-01-01

We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the ...

Estimating Single and Multiple Target Locations Using K-Means Clustering with Radio Tomographic Imaging in Wireless Sensor Networks

Science.gov (United States)

2015-03-26

clustering is an algorithm that has been used in data mining applications such as machine learning applications , pattern recognition, hyper-spectral imagery...42 3.7.2 Application of K-means Clustering . . . . . . . . . . . . . . . . . 42 3.8 Experiment Design...Tomographic Imaging WLAN Wireless Local Area Networks WSN Wireless Sensor Network xx ESTIMATING SINGLE AND MULTIPLE TARGET LOCATIONS USING K-MEANS CLUSTERING

Lossless compression of multispectral images using spectral information

Science.gov (United States)

Ma, Long; Shi, Zelin; Tang, Xusheng

2009-10-01

Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

Spectral differential imaging detection of planets about nearby stars

International Nuclear Information System (INIS)

Smith, W.H.

1987-01-01

Direct ground-based optical imaging of planets in orbit about nearby stars may be accomplished by spectral differential imaging using multiple passband acoustooptic filters with a CCD. This technique provides two essential results. First, it provides a means to modulate the stellar flux reflected from a planet while leaving the flux from the star and other sources in the same field of view unmodulated. Second, spectral differential imaging enables the CCD detector to achieve a sufficiently high dynamic range to locate planets near a star in spite of an integrated brightness differential of 5 x 10 8 . Spectral differential imaging at nearby diffraction limited imaging conditions with telescope apodization can reduce the time to conduct a sensitive planetary search to a few hours in some cases. The feasibility of this idea is discussed here and shown to provide, in principle, the discrimination and sensitivity to detect a Jovian-class planet about stars at distances of about 10 parsecs. The detection of brown dwarfs is shown to be feasible as well. 31 references

Toward CMOS image sensor based glucose monitoring.

Science.gov (United States)

Devadhasan, Jasmine Pramila; Kim, Sanghyo

2012-09-07

Complementary metal oxide semiconductor (CMOS) image sensor is a powerful tool for biosensing applications. In this present study, CMOS image sensor has been exploited for detecting glucose levels by simple photon count variation with high sensitivity. Various concentrations of glucose (100 mg dL(-1) to 1000 mg dL(-1)) were added onto a simple poly-dimethylsiloxane (PDMS) chip and the oxidation of glucose was catalyzed with the aid of an enzymatic reaction. Oxidized glucose produces a brown color with the help of chromogen during enzymatic reaction and the color density varies with the glucose concentration. Photons pass through the PDMS chip with varying color density and hit the sensor surface. Photon count was recognized by CMOS image sensor depending on the color density with respect to the glucose concentration and it was converted into digital form. By correlating the obtained digital results with glucose concentration it is possible to measure a wide range of blood glucose levels with great linearity based on CMOS image sensor and therefore this technique will promote a convenient point-of-care diagnosis.

Computational multispectral video imaging [Invited].

Science.gov (United States)

Wang, Peng; Menon, Rajesh

2018-01-01

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430-718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.

Extended SWIR imaging sensors for hyperspectral imaging applications

Science.gov (United States)

Weber, A.; Benecke, M.; Wendler, J.; Sieck, A.; Hübner, D.; Figgemeier, H.; Breiter, R.

2016-05-01

AIM has developed SWIR modules including FPAs based on liquid phase epitaxy (LPE) grown MCT usable in a wide range of hyperspectral imaging applications. Silicon read-out integrated circuits (ROIC) provide various integration and readout modes including specific functions for spectral imaging applications. An important advantage of MCT based detectors is the tunable band gap. The spectral sensitivity of MCT detectors can be engineered to cover the extended SWIR spectral region up to 2.5μm without compromising in performance. AIM developed the technology to extend the spectral sensitivity of its SWIR modules also into the VIS. This has been successfully demonstrated for 384x288 and 1024x256 FPAs with 24μm pitch. Results are presented in this paper. The FPAs are integrated into compact dewar cooler configurations using different types of coolers, like rotary coolers, AIM's long life split linear cooler MCC030 or extreme long life SF100 Pulse Tube cooler. The SWIR modules include command and control electronics (CCE) which allow easy interfacing using a digital standard interface. The development status and performance results of AIM's latest MCT SWIR modules suitable for hyperspectral systems and applications will be presented.

Establishing imaging sensor specifications for digital still cameras

Science.gov (United States)

Kriss, Michael A.

2007-02-01

Digital Still Cameras, DSCs, have now displaced conventional still cameras in most markets. The heart of a DSC is thought to be the imaging sensor, be it Full Frame CCD, and Interline CCD, a CMOS sensor or the newer Foveon buried photodiode sensors. There is a strong tendency by consumers to consider only the number of mega-pixels in a camera and not to consider the overall performance of the imaging system, including sharpness, artifact control, noise, color reproduction, exposure latitude and dynamic range. This paper will provide a systematic method to characterize the physical requirements of an imaging sensor and supporting system components based on the desired usage. The analysis is based on two software programs that determine the "sharpness", potential for artifacts, sensor "photographic speed", dynamic range and exposure latitude based on the physical nature of the imaging optics, sensor characteristics (including size of pixels, sensor architecture, noise characteristics, surface states that cause dark current, quantum efficiency, effective MTF, and the intrinsic full well capacity in terms of electrons per square centimeter). Examples will be given for consumer, pro-consumer, and professional camera systems. Where possible, these results will be compared to imaging system currently on the market.

Simultaneous live cell imaging using dual FRET sensors with a single excitation light.

Directory of Open Access Journals (Sweden)

Yusuke Niino

Full Text Available Fluorescence resonance energy transfer (FRET between fluorescent proteins is a powerful tool for visualization of signal transduction in living cells, and recently, some strategies for imaging of dual FRET pairs in a single cell have been reported. However, these necessitate alteration of excitation light between two different wavelengths to avoid the spectral overlap, resulting in sequential detection with a lag time. Thus, to follow fast signal dynamics or signal changes in highly motile cells, a single-excitation dual-FRET method should be required. Here we reported this by using four-color imaging with a single excitation light and subsequent linear unmixing to distinguish fluorescent proteins. We constructed new FRET sensors with Sapphire/RFP to combine with CFP/YFP, and accomplished simultaneous imaging of cAMP and cGMP in single cells. We confirmed that signal amplitude of our dual FRET measurement is comparable to of conventional single FRET measurement. Finally, we demonstrated to monitor both intracellular Ca(2+ and cAMP in highly motile cardiac myocytes. To cancel out artifacts caused by the movement of the cell, this method expands the applicability of the combined use of dual FRET sensors for cell samples with high motility.

Fusion of Images from Dissimilar Sensor Systems

National Research Council Canada - National Science Library

Chow, Khin

2004-01-01

Different sensors exploit different regions of the electromagnetic spectrum; therefore a multi-sensor image fusion system can take full advantage of the complementary capabilities of individual sensors in the suit...

Impact of the cameras radiometric resolution on the accuracy of determining spectral reflectance coefficients

Science.gov (United States)

Orych, A.; Walczykowski, P.; Jenerowicz, A.; Zdunek, Z.

2014-11-01

Nowadays remote sensing plays a very important role in many different study fields, i.e. environmental studies, hydrology, mineralogy, ecosystem studies, etc. One of the key areas of remote sensing applications is water quality monitoring. Understanding and monitoring of the water quality parameters and detecting different water contaminants is an important issue in water management and protection of whole environment and especially the water ecosystem. There are many remote sensing methods to monitor water quality and detect water pollutants. One of the most widely used method for substance detection with remote sensing techniques is based on usage of spectral reflectance coefficients. They are usually acquired using discrete methods such as spectrometric measurements. These however can be very time consuming, therefore image-based methods are used more and more often. In order to work out the proper methodology of obtaining spectral reflectance coefficients from hyperspectral and multispectral images, it is necessary to verify the impact of cameras radiometric resolution on the accuracy of determination of them. This paper presents laboratory experiments that were conducted using two monochromatic XEVA video sensors (400-1700 nm spectral data registration) with two different radiometric resolutions (12 and 14 bits). In view of determining spectral characteristics from images, the research team used set of interferometric filters. All data collected with multispectral digital video cameras were compared with spectral reflectance coefficients obtained with spectroradiometer. The objective of this research is to find the impact of cameras radiometric resolution on reflectance values in chosen wavelength. The main topic of this study is the analysis of accuracy of spectral coefficients from sensors with different radiometric resolution. By comparing values collected from images acquired with XEVA sensors and with the curves obtained with spectroradiometer it

Collaborative Image Coding and Transmission over Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Min Wu

2007-01-01

Full Text Available The imaging sensors are able to provide intuitive visual information for quick recognition and decision. However, imaging sensors usually generate vast amount of data. Therefore, processing and coding of image data collected in a sensor network for the purpose of energy efficient transmission poses a significant technical challenge. In particular, multiple sensors may be collecting similar visual information simultaneously. We propose in this paper a novel collaborative image coding and transmission scheme to minimize the energy for data transmission. First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors. For a given image sequence, we transmit background image only once. A lightweight and efficient background subtraction method is employed to detect targets. Only the regions of target and their spatial locations are transmitted to the monitoring center. The whole image can then be reconstructed by fusing the background and the target images as well as their spatial locations. Experimental results show that the energy for image transmission can indeed be greatly reduced with collaborative image coding and transmission.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

Science.gov (United States)

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

GOES-R Advanced Baseline Imager: spectral response functions and radiometric biases with the NPP Visible Infrared Imaging Radiometer Suite evaluated for desert calibration sites.

Science.gov (United States)

Pearlman, Aaron; Pogorzala, David; Cao, Changyong

2013-11-01

The Advanced Baseline Imager (ABI), which will be launched in late 2015 on the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellite R-series satellite, will be evaluated in terms of its data quality postlaunch through comparisons with other satellite sensors such as the recently launched Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership satellite. The ABI has completed much of its prelaunch characterization and its developers have generated and released its channel spectral response functions (response versus wavelength). Using these responses and constraining a radiative transfer model with ground reflectance, aerosol, and water vapor measurements, we simulate observed top of atmosphere (TOA) reflectances for analogous visible and near infrared channels of the VIIRS and ABI sensors at the Sonoran Desert and White Sands National Monument sites and calculate the radiometric biases and their uncertainties. We also calculate sensor TOA reflectances using aircraft hyperspectral data from the Airborne Visible/Infrared Imaging Spectrometer to validate the uncertainties in several of the ABI and VIIRS channels and discuss the potential for validating the others. Once on-orbit, calibration scientists can use these biases to ensure ABI data quality and consistency to support the numerical weather prediction community and other data users. They can also use the results for ABI or VIIRS anomaly detection and resolution.

Applications of cost-effective spectral imaging microscopy in cancer research

International Nuclear Information System (INIS)

Barber, P R; Vojnovic, B; Atkin, G; Daley, F M; Everett, S A; Wilson, G D; Gilbey, J D

2003-01-01

The application of a cost-effective spectral imager to spatially segmenting absorptive and fluorescent chemical probes on the basis of their spectral characteristics has been demonstrated. The imager comprises a computer-controlled spectrally selective element that allows random access to a bandwidth of 15 nm between 400 and 700 nm. Further, the use of linear un-mixing of the spectral response of a sample at a single pixel has been facilitated using non-negative least squares fitting. Examples are given showing the separation of dye distributions, such as immunohistochemical markers for tumour hypoxia, from multiply stained thin tissue sections, imaged by trans-illumination microscopy. A quantitative study is also presented that shows a correlation between staining intensity and normal versus tumour tissue, and the advantage of reducing the amount of data captured for a particular study is also demonstrated. An example of the application to fluorescence microscopy is also given, showing the separation of green fluorescent protein, Cy3 and Cy5 at a single pixel. The system has been validated against samples of known optical density and of known overlapping combinations of coloured filters. These results confirm the ability of this technique to separate spectral responses that cannot be resolved with conventional colour imaging

CMOS Active-Pixel Image Sensor With Intensity-Driven Readout

Science.gov (United States)

Langenbacher, Harry T.; Fossum, Eric R.; Kemeny, Sabrina

1996-01-01

Proposed complementary metal oxide/semiconductor (CMOS) integrated-circuit image sensor automatically provides readouts from pixels in order of decreasing illumination intensity. Sensor operated in integration mode. Particularly useful in number of image-sensing tasks, including diffractive laser range-finding, three-dimensional imaging, event-driven readout of sparse sensor arrays, and star tracking.

Deblurring sequential ocular images from multi-spectral imaging (MSI) via mutual information.

Science.gov (United States)

Lian, Jian; Zheng, Yuanjie; Jiao, Wanzhen; Yan, Fang; Zhao, Bojun

2018-06-01

Multi-spectral imaging (MSI) produces a sequence of spectral images to capture the inner structure of different species, which was recently introduced into ocular disease diagnosis. However, the quality of MSI images can be significantly degraded by motion blur caused by the inevitable saccades and exposure time required for maintaining a sufficiently high signal-to-noise ratio. This degradation may confuse an ophthalmologist, reduce the examination quality, or defeat various image analysis algorithms. We propose an early work specially on deblurring sequential MSI images, which is distinguished from many of the current image deblurring techniques by resolving the blur kernel simultaneously for all the images in an MSI sequence. It is accomplished by incorporating several a priori constraints including the sharpness of the latent clear image, the spatial and temporal smoothness of the blur kernel and the similarity between temporally-neighboring images in MSI sequence. Specifically, we model the similarity between MSI images with mutual information considering the different wavelengths used for capturing different images in MSI sequence. The optimization of the proposed approach is based on a multi-scale framework and stepwise optimization strategy. Experimental results from 22 MSI sequences validate that our approach outperforms several state-of-the-art techniques in natural image deblurring.

Comparison of Background Parenchymal Enhancement at Contrast-enhanced Spectral Mammography and Breast MR Imaging.

Science.gov (United States)

Sogani, Julie; Morris, Elizabeth A; Kaplan, Jennifer B; D'Alessio, Donna; Goldman, Debra; Moskowitz, Chaya S; Jochelson, Maxine S

2017-01-01

Purpose To assess the extent of background parenchymal enhancement (BPE) at contrast material-enhanced (CE) spectral mammography and breast magnetic resonance (MR) imaging, to evaluate interreader agreement in BPE assessment, and to examine the relationships between clinical factors and BPE. Materials and Methods This was a retrospective, institutional review board-approved, HIPAA-compliant study. Two hundred seventy-eight women from 25 to 76 years of age with increased breast cancer risk who underwent CE spectral mammography and MR imaging for screening or staging from 2010 through 2014 were included. Three readers independently rated BPE on CE spectral mammographic and MR images with the ordinal scale: minimal, mild, moderate, or marked. To assess pairwise agreement between BPE levels on CE spectral mammographic and MR images and among readers, weighted κ coefficients with quadratic weights were calculated. For overall agreement, mean κ values and bootstrapped 95% confidence intervals were calculated. The univariate and multivariate associations between BPE and clinical factors were examined by using generalized estimating equations separately for CE spectral mammography and MR imaging. Results Most women had minimal or mild BPE at both CE spectral mammography (68%-76%) and MR imaging (69%-76%). Between CE spectral mammography and MR imaging, the intrareader agreement ranged from moderate to substantial (κ = 0.55-0.67). Overall agreement on BPE levels between CE spectral mammography and MR imaging and among readers was substantial (κ = 0.66; 95% confidence interval: 0.61, 0.70). With both modalities, BPE demonstrated significant association with menopausal status, prior breast radiation therapy, hormonal treatment, breast density on CE spectral mammographic images, and amount of fibroglandular tissue on MR images (P spectral mammographic and MR images. © RSNA, 2016.

Laser-induced fluorescence imaging of subsurface tissue structures with a volume holographic spatial-spectral imaging system.

Science.gov (United States)

Luo, Yuan; Gelsinger-Austin, Paul J; Watson, Jonathan M; Barbastathis, George; Barton, Jennifer K; Kostuk, Raymond K

2008-09-15

A three-dimensional imaging system incorporating multiplexed holographic gratings to visualize fluorescence tissue structures is presented. Holographic gratings formed in volume recording materials such as a phenanthrenquinone poly(methyl methacrylate) photopolymer have narrowband angular and spectral transmittance filtering properties that enable obtaining spatial-spectral information within an object. We demonstrate this imaging system's ability to obtain multiple depth-resolved fluorescence images simultaneously.

Hyperspectral imaging simulation of object under sea-sky background

Science.gov (United States)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

Virtual View Image over Wireless Visual Sensor Network

Directory of Open Access Journals (Sweden)

Gamantyo Hendrantoro

2011-12-01

Full Text Available In general, visual sensors are applied to build virtual view images. When number of visual sensors increases then quantity and quality of the information improves. However, the view images generation is a challenging task in Wireless Visual Sensor Network environment due to energy restriction, computation complexity, and bandwidth limitation. Hence this paper presents a new method of virtual view images generation from selected cameras on Wireless Visual Sensor Network. The aim of the paper is to meet bandwidth and energy limitations without reducing information quality. The experiment results showed that this method could minimize number of transmitted imageries with sufficient information.

Degradation of CMOS image sensors in deep-submicron technology due to γ-irradiation

Science.gov (United States)

Rao, Padmakumar R.; Wang, Xinyang; Theuwissen, Albert J. P.

2008-09-01

In this work, radiation induced damage mechanisms in deep submicron technology is resolved using finger gated-diodes (FGDs) as a radiation sensitive tool. It is found that these structures are simple yet efficient structures to resolve radiation induced damage in advanced CMOS processes. The degradation of the CMOS image sensors in deep-submicron technology due to γ-ray irradiation is studied by developing a model for the spectral response of the sensor and also by the dark-signal degradation as a function of STI (shallow-trench isolation) parameters. It is found that threshold shifts in the gate-oxide/silicon interface as well as minority carrier life-time variations in the silicon bulk are minimal. The top-layer material properties and the photodiode Si-SiO2 interface quality are degraded due to γ-ray irradiation. Results further suggest that p-well passivated structures are inevitable for radiation-hard designs. It was found that high electrical fields in submicron technologies pose a threat to high quality imaging in harsh environments.

A review of spectrally coded multiplexing techniques for fibre grating sensor systems

International Nuclear Information System (INIS)

Childs, Paul; Wong, Allan C L; Yan, Binbin; Li, Mo; Peng, Gang-Ding

2010-01-01

We review recent work and progress on spectrally coded multiplexing (SCM). SCM is a generic multiplexing technique that provides more efficient data usage, additional flexibility and greater channel capability for fibre and fibre grating based sensor systems. We show a few examples of newly developed SCM techniques based on specially designed fibre gratings

Smart CMOS image sensor for lightning detection and imaging.

Science.gov (United States)

Rolando, Sébastien; Goiffon, Vincent; Magnan, Pierre; Corbière, Franck; Molina, Romain; Tulet, Michel; Bréart-de-Boisanger, Michel; Saint-Pé, Olivier; Guiry, Saïprasad; Larnaudie, Franck; Leone, Bruno; Perez-Cuevas, Leticia; Zayer, Igor

2013-03-01

We present a CMOS image sensor dedicated to lightning detection and imaging. The detector has been designed to evaluate the potentiality of an on-chip lightning detection solution based on a smart sensor. This evaluation is performed in the frame of the predevelopment phase of the lightning detector that will be implemented in the Meteosat Third Generation Imager satellite for the European Space Agency. The lightning detection process is performed by a smart detector combining an in-pixel frame-to-frame difference comparison with an adjustable threshold and on-chip digital processing allowing an efficient localization of a faint lightning pulse on the entire large format array at a frequency of 1 kHz. A CMOS prototype sensor with a 256×256 pixel array and a 60 μm pixel pitch has been fabricated using a 0.35 μm 2P 5M technology and tested to validate the selected detection approach.

Robust Dehaze Algorithm for Degraded Image of CMOS Image Sensors

Directory of Open Access Journals (Sweden)

Chen Qu

2017-09-01

Full Text Available The CMOS (Complementary Metal-Oxide-Semiconductor is a new type of solid image sensor device widely used in object tracking, object recognition, intelligent navigation fields, and so on. However, images captured by outdoor CMOS sensor devices are usually affected by suspended atmospheric particles (such as haze, causing a reduction in image contrast, color distortion problems, and so on. In view of this, we propose a novel dehazing approach based on a local consistent Markov random field (MRF framework. The neighboring clique in traditional MRF is extended to the non-neighboring clique, which is defined on local consistent blocks based on two clues, where both the atmospheric light and transmission map satisfy the character of local consistency. In this framework, our model can strengthen the restriction of the whole image while incorporating more sophisticated statistical priors, resulting in more expressive power of modeling, thus, solving inadequate detail recovery effectively and alleviating color distortion. Moreover, the local consistent MRF framework can obtain details while maintaining better results for dehazing, which effectively improves the image quality captured by the CMOS image sensor. Experimental results verified that the method proposed has the combined advantages of detail recovery and color preservation.

Molecular spectral imaging system for quantitative immunohistochemical analysis of early diabetic retinopathy.

Science.gov (United States)

Li, Qingli; Zhang, Jingfa; Wang, Yiting; Xu, Guoteng

2009-12-01

A molecular spectral imaging system has been developed based on microscopy and spectral imaging technology. The system is capable of acquiring molecular spectral images from 400 nm to 800 nm with 2 nm wavelength increments. The basic principles, instrumental systems, and system calibration method as well as its applications for the calculation of the stain-uptake by tissues are introduced. As a case study, the system is used for determining the pathogenesis of diabetic retinopathy and evaluating the therapeutic effects of erythropoietin. Some molecular spectral images of retinal sections of normal, diabetic, and treated rats were collected and analyzed. The typical transmittance curves of positive spots stained for albumin and advanced glycation end products are retrieved from molecular spectral data with the spectral response calibration algorithm. To explore and evaluate the protective effect of erythropoietin (EPO) on retinal albumin leakage of streptozotocin-induced diabetic rats, an algorithm based on Beer-Lambert's law is presented. The algorithm can assess the uptake by histologic retinal sections of stains used in quantitative pathology to label albumin leakage and advanced glycation end products formation. Experimental results show that the system is helpful for the ophthalmologist to reveal the pathogenesis of diabetic retinopathy and explore the protective effect of erythropoietin on retinal cells of diabetic rats. It also highlights the potential of molecular spectral imaging technology to provide more effective and reliable diagnostic criteria in pathology.

The high throughput virtual slit enables compact, inexpensive Raman spectral imagers

Science.gov (United States)

Gooding, Edward; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

2018-02-01

Raman spectral imaging is increasingly becoming the tool of choice for field-based applications such as threat, narcotics and hazmat detection; air, soil and water quality monitoring; and material ID. Conventional fiber-coupled point source Raman spectrometers effectively interrogate a small sample area and identify bulk samples via spectral library matching. However, these devices are very slow at mapping over macroscopic areas. In addition, the spatial averaging performed by instruments that collect binned spectra, particularly when used in combination with orbital raster scanning, tends to dilute the spectra of trace particles in a mixture. Our design, employing free space line illumination combined with area imaging, reveals both the spectral and spatial content of heterogeneous mixtures. This approach is well suited to applications such as detecting explosives and narcotics trace particle detection in fingerprints. The patented High Throughput Virtual Slit1 is an innovative optical design that enables compact, inexpensive handheld Raman spectral imagers. HTVS-based instruments achieve significantly higher spectral resolution than can be obtained with conventional designs of the same size. Alternatively, they can be used to build instruments with comparable resolution to large spectrometers, but substantially smaller size, weight and unit cost, all while maintaining high sensitivity. When used in combination with laser line imaging, this design eliminates sample photobleaching and unwanted photochemistry while greatly enhancing mapping speed, all with high selectivity and sensitivity. We will present spectral image data and discuss applications that are made possible by low cost HTVS-enabled instruments.

Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

Directory of Open Access Journals (Sweden)

Myung-Ho Ju

2013-10-01

Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin

NARCIS (Netherlands)

Fereidouni, F.; Bader, A.N.; Colonna, A.; Gerritsen, H.C.

2014-01-01

Skin contains many autofluorescent components that can be studied using spectral imaging. We employed a spectral phasor method to analyse two photon excited auto-fluorescence and second harmonic generation images of in vivo human skin. This method allows segmentation of images based on spectral

Contact CMOS imaging of gaseous oxygen sensor array.

Science.gov (United States)

Daivasagaya, Daisy S; Yao, Lei; Yi Yung, Ka; Hajj-Hassan, Mohamad; Cheung, Maurice C; Chodavarapu, Vamsy P; Bright, Frank V

2011-10-01

We describe a compact luminescent gaseous oxygen (O 2 ) sensor microsystem based on the direct integration of sensor elements with a polymeric optical filter and placed on a low power complementary metal-oxide semiconductor (CMOS) imager integrated circuit (IC). The sensor operates on the measurement of excited-state emission intensity of O 2 -sensitive luminophore molecules tris(4,7-diphenyl-1,10-phenanthroline) ruthenium(II) ([Ru(dpp) 3 ] 2+ ) encapsulated within sol-gel derived xerogel thin films. The polymeric optical filter is made with polydimethylsiloxane (PDMS) that is mixed with a dye (Sudan-II). The PDMS membrane surface is molded to incorporate arrays of trapezoidal microstructures that serve to focus the optical sensor signals on to the imager pixels. The molded PDMS membrane is then attached with the PDMS color filter. The xerogel sensor arrays are contact printed on top of the PDMS trapezoidal lens-like microstructures. The CMOS imager uses a 32 × 32 (1024 elements) array of active pixel sensors and each pixel includes a high-gain phototransistor to convert the detected optical signals into electrical currents. Correlated double sampling circuit, pixel address, digital control and signal integration circuits are also implemented on-chip. The CMOS imager data is read out as a serial coded signal. The CMOS imager consumes a static power of 320 µW and an average dynamic power of 625 µW when operating at 100 Hz sampling frequency and 1.8 V DC. This CMOS sensor system provides a useful platform for the development of miniaturized optical chemical gas sensors.

Multi-sensor image fusion and its applications

CERN Document Server

Blum, Rick S

2005-01-01

Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies.After a review of state-of-the-art image fusion techniques,

[An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

Science.gov (United States)

Xu, Yonghong; Gao, Shangce; Hao, Xiaofei

2016-04-01

Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

Science.gov (United States)

Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

2017-09-01

Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

A spectral profile multiplexed FBG sensor network with application to strain measurement in a Kevlar woven fabric

Science.gov (United States)

Guo, Guodong; Hackney, Drew; Pankow, Mark; Peters, Kara

2017-04-01

A spectral profile division multiplexed fiber Bragg grating (FBG) sensor network is described in this paper. The unique spectral profile of each sensor in the network is identified as a distinct feature to be interrogated. Spectrum overlap is allowed under working conditions. Thus, a specific wavelength window does not need to be allocated to each sensor as in a wavelength division multiplexed (WDM) network. When the sensors are serially connected in the network, the spectrum output is expressed through a truncated series. To track the wavelength shift of each sensor, the identification problem is transformed to a nonlinear optimization problem, which is then solved by a modified dynamic multi-swarm particle swarm optimizer (DMS-PSO). To demonstrate the application of the developed network, a network consisting of four FBGs was integrated into a Kevlar woven fabric, which was under a quasi-static load imposed by an impactor head. Due to the substantial radial strain in the fabric, the spectrums of different FBGs were found to overlap during the loading process. With the developed interrogating method, the overlapped spectrum would be distinguished thus the wavelength shift of each sensor can be monitored.

The spectral combination characteristic of grating and the bi-grating diffraction imaging effect

Institute of Scientific and Technical Information of China (English)

2007-01-01

This paper reports on a new property of grating, namely spectral combination, and on bi-grating diffraction imaging that is based on spectral combination. The spectral combination characteristic of a grating is the capability of combining multiple light beams of different wavelengths incident from specific angles into a single beam. The bi-grating diffraction imaging is the formation of the image of an object with two gratings: the first grating disperses the multi-color light beams from the object and the second combines the dispersed light beams to form the image. We gave the conditions necessary for obtaining the spectral combination. We also presented the equations that relate the two gratings’ spatial frequencies, diffraction orders and positions necessary for obtaining the bi-grating diffraction imaging.

Tissues segmentation based on multi spectral medical images

Science.gov (United States)

Li, Ya; Wang, Ying

2017-11-01

Each band image contains the most obvious tissue feature according to the optical characteristics of different tissues in different specific bands for multispectral medical images. In this paper, the tissues were segmented by their spectral information at each multispectral medical images. Four Local Binary Patter descriptors were constructed to extract blood vessels based on the gray difference between the blood vessels and their neighbors. The segmented tissue in each band image was merged to a clear image.

Fully wireless pressure sensor based on endoscopy images

Science.gov (United States)

Maeda, Yusaku; Mori, Hirohito; Nakagawa, Tomoaki; Takao, Hidekuni

2018-04-01

In this paper, the result of developing a fully wireless pressure sensor based on endoscopy images for an endoscopic surgery is reported for the first time. The sensor device has structural color with a nm-scale narrow gap, and the gap is changed by air pressure. The structural color of the sensor is acquired from camera images. Pressure detection can be realized with existing endoscope configurations only. The inner air pressure of the human body should be measured under flexible-endoscope operation using the sensor. Air pressure monitoring, has two important purposes. The first is to quantitatively measure tumor size under a constant air pressure for treatment selection. The second purpose is to prevent the endangerment of a patient due to over transmission of air. The developed sensor was evaluated, and the detection principle based on only endoscopy images has been successfully demonstrated.

Multi-spectral Image Analysis for Astaxanthin Coating Classification

DEFF Research Database (Denmark)

Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

2011-01-01

Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

3D-LSI technology for image sensor

International Nuclear Information System (INIS)

Motoyoshi, Makoto; Koyanagi, Mitsumasa

2009-01-01

Recently, the development of three-dimensional large-scale integration (3D-LSI) technologies has accelerated and has advanced from the research level or the limited production level to the investigation level, which might lead to mass production. By separating 3D-LSI technology into elementary technologies such as (1) through silicon via (TSV) formation, (2) bump formation, (3) wafer thinning, (4) chip/wafer alignment, and (5) chip/wafer stacking and reconstructing the entire process and structure, many methods to realize 3D-LSI devices can be developed. However, by considering a specific application, the supply chain of base wafers, and the purpose of 3D integration, a few suitable combinations can be identified. In this paper, we focus on the application of 3D-LSI technologies to image sensors. We describe the process and structure of the chip size package (CSP), developed on the basis of current and advanced 3D-LSI technologies, to be used in CMOS image sensors. Using the current LSI technologies, CSPs for 1.3 M, 2 M, and 5 M pixel CMOS image sensors were successfully fabricated without any performance degradation. 3D-LSI devices can be potentially employed in high-performance focal-plane-array image sensors. We propose a high-speed image sensor with an optical fill factor of 100% to be developed using next-generation 3D-LSI technology and fabricated using micro(μ)-bumps and micro(μ)-TSVs.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

Science.gov (United States)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

Image acquisition system using on sensor compressed sampling technique

Science.gov (United States)

Gupta, Pravir Singh; Choi, Gwan Seong

2018-01-01

Advances in CMOS technology have made high-resolution image sensors possible. These image sensors pose significant challenges in terms of the amount of raw data generated, energy efficiency, and frame rate. This paper presents a design methodology for an imaging system and a simplified image sensor pixel design to be used in the system so that the compressed sensing (CS) technique can be implemented easily at the sensor level. This results in significant energy savings as it not only cuts the raw data rate but also reduces transistor count per pixel; decreases pixel size; increases fill factor; simplifies analog-to-digital converter, JPEG encoder, and JPEG decoder design; decreases wiring; and reduces the decoder size by half. Thus, CS has the potential to increase the resolution of image sensors for a given technology and die size while significantly decreasing the power consumption and design complexity. We show that it has potential to reduce power consumption by about 23% to 65%.

Quantitative functional optical imaging of the human skin using multi-spectral imaging

International Nuclear Information System (INIS)

Kainerstorfer, J. M.

2010-01-01

Light tissue interactions can be described by the physical principles of absorption and scattering. Based on those parameters, different tissue types and analytes can be distinguished. Extracting blood volume and oxygenation is of particular interest in clinical routines for tumor diagnostics and treatment follow up, since they are parameters of angiogenic processes. The quantification of those analytes in tissue can be done by physical modeling of light tissue interaction. The physical model used here is the random walk theory. However, for quantification and clinical usefulness, one has to account for multiple challenges. First, one must consider the effect of topology of the sample on measured physical parameters. Second, diffusion of light inside the tissue is dependent on the structure of the sample imaged. Thus, the structural conformation has to be taken into account. Third, clinical translation of imaging modalities is often hindered due to the complicated post-processing of data, not providing results in real-time. In this thesis, two imaging modalities are being utilized, where the first one, diffuse multi-spectral imaging, is based on absorption contrast and spectral characteristics and the second one, Optical Coherence Tomography (OCT), is based on scattering changes within the tissue. Multi-spectral imaging can provide spatial distributions of blood volume and blood oxygenation and OCT yields 3D structural images with micrometer resolution. In order to address the challenges mentioned above, a curvature correction algorithm for taking the topology into account was developed. Without taking curvature of the object into account, reconstruction of optical properties is not accurate. The method developed removes this artifact and recovers the underlying data, without the necessity of measuring the object's shape. The next step was to recover blood volume and oxygenation values in real time. Principal Component Analysis (PCA) on multi spectral images is

Hyper-Spectral Imager in visible and near-infrared band for lunar ...

Indian Academy of Sciences (India)

India's first lunar mission, Chandrayaan-1, will have a Hyper-Spectral Imager in the visible and near-infrared spectral ... mapping of the Moon's crust in a large number of spectral channels. The planned .... In-flight verification may be done.

Superpixel segmentation and pigment identification of colored relics based on visible spectral image

Science.gov (United States)

Li, Junfeng; Wan, Xiaoxia

2018-01-01

To enrich the contents of digital archive and to guide the copy and restoration of colored relics, non-invasive methods for extraction of painting boundary and identification of pigment composition are proposed in this study based on the visible spectral images of colored relics. Superpixel concept is applied for the first time to the field of oversegmentation of visible spectral images and implemented on the visible spectral images of colored relics to extract their painting boundary. Since different pigments are characterized by their own spectrum and the same kind of pigment has the similar geometric profile in spectrum, an automatic identification method is established by comparing the proximity between the geometric profiles of the unknown spectrum from each superpixel and the pre-known spectrum from a deliberately prepared database. The methods are validated using the visible spectral images of the ancient wall paintings in Mogao Grottoes. By the way, the visible spectral images are captured by a multispectral imaging system consisting of two broadband filters and a RGB camera with high spatial resolution.

CMOS sensors for atmospheric imaging

Science.gov (United States)

Pratlong, Jérôme; Burt, David; Jerram, Paul; Mayer, Frédéric; Walker, Andrew; Simpson, Robert; Johnson, Steven; Hubbard, Wendy

2017-09-01

Recent European atmospheric imaging missions have seen a move towards the use of CMOS sensors for the visible and NIR parts of the spectrum. These applications have particular challenges that are completely different to those that have driven the development of commercial sensors for applications such as cell-phone or SLR cameras. This paper will cover the design and performance of general-purpose image sensors that are to be used in the MTG (Meteosat Third Generation) and MetImage satellites and the technology challenges that they have presented. We will discuss how CMOS imagers have been designed with 4T pixel sizes of up to 250 μm square achieving good charge transfer efficiency, or low lag, with signal levels up to 2M electrons and with high line rates. In both devices a low noise analogue read-out chain is used with correlated double sampling to suppress the readout noise and give a maximum dynamic range that is significantly larger than in standard commercial devices. Radiation hardness is a particular challenge for CMOS detectors and both of these sensors have been designed to be fully radiation hard with high latch-up and single-event-upset tolerances, which is now silicon proven on MTG. We will also cover the impact of ionising radiation on these devices. Because with such large pixels the photodiodes have a large open area, front illumination technology is sufficient to meet the detection efficiency requirements but with thicker than standard epitaxial silicon to give improved IR response (note that this makes latch up protection even more important). However with narrow band illumination reflections from the front and back of the dielectric stack on the top of the sensor produce Fabry-Perot étalon effects, which have been minimised with process modifications. We will also cover the addition of precision narrow band filters inside the MTG package to provide a complete imaging subsystem. Control of reflected light is also critical in obtaining the

Innovative monolithic detector for tri-spectral (THz, IR, Vis) imaging

Science.gov (United States)

Pocas, S.; Perenzoni, M.; Massari, N.; Simoens, F.; Meilhan, J.; Rabaud, W.; Martin, S.; Delplanque, B.; Imperinetti, P.; Goudon, V.; Vialle, C.; Arnaud, A.

2012-10-01

Fusion of multispectral images has been explored for many years for security and used in a number of commercial products. CEA-Leti and FBK have developed an innovative sensor technology that gathers monolithically on a unique focal plane arrays, pixels sensitive to radiation in three spectral ranges that are terahertz (THz), infrared (IR) and visible. This technology benefits of many assets for volume market: compactness, full CMOS compatibility on 200mm wafers, advanced functions of the CMOS read-out integrated circuit (ROIC), and operation at room temperature. The ROIC houses visible APS diodes while IR and THz detections are carried out by microbolometers collectively processed above the CMOS substrate. Standard IR bolometric microbridges (160x160 pixels) are surrounding antenna-coupled bolometers (32X32 pixels) built on a resonant cavity customized to THz sensing. This paper presents the different technological challenges achieved in this development and first electrical and sensitivity experimental tests.

A Wildlife Monitoring System Based on Wireless Image Sensor Networks

Directory of Open Access Journals (Sweden)

Junguo Zhang

2014-10-01

Full Text Available Survival and development of wildlife sustains the balance and stability of the entire ecosystem. Wildlife monitoring can provide lots of information such as wildlife species, quantity, habits, quality of life and habitat conditions, to help researchers grasp the status and dynamics of wildlife resources, and to provide basis for the effective protection, sustainable use, and scientific management of wildlife resources. Wildlife monitoring is the foundation of wildlife protection and management. Wireless Sensor Networks (WSN technology has become the most popular technology in the field of information. With advance of the CMOS image sensor technology, wireless sensor networks combined with image sensors, namely Wireless Image Sensor Networks (WISN technology, has emerged as an alternative in monitoring applications. Monitoring wildlife is one of its most promising applications. In this paper, system architecture of the wildlife monitoring system based on the wireless image sensor networks was presented to overcome the shortcomings of the traditional monitoring methods. Specifically, some key issues including design of wireless image sensor nodes and software process design have been studied and presented. A self-powered rotatable wireless infrared image sensor node based on ARM and an aggregation node designed for large amounts of data were developed. In addition, their corresponding software was designed. The proposed system is able to monitor wildlife accurately, automatically, and remotely in all-weather condition, which lays foundations for applications of wireless image sensor networks in wildlife monitoring.

Spectral autofluorescence imaging of the retina for drusen detection

Science.gov (United States)

Foubister, James J.; Gorman, Alistair; Harvey, Andy; Hemert, Jano van

2018-02-01

The presence and characteristics of drusen in retinal images, namely their size, location, and distribution, can be used to aid in the diagnosis and monitoring of Age Related Macular Degeneration (AMD); one of the leading causes for blindness in the elderly population. Current imaging techniques are effective at determining the presence and number of drusen, but fail when it comes to classifying their size and form. These distinctions are important for correctly characterising the disease, especially in the early stages where the development of just one larger drusen can indicate progression. Another challenge for automated detection is in distinguishing them from other retinal features, such as cotton wool spots. We describe the development of a multi-spectral scanning-laser ophthalmoscope that records images of retinal autofluorescence (AF) in four spectral bands. This will offer the potential to detect drusen with improved contrast based on spectral discrimination for automated classification. The resulting improved specificity and sensitivity for their detection offers more reliable characterisation of AMD. We present proof of principle images prior to further system optimisation and clinical trials for assessment of enhanced detection of drusen.

Specialized Color Targets for Spectral Reflectance Reconstruction of Magnified Images

Science.gov (United States)

Kruschwitz, Jennifer D. T.

Digital images are used almost exclusively instead of film to capture visual information across many scientific fields. The colorimetric color representation within these digital images can be relayed from the digital counts produced by the camera with the use of a known color target. In image capture of magnified images, there is currently no reliable color target that can be used at multiple magnifications and give the user a solid understanding of the color ground truth within those images. The first part of this dissertation included the design, fabrication, and testing of a color target produced with optical interference coated microlenses for use in an off-axis illumination, compound microscope. An ideal target was designed to increase the color gamut for colorimetric imaging and provide the necessary "Block Dye" spectral reflectance profiles across the visible spectrum to reduce the number of color patches necessary for multiple filter imaging systems that rely on statistical models for spectral reflectance reconstruction. There are other scientific disciplines that can benefit from a specialized color target to determine the color ground truth in their magnified images and perform spectral estimation. Not every discipline has the luxury of having a multi-filter imaging system. The second part of this dissertation developed two unique ways of using an interference coated color mirror target: one that relies on multiple light-source angles, and one that leverages a dynamic color change with time. The source multi-angle technique would be used for the microelectronic discipline where the reconstructed spectral reflectance would be used to determine a dielectric film thickness on a silicon substrate, and the time varying technique would be used for a biomedical example to determine the thickness of human tear film.

Imaging spectroscopy using embedded diffractive optical arrays

Science.gov (United States)

Hinnrichs, Michele; Hinnrichs, Bradford

2017-09-01

Pacific Advanced Technology (PAT) has developed an infrared hyperspectral camera based on diffractive optic arrays. This approach to hyperspectral imaging has been demonstrated in all three infrared bands SWIR, MWIR and LWIR. The hyperspectral optical system has been integrated into the cold-shield of the sensor enabling the small size and weight of this infrared hyperspectral sensor. This new and innovative approach to an infrared hyperspectral imaging spectrometer uses micro-optics that are made up of an area array of diffractive optical elements where each element is tuned to image a different spectral region on a common focal plane array. The lenslet array is embedded in the cold-shield of the sensor and actuated with a miniature piezo-electric motor. This approach enables rapid infrared spectral imaging with multiple spectral images collected and processed simultaneously each frame of the camera. This paper will present our optical mechanical design approach which results in an infrared hyper-spectral imaging system that is small enough for a payload on a small satellite, mini-UAV, commercial quadcopter or man portable. Also, an application of how this spectral imaging technology can easily be used to quantify the mass and volume flow rates of hydrocarbon gases. The diffractive optical elements used in the lenslet array are blazed gratings where each lenslet is tuned for a different spectral bandpass. The lenslets are configured in an area array placed a few millimeters above the focal plane and embedded in the cold-shield to reduce the background signal normally associated with the optics. The detector array is divided into sub-images covered by each lenslet. We have developed various systems using a different number of lenslets in the area array. Depending on the size of the focal plane and the diameter of the lenslet array will determine the number of simultaneous different spectral images collected each frame of the camera. A 2 x 2 lenslet array will image

Cloud-based processing of multi-spectral imaging data

Science.gov (United States)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

The Fresnel Zone Light Field Spectral Imager

Science.gov (United States)

2017-03-23

detection efficiency for weak signals . Additionally, further study should be done on spectral calibration methods for a FZLFSI. When dealing with weak ... detection assembly. The different image formation planes for each wavelength are constructed synthetically through processing the collected light ...a single micro-lens image. This character- istic also holds for wavelengths other than the design wavelength. 36 modified light field PSF is detected

Room temperature mid-IR single photon spectral imaging

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

2012-01-01

Spectral imaging and detection of mid-infrared (mid-IR) wavelengths are emerging as an enabling technology of great technical and scientific interest; primarily because important chemical compounds display unique and strong mid-IR spectral fingerprints revealing valuable chemical information. Whi...... 20 % for polarized incoherent light at 3 \\mum. The proposed method is relevant for existing and new mid-IR applications like gas analysis and medical diagnostics....

A time-resolved image sensor for tubeless streak cameras

Science.gov (United States)

Yasutomi, Keita; Han, SangMan; Seo, Min-Woong; Takasawa, Taishi; Kagawa, Keiichiro; Kawahito, Shoji

2014-03-01

This paper presents a time-resolved CMOS image sensor with draining-only modulation (DOM) pixels for tube-less streak cameras. Although the conventional streak camera has high time resolution, the device requires high voltage and bulky system due to the structure with a vacuum tube. The proposed time-resolved imager with a simple optics realize a streak camera without any vacuum tubes. The proposed image sensor has DOM pixels, a delay-based pulse generator, and a readout circuitry. The delay-based pulse generator in combination with an in-pixel logic allows us to create and to provide a short gating clock to the pixel array. A prototype time-resolved CMOS image sensor with the proposed pixel is designed and implemented using 0.11um CMOS image sensor technology. The image array has 30(Vertical) x 128(Memory length) pixels with the pixel pitch of 22.4um. .

Spectral Properties of Homogeneous and Nonhomogeneous Radar Images

DEFF Research Database (Denmark)

Madsen, Søren Nørvang

1987-01-01

On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown that the sp......On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown...... that the spectrum of the intensityimage is in general related to the radar scene spectrum by a linearintegral equation, a Fredholm's integral equation of the third kind.Under simplifying assumptions, a closed-form equation giving theradar scene spectrum as a function of the SAR image spectrum canbe derived....

Interpretation of archaeological small-scale features in spectral images

DEFF Research Database (Denmark)

Grøn, Ole; Palmer, Susanna; Stylegar, Frans-Arne

2011-01-01

The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern-recognition are......The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern...

Endoscopic hyperspectral imaging: light guide optimization for spectral light source

Science.gov (United States)

Browning, Craig M.; Mayes, Samuel; Rich, Thomas C.; Leavesley, Silas J.

2018-02-01

Hyperspectral imaging (HSI) is a technology used in remote sensing, food processing and documentation recovery. Recently, this approach has been applied in the medical field to spectrally interrogate regions of interest within respective substrates. In spectral imaging, a two (spatial) dimensional image is collected, at many different (spectral) wavelengths, to sample spectral signatures from different regions and/or components within a sample. Here, we report on the use of hyperspectral imaging for endoscopic applications. Colorectal cancer is the 3rd leading cancer for incidences and deaths in the US. One factor of severity is the miss rate of precancerous/flat lesions ( 65% accuracy). Integrating HSI into colonoscopy procedures could minimize misdiagnosis and unnecessary resections. We have previously reported a working prototype light source with 16 high-powered light emitting diodes (LEDs) capable of high speed cycling and imaging. In recent testing, we have found our current prototype is limited by transmission loss ( 99%) through the multi-furcated solid light guide (lightpipe) and the desired framerate (20-30 fps) could not be achieved. Here, we report on a series of experimental and modeling studies to better optimize the lightpipe and the spectral endoscopy system as a whole. The lightpipe was experimentally evaluated using an integrating sphere and spectrometer (Ocean Optics). Modeling the lightpipe was performed using Monte Carlo optical ray tracing in TracePro (Lambda Research Corp.). Results of these optimization studies will aid in manufacturing a revised prototype with the newly designed light guide and increased sensitivity. Once the desired optical output (5-10 mW) is achieved then the HIS endoscope system will be able to be implemented without adding onto the procedure time.

Classification of Pansharpened Urban Satellite Images

DEFF Research Database (Denmark)

Palsson, Frosti; Sveinsson, Johannes R.; Benediktsson, Jon Atli

2012-01-01

The classification of high resolution urban remote sensing imagery is addressed with the focus on classification of imagery that has been pansharpened by a number of different pansharpening methods. The pansharpening process introduces some spectral and spatial distortions in the resulting fused...... multispectral image, the amount of which highly varies depending on which pansharpening technique is used. In the majority of the pansharpening techniques that have been proposed, there is a compromise between the spatial enhancement and the spectral consistency. Here we study the effects of the spectral...... information from the panchromatic data. Random Forests (RF) and Support Vector Machines (SVM) will be used as classifiers. Experiments are done for three different datasets that have been obtained by two different imaging sensors, IKONOS and QuickBird. These sensors deliver multispectral images that have four...

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

Science.gov (United States)

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

International Nuclear Information System (INIS)

Chen, Q G; Xu, Y; Zhu, H H; Chen, H; Lin, B

2015-01-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565–750 nm. The spectral parameter, defined as the ratio of wavebands at 565–750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66–1.06, 1.06–1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems. (paper)

Self-Similarity Superresolution for Resource-Constrained Image Sensor Node in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Yuehai Wang

2014-01-01

Full Text Available Wireless sensor networks, in combination with image sensors, open up a grand sensing application field. It is a challenging problem to recover a high resolution (HR image from its low resolution (LR counterpart, especially for low-cost resource-constrained image sensors with limited resolution. Sparse representation-based techniques have been developed recently and increasingly to solve this ill-posed inverse problem. Most of these solutions are based on an external dictionary learned from huge image gallery, consequently needing tremendous iteration and long time to match. In this paper, we explore the self-similarity inside the image itself, and propose a new combined self-similarity superresolution (SR solution, with low computation cost and high recover performance. In the self-similarity image super resolution model (SSIR, a small size sparse dictionary is learned from the image itself by the methods such as KSVD. The most similar patch is searched and specially combined during the sparse regulation iteration. Detailed information, such as edge sharpness, is preserved more faithfully and clearly. Experiment results confirm the effectiveness and efficiency of this double self-learning method in the image super resolution.

Evolution of miniature detectors and focal plane arrays for infrared sensors

Science.gov (United States)

Watts, Louis A.

1993-06-01

Sensors that are sensitive in the infrared spectral region have been under continuous development since the WW2 era. A quest for the military advantage of 'seeing in the dark' has pushed thermal imaging technology toward high spatial and temporal resolution for night vision equipment, fire control, search track, and seeker 'homing' guidance sensing devices. Similarly, scientific applications have pushed spectral resolution for chemical analysis, remote sensing of earth resources, and astronomical exploration applications. As a result of these developments, focal plane arrays (FPA) are now available with sufficient sensitivity for both high spatial and narrow bandwidth spectral resolution imaging over large fields of view. Such devices combined with emerging opto-electronic developments in integrated FPA data processing techniques can yield miniature sensors capable of imaging reflected sunlight in the near IR and emitted thermal energy in the Mid-wave (MWIR) and longwave (LWIR) IR spectral regions. Robotic space sensors equipped with advanced versions of these FPA's will provide high resolution 'pictures' of their surroundings, perform remote analysis of solid, liquid, and gas matter, or selectively look for 'signatures' of specific objects. Evolutionary trends and projections of future low power micro detector FPA developments for day/night operation or use in adverse viewing conditions are presented in the following test.

Inductive Sensor Performance in Partial Discharges and Noise Separation by Means of Spectral Power Ratios

Directory of Open Access Journals (Sweden)

Jorge Alfredo Ardila-Rey

2014-02-01

Full Text Available Partial discharge (PD detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

Science.gov (United States)

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

High-speed imaging using CMOS image sensor with quasi pixel-wise exposure

Science.gov (United States)

Sonoda, T.; Nagahara, H.; Endo, K.; Sugiyama, Y.; Taniguchi, R.

2017-02-01

Several recent studies in compressive video sensing have realized scene capture beyond the fundamental trade-off limit between spatial resolution and temporal resolution using random space-time sampling. However, most of these studies showed results for higher frame rate video that were produced by simulation experiments or using an optically simulated random sampling camera, because there are currently no commercially available image sensors with random exposure or sampling capabilities. We fabricated a prototype complementary metal oxide semiconductor (CMOS) image sensor with quasi pixel-wise exposure timing that can realize nonuniform space-time sampling. The prototype sensor can reset exposures independently by columns and fix these amount of exposure by rows for each 8x8 pixel block. This CMOS sensor is not fully controllable via the pixels, and has line-dependent controls, but it offers flexibility when compared with regular CMOS or charge-coupled device sensors with global or rolling shutters. We propose a method to realize pseudo-random sampling for high-speed video acquisition that uses the flexibility of the CMOS sensor. We reconstruct the high-speed video sequence from the images produced by pseudo-random sampling using an over-complete dictionary.

Signal-to-noise analysis of a birefringent spectral zooming imaging spectrometer

Science.gov (United States)

Li, Jie; Zhang, Xiaotong; Wu, Haiying; Qi, Chun

2018-05-01

Study of signal-to-noise ratio (SNR) of a novel spectral zooming imaging spectrometer (SZIS) based on two identical Wollaston prisms is conducted. According to the theory of radiometry and Fourier transform spectroscopy, we deduce the theoretical equations of SNR of SZIS in spectral domain with consideration of the incident wavelength and the adjustable spectral resolution. An example calculation of SNR of SZIS is performed over 400-1000 nm. The calculation results indicate that SNR with different spectral resolutions of SZIS can be optionally selected by changing the spacing between the two identical Wollaston prisms. This will provide theoretical basis for the design, development and engineering of the developed imaging spectrometer for broad spectrum and SNR requirements.

Spectral analysis of mammographic images using a multitaper method

International Nuclear Information System (INIS)

Wu Gang; Mainprize, James G.; Yaffe, Martin J.

2012-01-01

Purpose: Power spectral analysis in radiographic images is conventionally performed using a windowed overlapping averaging periodogram. This study describes an alternative approach using a multitaper technique and compares its performance with that of the standard method. This tool will be valuable in power spectrum estimation of images, whose content deviates significantly from uniform white noise. The performance of the multitaper approach will be evaluated in terms of spectral stability, variance reduction, bias, and frequency precision. The ultimate goal is the development of a useful tool for image quality assurance. Methods: A multitaper approach uses successive data windows of increasing order. This mitigates spectral leakage allowing one to calculate a reduced-variance power spectrum. The multitaper approach will be compared with the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom, NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems, and the estimation of the anatomic noise in mammographic images (simulated images and clinical mammograms). Results: Examination of spectrum variance versus frequency resolution and bias indicates that the multitaper approach is superior to the conventional single taper methods in the prevention of spectrum leakage and variance reduction. More than four times finer frequency precision can be achieved with equivalent or less variance and bias. Conclusions: Without any shortening of the image data length, the bias is smaller and the frequency resolution is higher with the multitaper method, and the need to compromise in the choice of regions of interest size to balance between the reduction of variance and the loss of frequency resolution is largely eliminated.

Thermoelectric infrared imaging sensors for automotive applications

Science.gov (United States)

Hirota, Masaki; Nakajima, Yasushi; Saito, Masanori; Satou, Fuminori; Uchiyama, Makoto

2004-07-01

This paper describes three low-cost thermoelectric infrared imaging sensors having a 1,536, 2,304, and 10,800 element thermoelectric focal plane array (FPA) respectively and two experimental automotive application systems. The FPAs are basically fabricated with a conventional IC process and micromachining technologies and have a low cost potential. Among these sensors, the sensor having 2,304 elements provide high responsivity of 5,500 V/W and a very small size with adopting a vacuum-sealed package integrated with a wide-angle ZnS lens. One experimental system incorporated in the Nissan ASV-2 is a blind spot pedestrian warning system that employs four infrared imaging sensors. This system helps alert the driver to the presence of a pedestrian in a blind spot by detecting the infrared radiation emitted from the person"s body. The system can also prevent the vehicle from moving in the direction of the pedestrian. The other is a rearview camera system with an infrared detection function. This system consists of a visible camera and infrared sensors, and it helps alert the driver to the presence of a pedestrian in a rear blind spot. Various issues that will need to be addressed in order to expand the automotive applications of IR imaging sensors in the future are also summarized. This performance is suitable for consumer electronics as well as automotive applications.

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

Directory of Open Access Journals (Sweden)

Ying Cai

2012-09-01

Full Text Available In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT, the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3% and overall (92.0%–93.1% accuracies. Our

CMOS image sensor-based immunodetection by refractive-index change.

Science.gov (United States)

Devadhasan, Jasmine P; Kim, Sanghyo

2012-01-01

A complementary metal oxide semiconductor (CMOS) image sensor is an intriguing technology for the development of a novel biosensor. Indeed, the CMOS image sensor mechanism concerning the detection of the antigen-antibody (Ag-Ab) interaction at the nanoscale has been ambiguous so far. To understand the mechanism, more extensive research has been necessary to achieve point-of-care diagnostic devices. This research has demonstrated a CMOS image sensor-based analysis of cardiovascular disease markers, such as C-reactive protein (CRP) and troponin I, Ag-Ab interactions on indium nanoparticle (InNP) substrates by simple photon count variation. The developed sensor is feasible to detect proteins even at a fg/mL concentration under ordinary room light. Possible mechanisms, such as dielectric constant and refractive-index changes, have been studied and proposed. A dramatic change in the refractive index after protein adsorption on an InNP substrate was observed to be a predominant factor involved in CMOS image sensor-based immunoassay.

Retrieval of spectral aerosol optical thickness over land using ocean color sensors MERIS and SeaWiFS

Directory of Open Access Journals (Sweden)

W. von Hoyningen-Huene

2011-02-01

Full Text Available For the determination of aerosol optical thickness (AOT Bremen AErosol Retrieval (BAER has been developed. Method and main features on the aerosol retrieval are described together with validation and results. The retrieval separates the spectral aerosol reflectance from surface and Rayleigh path reflectance for the shortwave range of the measured spectrum of top-of-atmosphere reflectance for wavelength less than 0.670 μm. The advantage of MERIS (Medium Resolution Imaging Spectrometer on the Environmental Satellite – ENVISAT – of the European Space Agency – ESA and SeaWiFS (Sea viewing Wide Field Sensor on OrbView-2 spacecraft observations is the availability of several spectral channels in the blue and visible range enabling the spectral determination of AOT in 7 (or 6 channels (0.412–0.670 μm and additionally channels in the NIR, which can be used to characterize the surface properties. A dynamical spectral surface reflectance model for different surface types is used to obtain the spectral surface reflectance for this separation. The normalized differential vegetation index (NDVI, taken from the satellite observations, is the model input. Further surface bi-directional reflectance distribution function (BRDF is considered by the Raman-Pinty-Verstraete (RPV model. Spectral AOT is obtained from aerosol reflectance using look-up-tables, obtained from radiative transfer calculations with given aerosol phase functions and single scattering albedos either from aerosol models, given by model package "optical properties of aerosol components" (OPAC or from experimental campaigns. Validations of the obtained AOT retrieval results with data of Aerosol Robotic Network (AERONET over Europe gave a preference for experimental phase functions derived from almucantar measurements. Finally long-term observations of SeaWiFS have been investigated for 11 year trends in AOT. Western European regions have negative trends with decreasing AOT with time

An improved feature extraction algorithm based on KAZE for multi-spectral image

Science.gov (United States)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

A compact bio-inspired visible/NIR imager for image-guided surgery (Conference Presentation)

Science.gov (United States)

Gao, Shengkui; Garcia, Missael; Edmiston, Chris; York, Timothy; Marinov, Radoslav; Mondal, Suman B.; Zhu, Nan; Sudlow, Gail P.; Akers, Walter J.; Margenthaler, Julie A.; Liang, Rongguang; Pepino, Marta; Achilefu, Samuel; Gruev, Viktor

2016-03-01

Inspired by the visual system of the morpho butterfly, we have designed, fabricated, tested and clinically translated an ultra-sensitive, light weight and compact imaging sensor capable of simultaneously capturing near infrared (NIR) and visible spectrum information. The visual system of the morpho butterfly combines photosensitive cells with spectral filters at the receptor level. The spectral filters are realized by alternating layers of high and low dielectric constant, such as air and cytoplasm. We have successfully mimicked this concept by integrating pixelated spectral filters, realized by alternating silicon dioxide and silicon nitrate layers, with an array of CCD detectors. There are four different types of pixelated spectral filters in the imaging plane: red, green, blue and NIR. The high optical density (OD) of all spectral filters (OD>4) allow for efficient rejections of photons from unwanted bands. The single imaging chip weighs 20 grams with form factor of 5mm by 5mm. The imaging camera is integrated with a goggle display system. A tumor targeted agent, LS301, is used to identify all spontaneous tumors in a transgenic PyMT murine model of breast cancer. The imaging system achieved sensitivity of 98% and selectivity of 95%. We also used our imaging sensor to locate sentinel lymph nodes (SLNs) in patients with breast cancer using indocyanine green tracer. The surgeon was able to identify 100% of SLNs when using our bio-inspired imaging system, compared to 93% when using information from the lymphotropic dye and 96% when using information from the radioactive tracer.

Women's preferences of dynamic spectral imaging colposcopy

NARCIS (Netherlands)

Louwers, J.A.; Zaal, Afra; Kocken, M.; Papagiannakis, E.; Meijer, C.J.; Verheijen, RHM

2015-01-01

Background: The focus of testing the dynamic spectral imaging (DSI) colposcope has been on the technical characteristics and clinical performance. However, aspects from a patient’s perspective are just as important. Methods: This study was designed as a substudy of the DSI validation study, a

Objective image characterization of a spectral CT scanner with dual-layer detector

Science.gov (United States)

Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

2018-01-01

This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

Infrared hyperspectral imaging miniaturized for UAV applications

Science.gov (United States)

Hinnrichs, Michele; Hinnrichs, Bradford; McCutchen, Earl

2017-02-01

Pacific Advanced Technology (PAT) has developed an infrared hyperspectral camera, both MWIR and LWIR, small enough to serve as a payload on a miniature unmanned aerial vehicles. The optical system has been integrated into the cold-shield of the sensor enabling the small size and weight of the sensor. This new and innovative approach to infrared hyperspectral imaging spectrometer uses micro-optics and will be explained in this paper. The micro-optics are made up of an area array of diffractive optical elements where each element is tuned to image a different spectral region on a common focal plane array. The lenslet array is embedded in the cold-shield of the sensor and actuated with a miniature piezo-electric motor. This approach enables rapid infrared spectral imaging with multiple spectral images collected and processed simultaneously each frame of the camera. This paper will present our optical mechanical design approach which results in an infrared hyper-spectral imaging system that is small enough for a payload on a mini-UAV or commercial quadcopter. Also, an example of how this technology can easily be used to quantify a hydrocarbon gas leak's volume and mass flowrates. The diffractive optical elements used in the lenslet array are blazed gratings where each lenslet is tuned for a different spectral bandpass. The lenslets are configured in an area array placed a few millimeters above the focal plane and embedded in the cold-shield to reduce the background signal normally associated with the optics. We have developed various systems using a different number of lenslets in the area array. Depending on the size of the focal plane and the diameter of the lenslet array will determine the spatial resolution. A 2 x 2 lenslet array will image four different spectral images of the scene each frame and when coupled with a 512 x 512 focal plane array will give spatial resolution of 256 x 256 pixel each spectral image. Another system that we developed uses a 4 x 4

An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles

Directory of Open Access Journals (Sweden)

Youkyung Han

2017-01-01

Full Text Available Multitemporal hyperspectral remote sensing data have the potential to detect altered areas on the earth’s surface. However, dissimilar radiometric and geometric properties between the multitemporal data due to the acquisition time or position of the sensors should be resolved to enable hyperspectral imagery for detecting changes in natural and human-impacted areas. In addition, data noise in the hyperspectral imagery spectrum decreases the change-detection accuracy when general change-detection algorithms are applied to hyperspectral images. To address these problems, we present an unsupervised change-detection algorithm based on statistical analyses of spectral profiles; the profiles are generated from a synthetic image fusion method for multitemporal hyperspectral images. This method aims to minimize the noise between the spectra corresponding to the locations of identical positions by increasing the change-detection rate and decreasing the false-alarm rate without reducing the dimensionality of the original hyperspectral data. Using a quantitative comparison of an actual dataset acquired by airborne hyperspectral sensors, we demonstrate that the proposed method provides superb change-detection results relative to the state-of-the-art unsupervised change-detection algorithms.

Methods for Enhancing Geological Structures in Spectral Spatial Difference－Based on Remote-Sensing Image

Institute of Scientific and Technical Information of China (English)

无

2000-01-01

@@In this paper, some image processing methods such as directional template (mask) matching enhancement, pseudocolor or false color enhancement, K-L transform enhancement are used to enhance a geological structure, one of important ore-controlling factors, shown in the remote-sensing images.This geological structure is regarded as image anomaly in the remote-sensing image, since considerable differences, based on the spatial spectral distribution pattern, in gray values (spectral), color tones and texture, are always present between the geological structure and background. Therefore,the enhancement of the geological structure in the remotesensing image is that of the spectral spatial difference.

Utility of BRDF Models for Estimating Optimal View Angles in Classification of Remotely Sensed Images

Science.gov (United States)

Valdez, P. F.; Donohoe, G. W.

1997-01-01

Statistical classification of remotely sensed images attempts to discriminate between surface cover types on the basis of the spectral response recorded by a sensor. It is well known that surfaces reflect incident radiation as a function of wavelength producing a spectral signature specific to the material under investigation. Multispectral and hyperspectral sensors sample the spectral response over tens and even hundreds of wavelength bands to capture the variation of spectral response with wavelength. Classification algorithms then exploit these differences in spectral response to distinguish between materials of interest. Sensors of this type, however, collect detailed spectral information from one direction (usually nadir); consequently, do not consider the directional nature of reflectance potentially detectable at different sensor view angles. Improvements in sensor technology have resulted in remote sensing platforms capable of detecting reflected energy across wavelengths (spectral signatures) and from multiple view angles (angular signatures) in the fore and aft directions. Sensors of this type include: the moderate resolution imaging spectroradiometer (MODIS), the multiangle imaging spectroradiometer (MISR), and the airborne solid-state array spectroradiometer (ASAS). A goal of this paper, then, is to explore the utility of Bidirectional Reflectance Distribution Function (BRDF) models in the selection of optimal view angles for the classification of remotely sensed images by employing a strategy of searching for the maximum difference between surface BRDFs. After a brief discussion of directional reflect ante in Section 2, attention is directed to the Beard-Maxwell BRDF model and its use in predicting the bidirectional reflectance of a surface. The selection of optimal viewing angles is addressed in Section 3, followed by conclusions and future work in Section 4.

Design and Fabrication of Vertically-Integrated CMOS Image Sensors

Science.gov (United States)

Skorka, Orit; Joseph, Dileepan

2011-01-01

Technologies to fabricate integrated circuits (IC) with 3D structures are an emerging trend in IC design. They are based on vertical stacking of active components to form heterogeneous microsystems. Electronic image sensors will benefit from these technologies because they allow increased pixel-level data processing and device optimization. This paper covers general principles in the design of vertically-integrated (VI) CMOS image sensors that are fabricated by flip-chip bonding. These sensors are composed of a CMOS die and a photodetector die. As a specific example, the paper presents a VI-CMOS image sensor that was designed at the University of Alberta, and fabricated with the help of CMC Microsystems and Micralyne Inc. To realize prototypes, CMOS dies with logarithmic active pixels were prepared in a commercial process, and photodetector dies with metal-semiconductor-metal devices were prepared in a custom process using hydrogenated amorphous silicon. The paper also describes a digital camera that was developed to test the prototype. In this camera, scenes captured by the image sensor are read using an FPGA board, and sent in real time to a PC over USB for data processing and display. Experimental results show that the VI-CMOS prototype has a higher dynamic range and a lower dark limit than conventional electronic image sensors. PMID:22163860

Scattering and absorption measurements of cervical tissues measures using low cost multi-spectral imaging

Science.gov (United States)

Bernat, Amir S.; Bar-Am, Kfir; Cataldo, Leigh; Bolton, Frank J.; Kahn, Bruce S.; Levitz, David

2018-02-01

Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging ( 30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

CMOS-sensors for energy-resolved X-ray imaging

International Nuclear Information System (INIS)

Doering, D.; Amar-Youcef, S.; Deveaux, M.; Linnik, B.; Müntz, C.; Stroth, Joachim; Baudot, J.; Dulinski, W.; Kachel, M.

2016-01-01

Due to their low noise, CMOS Monolithic Active Pixel Sensors are suited to sense X-rays with a few keV quantum energy, which is of interest for high resolution X-ray imaging. Moreover, the good energy resolution of the silicon sensors might be used to measure this quantum energy. Combining both features with the good spatial resolution of CMOS sensors opens the potential to build ''color sensitive' X-ray cameras. Taking such colored images is hampered by the need to operate the CMOS sensors in a single photon counting mode, which restricts the photon flux capability of the sensors. More importantly, the charge sharing between the pixels smears the potentially good energy resolution of the sensors. Based on our experience with CMOS sensors for charged particle tracking, we studied techniques to overcome the latter by means of an offline processing of the data obtained from a CMOS sensor prototype. We found that the energy resolution of the pixels can be recovered at the expense of reduced quantum efficiency. We will introduce the results of our study and discuss the feasibility of taking colored X-ray pictures with CMOS sensors

A Workflow for Automated Satellite Image Processing: from Raw VHSR Data to Object-Based Spectral Information for Smallholder Agriculture

Directory of Open Access Journals (Sweden)

Dimitris Stratoulias

2017-10-01

Full Text Available Earth Observation has become a progressively important source of information for land use and land cover services over the past decades. At the same time, an increasing number of reconnaissance satellites have been set in orbit with ever increasing spatial, temporal, spectral, and radiometric resolutions. The available bulk of data, fostered by open access policies adopted by several agencies, is setting a new landscape in remote sensing in which timeliness and efficiency are important aspects of data processing. This study presents a fully automated workflow able to process a large collection of very high spatial resolution satellite images to produce actionable information in the application framework of smallholder farming. The workflow applies sequential image processing, extracts meaningful statistical information from agricultural parcels, and stores them in a crop spectrotemporal signature library. An important objective is to follow crop development through the season by analyzing multi-temporal and multi-sensor images. The workflow is based on free and open-source software, namely R, Python, Linux shell scripts, the Geospatial Data Abstraction Library, custom FORTRAN, C++, and the GNU Make utilities. We tested and applied this workflow on a multi-sensor image archive of over 270 VHSR WorldView-2, -3, QuickBird, GeoEye, and RapidEye images acquired over five different study areas where smallholder agriculture prevails.

Selecting optimal monochromatic level with spectral CT imaging for improving imaging quality in hepatic venography

International Nuclear Information System (INIS)

Sun Jun; Luo Xianfu; Wang Shou'an; Wang Jun; Sun Jiquan; Wang Zhijun; Wu Jingtao

2013-01-01

Objective: To investigate the effect of spectral CT monochromatic images for improving imaging quality in hepatic venography. Methods: Thirty patients underwent spectral CT examination on a GE Discovery CT 750 HD scanner. During portal phase, 1.25 mm slice thickness polychromatic images and optimal monochromatic images were obtained, and volume rendering and maximum intensity projection were created to show the hepatic veins respectively. The overall imaging quality was evaluated on a five-point scale by two radiologists. Inter-observer agreement in subjective image quality grading was assessed by Kappa statistics. Paired-sample t test were used to compare hepatic vein attenuation, hepatic parenchyma attenuation, CT value difference between the hepatic vein and the liver parenchyma, image noise, vein-to-liver contrast-to-noise ratio (CNR), the image quality score of hepatic venography between the two image data sets. Results: The monochromatic images at 50 keV were found to demonstrate the best CNR for hepatic vein.The hepatic vein attenuation [(329 ± 47) HU], hepatic parenchyma attenuation [(178 ± 33) HU], CT value difference between the hepatic vein and the liver parenchyma [(151 ± 33) HU], image noise (17.33 ± 4.18), CNR (9.13 ± 2.65), the image quality score (4.2 ± 0.6) of optimal monochromatic images were significantly higher than those of polychromatic images [(149 ± 18) HU], [(107 ± 14) HU], [(43 ±11) HU], 12.55 ± 3.02, 3.53 ± 1.03, 3.1 ± 0.8 (t values were 24.79, 13.95, 18.85, 9.07, 13.25 and 12.04, respectively, P < 0.01). In the comparison of image quality, Kappa value was 0.81 with optimal monochromatic images and 0.69 with polychromatic images. Conclusion: Monochromatic images of spectral CT could improve CNR for displaying hepatic vein and improve the image quality compared to the conventional polychromatic images. (authors)

Study of photoconductor-based radiological image sensors

International Nuclear Information System (INIS)

Beaumont, Francois

1989-01-01

Because of the evolution of medical imaging techniques to digital Systems, it is necessary to replace radiological film which has many drawbacks, by a detector quite as efficient and quickly giving a digitizable signal. The purpose of this thesis is to find new X-ray digital imaging processes using photoconductor materials such as amorphous selenium. After reviewing the principle of direct radiology and functions to be served by the X-ray sensor (i.e. detection, memory, assignment, visualization), we explain specification. We especially show the constraints due to the object to be radiographed (condition of minimal exposure), and to the reading signal (electronic noise detection associated with a reading frequency). As a result of this study, a first photoconductor sensor could be designed. Its principle is based on photo-carrier trapping at dielectric-photoconductor structure interface. The reading System needs the scanning of a laser beam upon the sensor surface. The dielectric-photoconductor structure enabled us to estimate the possibilities offered by the sensor and to build a complete x-ray imaging System. The originality of thermo-dielectric sensor, that was next studied, is to allow a thermal assignment reading. The chosen System consists in varying the ferroelectric polymer capacity whose dielectric permittivity is weak at room temperature. The thermo-dielectric material was studied by thermal or Joule effect stimulation. During our experiments, trapping was found in a sensor made of amorphous selenium between two electrodes. This new effect was performed and enabled us to expose a first interpretation. Eventually, the comparison of these new sensor concepts with radiological film shows the advantage of the proposed solution. (author) [fr

Fabricating Optical Fiber Imaging Sensors Using Inkjet Printing Technology: a pH Sensor Proof-of-Concept

Energy Technology Data Exchange (ETDEWEB)

Carter, J C; Alvis, R M; Brown, S B; Langry, K C; Wilson, T S; McBride, M T; Myrick, M L; Cox, W R; Grove, M E; Colston, B W

2005-03-01

We demonstrate the feasibility of using Drop-on-Demand microjet printing technology for fabricating imaging sensors by reproducibly printing an array of photopolymerizable sensing elements, containing a pH sensitive indicator, on the surface of an optical fiber image guide. The reproducibility of the microjet printing process is excellent for microdot (i.e. micron-sized polymer) sensor diameter (92.2 {+-} 2.2 microns), height (35.0 {+-} 1.0 microns), and roundness (0.00072 {+-} 0.00023). pH sensors were evaluated in terms of pH sensing ability ({le}2% sensor variation), response time, and hysteresis using a custom fluorescence imaging system. In addition, the microjet technique has distinct advantages over other fabrication methods, which are discussed in detail.

CMOS Imaging of Pin-Printed Xerogel-Based Luminescent Sensor Microarrays.

Science.gov (United States)

Yao, Lei; Yung, Ka Yi; Khan, Rifat; Chodavarapu, Vamsy P; Bright, Frank V

2010-12-01

We present the design and implementation of a luminescence-based miniaturized multisensor system using pin-printed xerogel materials which act as host media for chemical recognition elements. We developed a CMOS imager integrated circuit (IC) to image the luminescence response of the xerogel-based sensor array. The imager IC uses a 26 × 20 (520 elements) array of active pixel sensors and each active pixel includes a high-gain phototransistor to convert the detected optical signals into electrical currents. The imager includes a correlated double sampling circuit and pixel address/digital control circuit; the image data is read-out as coded serial signal. The sensor system uses a light-emitting diode (LED) to excite the target analyte responsive luminophores doped within discrete xerogel-based sensor elements. As a prototype, we developed a 4 × 4 (16 elements) array of oxygen (O 2 ) sensors. Each group of 4 sensor elements in the array (arranged in a row) is designed to provide a different and specific sensitivity to the target gaseous O 2 concentration. This property of multiple sensitivities is achieved by using a strategic mix of two oxygen sensitive luminophores ([Ru(dpp) 3 ] 2+ and ([Ru(bpy) 3 ] 2+ ) in each pin-printed xerogel sensor element. The CMOS imager consumes an average power of 8 mW operating at 1 kHz sampling frequency driven at 5 V. The developed prototype system demonstrates a low cost and miniaturized luminescence multisensor system.

Multichannel imager for littoral zone characterization

Science.gov (United States)

Podobna, Yuliya; Schoonmaker, Jon; Dirbas, Joe; Sofianos, James; Boucher, Cynthia; Gilbert, Gary

2010-04-01

This paper describes an approach to utilize a multi-channel, multi-spectral electro-optic (EO) system for littoral zone characterization. Advanced Coherent Technologies, LLC (ACT) presents their EO sensor systems for the surf zone environmental assessment and potential surf zone target detection. Specifically, an approach is presented to determine a Surf Zone Index (SZI) from the multi-spectral EO sensor system. SZI provides a single quantitative value of the surf zone conditions delivering an immediate understanding of the area and an assessment as to how well an airborne optical system might perform in a mine countermeasures (MCM) operation. Utilizing consecutive frames of SZI images, ACT is able to measure variability over time. A surf zone nomograph, which incorporates targets, sensor, and environmental data, including the SZI to determine the environmental impact on system performance, is reviewed in this work. ACT's electro-optical multi-channel, multi-spectral imaging system and test results are presented and discussed.

Lightning Imaging Sensor (LIS) on TRMM Science Data V4

Data.gov (United States)

National Aeronautics and Space Administration — The Lightning Imaging Sensor (LIS) Science Data was collected by the Lightning Imaging Sensor (LIS), which was an instrument on the Tropical Rainfall Measurement...

Fingerprint image reconstruction for swipe sensor using Predictive Overlap Method

Directory of Open Access Journals (Sweden)

Mardiansyah Ahmad Zafrullah

2018-01-01

Full Text Available Swipe sensor is one of many biometric authentication sensor types that widely applied to embedded devices. The sensor produces an overlap on every pixel block of the image, so the picture requires a reconstruction process before heading to the feature extraction process. Conventional reconstruction methods require extensive computation, causing difficult to apply to embedded devices that have limited computing process. In this paper, image reconstruction is proposed using predictive overlap method, which determines the image block shift from the previous set of change data. The experiments were performed using 36 images generated by a swipe sensor with 128 x 8 pixels size of the area, where each image has an overlap in each block. The results reveal computation can increase up to 86.44% compared with conventional methods, with accuracy decreasing to 0.008% in average.

Coresident sensor fusion and compression using the wavelet transform

Energy Technology Data Exchange (ETDEWEB)

Yocky, D.A.

1996-03-11

Imagery from coresident sensor platforms, such as unmanned aerial vehicles, can be combined using, multiresolution decomposition of the sensor images by means of the two-dimensional wavelet transform. The wavelet approach uses the combination of spatial/spectral information at multiple scales to create a fused image. This can be done in both an ad hoc or model-based approach. We compare results from commercial ``fusion`` software and the ad hoc, wavelet approach. Results show the wavelet approach outperforms the commercial algorithms and also supports efficient compression of the fused image.

THE RESEARCH OF SPECTRAL RECONSTRUCTION FOR LARGE APERTURE STATIC IMAGING SPECTROMETER

Directory of Open Access Journals (Sweden)

H. Lv

2018-04-01

Full Text Available Imaging spectrometer obtains or indirectly obtains the spectral information of the ground surface feature while obtaining the target image, which makes the imaging spectroscopy has a prominent advantage in fine characterization of terrain features, and is of great significance for the study of geoscience and other related disciplines. Since the interference data obtained by interferometric imaging spectrometer is intermediate data, which must be reconstructed to achieve the high quality spectral data and finally used by users. The difficulty to restrict the application of interferometric imaging spectroscopy is to reconstruct the spectrum accurately. Based on the original image acquired by Large Aperture Static Imaging Spectrometer as the input, this experiment selected the pixel that is identified as crop by artificial recognition, extract and preprocess the interferogram to recovery the corresponding spectrum of this pixel. The result shows that the restructured spectrum formed a small crest near the wavelength of 0.55 μm with obvious troughs on both sides. The relative reflection intensity of the restructured spectrum rises abruptly at the wavelength around 0.7 μm, forming a steep slope. All these characteristics are similar with the spectral reflection curve of healthy green plants. It can be concluded that the experimental result is consistent with the visual interpretation results, thus validating the effectiveness of the scheme for interferometric imaging spectrum reconstruction proposed in this paper.

The challenge of sCMOS image sensor technology to EMCCD

Science.gov (United States)

Chang, Weijing; Dai, Fang; Na, Qiyue

2018-02-01

In the field of low illumination image sensor, the noise of the latest scientific-grade CMOS image sensor is close to EMCCD, and the industry thinks it has the potential to compete and even replace EMCCD. Therefore we selected several typical sCMOS and EMCCD image sensors and cameras to compare their performance parameters. The results show that the signal-to-noise ratio of sCMOS is close to EMCCD, and the other parameters are superior. But signal-to-noise ratio is very important for low illumination imaging, and the actual imaging results of sCMOS is not ideal. EMCCD is still the first choice in the high-performance application field.

Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

Science.gov (United States)

Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon

2001-01-01

A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

Science.gov (United States)

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-10-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera

Directory of Open Access Journals (Sweden)

Thomas C. Wilkes

2016-10-01

Full Text Available Here, we report, for what we believe to be the first time, on the modification of a low cost sensor, designed for the smartphone camera market, to develop an ultraviolet (UV camera system. This was achieved via adaptation of Raspberry Pi cameras, which are based on back-illuminated complementary metal-oxide semiconductor (CMOS sensors, and we demonstrated the utility of these devices for applications at wavelengths as low as 310 nm, by remotely sensing power station smokestack emissions in this spectral region. Given the very low cost of these units, ≈ USD 25, they are suitable for widespread proliferation in a variety of UV imaging applications, e.g., in atmospheric science, volcanology, forensics and surface smoothness measurements.

A bio-image sensor for simultaneous detection of multi-neurotransmitters.

Science.gov (United States)

Lee, You-Na; Okumura, Koichi; Horio, Tomoko; Iwata, Tatsuya; Takahashi, Kazuhiro; Hattori, Toshiaki; Sawada, Kazuaki

2018-03-01

We report here a new bio-image sensor for simultaneous detection of spatial and temporal distribution of multi-neurotransmitters. It consists of multiple enzyme-immobilized membranes on a 128 × 128 pixel array with read-out circuit. Apyrase and acetylcholinesterase (AChE), as selective elements, are used to recognize adenosine 5'-triphosphate (ATP) and acetylcholine (ACh), respectively. To enhance the spatial resolution, hydrogen ion (H + ) diffusion barrier layers are deposited on top of the bio-image sensor and demonstrated their prevention capability. The results are used to design the space among enzyme-immobilized pixels and the null H + sensor to minimize the undesired signal overlap by H + diffusion. Using this bio-image sensor, we can obtain H + diffusion-independent imaging of concentration gradients of ATP and ACh in real-time. The sensing characteristics, such as sensitivity and detection of limit, are determined experimentally. With the proposed bio-image sensor the possibility exists for customizable monitoring of the activities of various neurochemicals by using different kinds of proton-consuming or generating enzymes. Copyright © 2017 Elsevier B.V. All rights reserved.

3D high spectral and spatial resolution imaging of ex vivo mouse brain

International Nuclear Information System (INIS)

Foxley, Sean; Karczmar, Gregory S.; Domowicz, Miriam; Schwartz, Nancy

2015-01-01

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T 2 * -weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T 2 * and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm 3 and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T 2 * -weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not

Conjugate Etalon Spectral Imager (CESI) & Scanning Etalon Methane Mapper (SEMM), Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The Conjugate Etalon Spectral Imaging (CESI) concept enables the development of miniature instruments with high spectral resolution, suitable for LEO missions aboard...

Dual-camera design for coded aperture snapshot spectral imaging.

Science.gov (United States)

Wang, Lizhi; Xiong, Zhiwei; Gao, Dahua; Shi, Guangming; Wu, Feng

2015-02-01

Coded aperture snapshot spectral imaging (CASSI) provides an efficient mechanism for recovering 3D spectral data from a single 2D measurement. However, since the reconstruction problem is severely underdetermined, the quality of recovered spectral data is usually limited. In this paper we propose a novel dual-camera design to improve the performance of CASSI while maintaining its snapshot advantage. Specifically, a beam splitter is placed in front of the objective lens of CASSI, which allows the same scene to be simultaneously captured by a grayscale camera. This uncoded grayscale measurement, in conjunction with the coded CASSI measurement, greatly eases the reconstruction problem and yields high-quality 3D spectral data. Both simulation and experimental results demonstrate the effectiveness of the proposed method.

An approach to estimate spatial distribution of analyte within cells using spectrally-resolved fluorescence microscopy

Science.gov (United States)

Sharma, Dharmendar Kumar; Irfanullah, Mir; Basu, Santanu Kumar; Madhu, Sheri; De, Suman; Jadhav, Sameer; Ravikanth, Mangalampalli; Chowdhury, Arindam

2017-03-01

While fluorescence microscopy has become an essential tool amongst chemists and biologists for the detection of various analyte within cellular environments, non-uniform spatial distribution of sensors within cells often restricts extraction of reliable information on relative abundance of analytes in different subcellular regions. As an alternative to existing sensing methodologies such as ratiometric or FRET imaging, where relative proportion of analyte with respect to the sensor can be obtained within cells, we propose a methodology using spectrally-resolved fluorescence microscopy, via which both the relative abundance of sensor as well as their relative proportion with respect to the analyte can be simultaneously extracted for local subcellular regions. This method is exemplified using a BODIPY sensor, capable of detecting mercury ions within cellular environments, characterized by spectral blue-shift and concurrent enhancement of emission intensity. Spectral emission envelopes collected from sub-microscopic regions allowed us to compare the shift in transition energies as well as integrated emission intensities within various intracellular regions. Construction of a 2D scatter plot using spectral shifts and emission intensities, which depend on the relative amount of analyte with respect to sensor and the approximate local amounts of the probe, respectively, enabled qualitative extraction of relative abundance of analyte in various local regions within a single cell as well as amongst different cells. Although the comparisons remain semi-quantitative, this approach involving analysis of multiple spectral parameters opens up an alternative way to extract spatial distribution of analyte in heterogeneous systems. The proposed method would be especially relevant for fluorescent probes that undergo relatively nominal shift in transition energies compared to their emission bandwidths, which often restricts their usage for quantitative ratiometric imaging in

Spectral CT of carotid atherosclerotic plaque: comparison with histology

Energy Technology Data Exchange (ETDEWEB)

Zainon, R.; Doesburg, R.M. [University of Canterbury, Department of Physics and Astronomy, Christchurch (New Zealand); Ronaldson, J.P.; Gieseg, S.P. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); Janmale, T. [University of Canterbury, Free Radical Biochemistry Laboratory, School of Biological Sciences, Christchurch (New Zealand); Scott, N.J. [University of Otago, Department of Medicine, Christchurch (New Zealand); Buckenham, T.M. [University of Otago, Department of Academic Radiology, Christchurch (New Zealand); Butler, A.P.H. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); University of Otago, Department of Academic Radiology, Christchurch (New Zealand); University of Canterbury, Department of Electrical and Computer Engineering, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); Butler, P.H. [University of Canterbury, Department of Physics and Astronomy, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); Roake, J.A. [Christchurch Hospital, Department of Vascular, Endovascular and Transplant Surgery, Christchurch (New Zealand); Anderson, N.G. [University of Otago, Centre for Bioengineering, Christchurch (New Zealand); University of Otago, Department of Academic Radiology, Christchurch (New Zealand); University of Otago, Christchurch, Department of Radiology, PO Box 4345, Christchurch (New Zealand)

2012-12-15

To distinguish components of vulnerable atherosclerotic plaque by imaging their energy response using spectral CT and comparing images with histology. After spectroscopic calibration using phantoms of plaque surrogates, excised human carotid atherosclerotic plaques were imaged using MARS CT using a photon-processing detector with a silicon sensor layer and microfocus X-ray tube (50 kVp, 0.5 mA) at 38-{mu}m voxel size. The plaques were imaged, sectioned and re-imaged using four threshold energies: 10, 16, 22 and 28 keV; then sequentially stained with modified Von Kossa, Perl's Prussian blue and Oil-Red O, and photographed. Relative Hounsfield units across the energies were entered into a linear algebraic material decomposition model to identify the unknown plaque components. Lipid, calcium, iron and water-like components of plaque have distinguishable energy responses to X-ray, visible on spectral CT images. CT images of the plaque surface correlated very well with histological photographs. Calcium deposits (>1,000 {mu}m) in plaque are larger than iron deposits (<100 {mu}m), but could not be distinguished from each other within the same voxel using the energy range available. Spectral CT displays energy information in image form at high spatial resolution, enhancing the intrinsic contrast of lipid, calcium and iron within atheroma. (orig.)

High dynamic range imaging sensors and architectures

CERN Document Server

Darmont, Arnaud

2013-01-01

Illumination is a crucial element in many applications, matching the luminance of the scene with the operational range of a camera. When luminance cannot be adequately controlled, a high dynamic range (HDR) imaging system may be necessary. These systems are being increasingly used in automotive on-board systems, road traffic monitoring, and other industrial, security, and military applications. This book provides readers with an intermediate discussion of HDR image sensors and techniques for industrial and non-industrial applications. It describes various sensor and pixel architectures capable

Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

Science.gov (United States)

Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

2017-04-01

Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

A Gimbal-Stabilized Compact Hyperspectral Imaging System, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — The Gimbal-stabilized Compact Hyperspectral Imaging System (GCHIS) fully integrates multi-sensor spectral imaging, stereovision, GPS and inertial measurement,...

Integrating two spectral imaging systems in an automated mineralogy application

CSIR Research Space (South Africa)

Harris, D

2009-11-01

Full Text Available is treated in batches, with trays of mono-layered material presented to various imaging systems. The identification of target grains is achieved by means of spectral imaging in two wavelength bands (Visible, and Long Wave Infrared). Target grains...

Experimental single-chip color HDTV image acquisition system with 8M-pixel CMOS image sensor

Science.gov (United States)

Shimamoto, Hiroshi; Yamashita, Takayuki; Funatsu, Ryohei; Mitani, Kohji; Nojiri, Yuji

2006-02-01

We have developed an experimental single-chip color HDTV image acquisition system using 8M-pixel CMOS image sensor. The sensor has 3840 × 2160 effective pixels and is progressively scanned at 60 frames per second. We describe the color filter array and interpolation method to improve image quality with a high-pixel-count single-chip sensor. We also describe an experimental image acquisition system we used to measured spatial frequency characteristics in the horizontal direction. The results indicate good prospects for achieving a high quality single chip HDTV camera that reduces pseudo signals and maintains high spatial frequency characteristics within the frequency band for HDTV.

Research on marine and freshwater fish identification model based on hyper-spectral imaging technology

Science.gov (United States)

Fu, Yan; Guo, Pei-yuan; Xiang, Ling-zi; Bao, Man; Chen, Xing-hai

2013-08-01

With the gradually mature of hyper spectral image technology, the application of the meat nondestructive detection and recognition has become one of the current research focuses. This paper for the study of marine and freshwater fish by the pre-processing and feature extraction of the collected spectral curve data, combined with BP network structure and LVQ network structure, a predictive model of hyper spectral image data of marine and freshwater fish has been initially established and finally realized the qualitative analysis and identification of marine and freshwater fish quality. The results of this study show that hyper spectral imaging technology combined with the BP and LVQ Artificial Neural Network Model can be used for the identification of marine and freshwater fish detection. Hyper-spectral data acquisition can be carried out without any pretreatment of the samples, thus hyper-spectral imaging technique is the lossless, high- accuracy and rapid detection method for quality of fish. In this study, only 30 samples are used for the exploratory qualitative identification of research, although the ideal study results are achieved, we will further increase the sample capacity to take the analysis of quantitative identification and verify the feasibility of this theory.

A multi-object spectral imaging instrument

International Nuclear Information System (INIS)

Gibson, G M; Dienerowitz, M; Kelleher, P A; Harvey, A R; Padgett, M J

2013-01-01

We have developed a snapshot spectral imaging system which fits onto the side camera port of a commercial inverted microscope. The system provides spectra, in real time, from multiple points randomly selected on the microscope image. Light from the selected points in the sample is directed from the side port imaging arm using a digital micromirror device to a spectrometer arm based on a dispersing prism and CCD camera. A multi-line laser source is used to calibrate the pixel positions on the CCD for wavelength. A CMOS camera on the front port of the microscope allows the full image of the sample to be displayed and can also be used for particle tracking, providing spectra of multiple particles moving in the sample. We demonstrate the system by recording the spectra of multiple fluorescent beads in aqueous solution and from multiple points along a microscope sample channel containing a mixture of red and blue dye. (paper)

WE-DE-BRA-07: Megavoltage Spectral Imaging with a Layered Detector

Energy Technology Data Exchange (ETDEWEB)

Myronakis, M; Rottmann, J; Berbeco, R [Brigham and Women’s Hospital, Boston, MA (United States); Hu, Y [Dana Farber Cancer Institute, Boston, MA (United States); Wang, A; Shedlock, D; Star-Lack, J [Varian Medical Systems, Palo Alto, CA (United States); Morf, D [Varian Medical Systems, Dattwil, Aargau (Switzerland)

2016-06-15

Purpose: The aim of the current work is to investigate the feasibility of megavoltage spectral imaging using a multiple layered detector for enhancement of low contrast detectability through material segmentation and discrimination (such as bone, markers and metal implants). Potentially the technique can be applied to improve detection and reduce dose in Megavoltage Cone Beam Computed Tomography (MV-CBCT). Methods: Experiments were performed with a prototype multi-layer imager (MLI) which has higher detective efficiency and lower noise characteristics than conventional Electronic Portal Imaging Devices (EPIDs). Images of a solid water phantom were acquired at 2.5 MV, 6MV and 6MV without flattening filter (FFF). The following materials were placed within a stack of solid water: aluminum, copper and gold. Material separation was assessed based on Contrast-to-Noise Ratio (CNR) of the weighted image, formed by a weighted subtraction of the images from two layers of the MLI. A range of weighting factors were investigated for material separation. Results: CNR can be minimized for each material by appropriate selection of the subtraction weighting factor. This is equivalent to a selective subtraction of specific materials from the image. Using multiple layers simultaneously also decreases the dose requirement and removes any registration errors. The minimum CNR for aluminum, copper and gold at the weighted image formed with 2.5MV was obtained at weighting factors equal to 0.92, 0.76 and 0.64 respectively. The corresponding values at 6MVFFF were 0.99, 0.92 and 0.78 respectively. Conclusion: In the current work, an MV spectral imaging feasibility study was attempted using a novel multi-layer prototype EPID imager. Initial results suggest that material separation based on spectral differences between different layers is possible. This spectral imaging technique has potential advantages in MV-CBCT for real-time target tracking, patient set-up imaging and adaptive radiotherapy

Spectral quality requirements for effluent identification

Science.gov (United States)

Czerwinski, R. N.; Seeley, J. A.; Wack, E. C.

2005-11-01

We consider the problem of remotely identifying gaseous materials using passive sensing of long-wave infrared (LWIR) spectral features at hyperspectral resolution. Gaseous materials are distinguishable in the LWIR because of their unique spectral fingerprints. A sensor degraded in capability by noise or limited spectral resolution, however, may be unable to positively identify contaminants, especially if they are present in low concentrations or if the spectral library used for comparisons includes materials with similar spectral signatures. This paper will quantify the relative importance of these parameters and express the relationships between them in a functional form which can be used as a rule of thumb in sensor design or in assessing sensor capability for a specific task. This paper describes the simulation of remote sensing datacontaining a gas cloud.In each simulation, the spectra are degraded in spectral resolution and through the addition of noise to simulate spectra collected by sensors of varying design and capability. We form a trade space by systematically varying the number of sensor spectral channels and signal-to-noise ratio over a range of values. For each scenario, we evaluate the capability of the sensor for gas identification by computing the ratio of the F-statistic for the truth gas tothe same statistic computed over the rest of the library.The effect of the scope of the library is investigated as well, by computing statistics on the variability of the identification capability as the library composition is varied randomly.

3D high spectral and spatial resolution imaging of ex vivo mouse brain

Energy Technology Data Exchange (ETDEWEB)

Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S. [Department of Radiology, University of Chicago, Chicago, Illinois 60637 (United States); Domowicz, Miriam [Department of Pediatrics, University of Chicago, Chicago, Illinois 60637 (United States); Schwartz, Nancy [Department of Pediatrics, Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637 (United States)

2015-03-15

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in

Performance study of double SOI image sensors

Science.gov (United States)

Miyoshi, T.; Arai, Y.; Fujita, Y.; Hamasaki, R.; Hara, K.; Ikegami, Y.; Kurachi, I.; Nishimura, R.; Ono, S.; Tauchi, K.; Tsuboyama, T.; Yamada, M.

2018-02-01

Double silicon-on-insulator (DSOI) sensors composed of two thin silicon layers and one thick silicon layer have been developed since 2011. The thick substrate consists of high resistivity silicon with p-n junctions while the thin layers are used as SOI-CMOS circuitry and as shielding to reduce the back-gate effect and crosstalk between the sensor and the circuitry. In 2014, a high-resolution integration-type pixel sensor, INTPIX8, was developed based on the DSOI concept. This device is fabricated using a Czochralski p-type (Cz-p) substrate in contrast to a single SOI (SSOI) device having a single thin silicon layer and a Float Zone p-type (FZ-p) substrate. In the present work, X-ray spectra of both DSOI and SSOI sensors were obtained using an Am-241 radiation source at four gain settings. The gain of the DSOI sensor was found to be approximately three times that of the SSOI device because the coupling capacitance is reduced by the DSOI structure. An X-ray imaging demonstration was also performed and high spatial resolution X-ray images were obtained.

Special Sensor Microwave Imager/Sounder (SSMIS) Sensor Data Record (SDR) in netCDF

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Special Sensor Microwave Imager/Sounder (SSMIS) is a series of passive microwave conically scanning imagers and sounders onboard the DMSP satellites beginning...

Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Ya-Shuo Li

2012-03-01

Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

Sparse spectral deconvolution algorithm for noncartesian MR spectroscopic imaging.

Science.gov (United States)

Bhave, Sampada; Eslami, Ramin; Jacob, Mathews

2014-02-01

To minimize line shape distortions and spectral leakage artifacts in MR spectroscopic imaging (MRSI). A spatially and spectrally regularized non-Cartesian MRSI algorithm that uses the line shape distortion priors, estimated from water reference data, to deconvolve the spectra is introduced. Sparse spectral regularization is used to minimize noise amplification associated with deconvolution. A spiral MRSI sequence that heavily oversamples the central k-space regions is used to acquire the MRSI data. The spatial regularization term uses the spatial supports of brain and extracranial fat regions to recover the metabolite spectra and nuisance signals at two different resolutions. Specifically, the nuisance signals are recovered at the maximum resolution to minimize spectral leakage, while the point spread functions of metabolites are controlled to obtain acceptable signal-to-noise ratio. The comparisons of the algorithm against Tikhonov regularized reconstructions demonstrates considerably reduced line-shape distortions and improved metabolite maps. The proposed sparsity constrained spectral deconvolution scheme is effective in minimizing the line-shape distortions. The dual resolution reconstruction scheme is capable of minimizing spectral leakage artifacts. Copyright © 2013 Wiley Periodicals, Inc.

[Influence of human body target's spectral characteristics on visual range of low light level image intensifiers].

Science.gov (United States)

Zhang, Jun-Ju; Yang, Wen-Bin; Xu, Hui; Liu, Lei; Tao, Yuan-Yaun

2013-11-01

To study the effect of different human target's spectral reflective characteristic on low light level (LLL) image intensifier's distance, based on the spectral characteristics of the night-sky radiation and the spectral reflective coefficients of common clothes, we established a equation of human body target's spectral reflective distribution, and analyzed the spectral reflective characteristics of different human targets wearing the clothes of different color and different material, and from the actual detection equation of LLL image intensifier distance, discussed the detection capability of LLL image intensifier for different human target. The study shows that the effect of different human target's spectral reflective characteristic on LLL image intensifier distance is mainly reflected in the average reflectivity rho(-) and the initial contrast of the target and the background C0. Reflective coefficient and spectral reflection intensity of cotton clothes are higher than polyester clothes, and detection capability of LLL image intensifier is stronger for the human target wearing cotton clothes. Experimental results show that the LLL image intensifiers have longer visual ranges for targets who wear cotton clothes than targets who wear same color but polyester clothes, and have longer visual ranges for targets who wear light-colored clothes than targets who wear dark-colored clothes. And in the full moon illumination conditions, LLL image intensifiers are more sensitive to the clothes' material.

Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

DEFF Research Database (Denmark)

Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

2007-01-01

based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method.......Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

Directory of Open Access Journals (Sweden)

MingXia He

2007-12-01

Full Text Available About 30 years ago, NASA launched the first ocean-color observing satellite:the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with anobjective to detect changes of phytoplankton (measured by concentration of chlorophyll inthe oceans. Twenty years later, for the same objective but with advanced technology, theSea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands, the Moderate-ResolutionImaging Spectrometer (MODIS, 8 bands, and the Medium Resolution ImagingSpectrometer (MERIS, 12 bands were launched. The selection of the number of bands andtheir positions was based on experimental and theoretical results achieved before thedesign of these satellite sensors. Recently, Lee and Carder (2002 demonstrated that foradequate derivation of major properties (phytoplankton biomass, colored dissolved organicmatter, suspended sediments, and bottom properties in both oceanic and coastalenvironments from observation of water color, it is better for a sensor to have ~15 bands inthe 400 – 800 nm range. In that study, however, it did not provide detailed analysesregarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (~ 3-nm resolution measurements of remote-sensing reflectance (a measure of water colortaken in both coastal and oceanic waters covering both optically deep and optically shallowwaters, first- and second-order derivatives were calculated after interpolating themeasurements to 1-nm resolution. From these derivatives, the frequency of zero values foreach wavelength was accounted for, and the distribution spectrum of such frequencies wasobtained. Furthermore, the wavelengths that have the highest appearance of zeros wereidentified. Because these spectral locations indicate extrema (a local maximum orminimum of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring

Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

Science.gov (United States)

Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

2013-11-20

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

A Lightweight Compact Multi-Spectral Imager Using Novel Computer-Generated Micro-Optics and Spectral-Extraction Algorithms

Data.gov (United States)

National Aeronautics and Space Administration — The objective of this NASA Early-stage research proposal is to demonstrate an ultra-compact, lightweight broadband hyper- and multi-spectral imaging system that is...

Liquid crystal-based Mueller matrix spectral imaging polarimetry for parameterizing mineral structural organization.

Science.gov (United States)

Gladish, James C; Duncan, Donald D

2017-01-20

Herein, we discuss the remote assessment of the subwavelength organizational structure of a medium. Specifically, we use spectral imaging polarimetry, as the vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. The ability to image these effects allows for inference of spatial structural organization parameters. This work describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from liquid crystal variable retarders and a liquid crystal tunable filter. We provide results to validate the system and then show results from measurements on a mineral sample.

Parametric Optimization of Lateral NIPIN Phototransistors for Flexible Image Sensors

Directory of Open Access Journals (Sweden)

Min Seok Kim

2017-08-01

Full Text Available Curved image sensors, which are a key component in bio-inspired imaging systems, have been widely studied because they can improve an imaging system in various aspects such as low optical aberrations, small-form, and simple optics configuration. Many methods and materials to realize a curvilinear imager have been proposed to address the drawbacks of conventional imaging/optical systems. However, there have been few theoretical studies in terms of electronics on the use of a lateral photodetector as a flexible image sensor. In this paper, we demonstrate the applicability of a Si-based lateral phototransistor as the pixel of a high-efficiency curved photodetector by conducting various electrical simulations with technology computer aided design (TCAD. The single phototransistor is analyzed with different device parameters: the thickness of the active cell, doping concentration, and structure geometry. This work presents a method to improve the external quantum efficiency (EQE, linear dynamic range (LDR, and mechanical stability of the phototransistor. We also evaluated the dark current in a matrix form of phototransistors to estimate the feasibility of the device as a flexible image sensor. Moreover, we fabricated and demonstrated an array of phototransistors based on our study. The theoretical study and design guidelines of a lateral phototransistor create new opportunities in flexible image sensors.

Multi-Temporal vs. Hyper-Spectral Imaging for Future Land Imaging at 30 m

Data.gov (United States)

National Aeronautics and Space Administration — We propose to determine the information content of multi-temporal land imaging in discrete Landsat-like spectral bands at 30 m with a 360 km swath width and compare...

Parametric image reconstruction using spectral analysis of PET projection data

International Nuclear Information System (INIS)

Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat

1998-01-01

Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)

Research-grade CMOS image sensors for demanding space applications

Science.gov (United States)

Saint-Pé, Olivier; Tulet, Michel; Davancens, Robert; Larnaudie, Franck; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Belliot, Pierre

2017-11-01

Imaging detectors are key elements for optical instruments and sensors on board space missions dedicated to Earth observation (high resolution imaging, atmosphere spectroscopy...), Solar System exploration (micro cameras, guidance for autonomous vehicle...) and Universe observation (space telescope focal planes, guiding sensors...). This market has been dominated by CCD technology for long. Since the mid- 90s, CMOS Image Sensors (CIS) have been competing with CCDs for more and more consumer domains (webcams, cell phones, digital cameras...). Featuring significant advantages over CCD sensors for space applications (lower power consumption, smaller system size, better radiations behaviour...), CMOS technology is also expanding in this field, justifying specific R&D and development programs funded by national and European space agencies (mainly CNES, DGA, and ESA). All along the 90s and thanks to their increasingly improving performances, CIS have started to be successfully used for more and more demanding applications, from vision and control functions requiring low-level performances to guidance applications requiring medium-level performances. Recent technology improvements have made possible the manufacturing of research-grade CIS that are able to compete with CCDs in the high-performances arena. After an introduction outlining the growing interest of optical instruments designers for CMOS image sensors, this talk will present the existing and foreseen ways to reach high-level electro-optics performances for CIS. The developments of CIS prototypes built using an imaging CMOS process and of devices based on improved designs will be presented.

Autonomous vision networking: miniature wireless sensor networks with imaging technology

Science.gov (United States)

Messinger, Gioia; Goldberg, Giora

2006-09-01

The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor

Single-event transient imaging with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor.

Science.gov (United States)

Mochizuki, Futa; Kagawa, Keiichiro; Okihara, Shin-ichiro; Seo, Min-Woong; Zhang, Bo; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2016-02-22

In the work described in this paper, an image reproduction scheme with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor was demonstrated. The sensor captures an object by compressing a sequence of images with focal-plane temporally random-coded shutters, followed by reconstruction of time-resolved images. Because signals are modulated pixel-by-pixel during capturing, the maximum frame rate is defined only by the charge transfer speed and can thus be higher than those of conventional ultra-high-speed cameras. The frame rate and optical efficiency of the multi-aperture scheme are discussed. To demonstrate the proposed imaging method, a 5×3 multi-aperture image sensor was fabricated. The average rising and falling times of the shutters were 1.53 ns and 1.69 ns, respectively. The maximum skew among the shutters was 3 ns. The sensor observed plasma emission by compressing it to 15 frames, and a series of 32 images at 200 Mfps was reconstructed. In the experiment, by correcting disparities and considering temporal pixel responses, artifacts in the reconstructed images were reduced. An improvement in PSNR from 25.8 dB to 30.8 dB was confirmed in simulations.

Hyperspectral imaging of polymer banknotes for building and analysis of spectral library

Science.gov (United States)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-11-01

The use of counterfeit banknotes increases crime rates and cripples the economy. New countermeasures are required to stop counterfeiters who use advancing technologies with criminal intent. Many countries started adopting polymer banknotes to replace paper notes, as polymer notes are more durable and have better quality. The research on authenticating such banknotes is of much interest to the forensic investigators. Hyperspectral imaging can be employed to build a spectral library of polymer notes, which can then be used for classification to authenticate these notes. This is however not widely reported and has become a research interest in forensic identification. This paper focuses on the use of hyperspectral imaging on polymer notes to build spectral libraries, using a pushbroom hyperspectral imager which has been previously reported. As an initial study, a spectral library will be built from three arbitrarily chosen regions of interest of five circulated genuine polymer notes. Principal component analysis is used for dimension reduction and to convert the information in the spectral library to principal components. A 99% confidence ellipse is formed around the cluster of principal component scores of each class and then used as classification criteria. The potential of the adopted methodology is demonstrated by the classification of the imaged regions as training samples.

Visualization of heavy ion-induced charge production in a CMOS image sensor

CERN Document Server

Végh, J; Klamra, W; Molnár, J; Norlin, LO; Novák, D; Sánchez-Crespo, A; Van der Marel, J; Fenyvesi, A; Valastyan, I; Sipos, A

2004-01-01

A commercial CMOS image sensor was irradiated with heavy ion beams in the several MeV energy range. The image sensor is equipped with a standard video output. The data were collected on-line through frame grabbing and analysed off-line after digitisation. It was shown that the response of the image sensor to the heavy ion bombardment varied with the type and energy of the projectiles. The sensor will be used for the CMS Barrel Muon Alignment system.

EIT Imaging Regularization Based on Spectral Graph Wavelets.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Vauhkonen, Marko; Wolf, Gerhard; Mueller-Lisse, Ullrich; Moeller, Knut

2017-09-01

The objective of electrical impedance tomographic reconstruction is to identify the distribution of tissue conductivity from electrical boundary conditions. This is an ill-posed inverse problem usually solved under the finite-element method framework. In previous studies, standard sparse regularization was used for difference electrical impedance tomography to achieve a sparse solution. However, regarding elementwise sparsity, standard sparse regularization interferes with the smoothness of conductivity distribution between neighboring elements and is sensitive to noise. As an effect, the reconstructed images are spiky and depict a lack of smoothness. Such unexpected artifacts are not realistic and may lead to misinterpretation in clinical applications. To eliminate such artifacts, we present a novel sparse regularization method that uses spectral graph wavelet transforms. Single-scale or multiscale graph wavelet transforms are employed to introduce local smoothness on different scales into the reconstructed images. The proposed approach relies on viewing finite-element meshes as undirected graphs and applying wavelet transforms derived from spectral graph theory. Reconstruction results from simulations, a phantom experiment, and patient data suggest that our algorithm is more robust to noise and produces more reliable images.

Low SWaP multispectral sensors using dichroic filter arrays

Science.gov (United States)

Dougherty, John; Varghese, Ron

2015-06-01

The benefits of multispectral imaging are well established in a variety of applications including remote sensing, authentication, satellite and aerial surveillance, machine vision, biomedical, and other scientific and industrial uses. However, many of the potential solutions require more compact, robust, and cost-effective cameras to realize these benefits. The next generation of multispectral sensors and cameras needs to deliver improvements in size, weight, power, portability, and spectral band customization to support widespread deployment for a variety of purpose-built aerial, unmanned, and scientific applications. A novel implementation uses micro-patterning of dichroic filters1 into Bayer and custom mosaics, enabling true real-time multispectral imaging with simultaneous multi-band image acquisition. Consistent with color image processing, individual spectral channels are de-mosaiced with each channel providing an image of the field of view. This approach can be implemented across a variety of wavelength ranges and on a variety of detector types including linear, area, silicon, and InGaAs. This dichroic filter array approach can also reduce payloads and increase range for unmanned systems, with the capability to support both handheld and autonomous systems. Recent examples and results of 4 band RGB + NIR dichroic filter arrays in multispectral cameras are discussed. Benefits and tradeoffs of multispectral sensors using dichroic filter arrays are compared with alternative approaches - including their passivity, spectral range, customization options, and scalable production.

Pesticide residue quantification analysis by hyperspectral imaging sensors

Science.gov (United States)

Liao, Yuan-Hsun; Lo, Wei-Sheng; Guo, Horng-Yuh; Kao, Ching-Hua; Chou, Tau-Meu; Chen, Junne-Jih; Wen, Chia-Hsien; Lin, Chinsu; Chen, Hsian-Min; Ouyang, Yen-Chieh; Wu, Chao-Cheng; Chen, Shih-Yu; Chang, Chein-I.

2015-05-01

Pesticide residue detection in agriculture crops is a challenging issue and is even more difficult to quantify pesticide residue resident in agriculture produces and fruits. This paper conducts a series of base-line experiments which are particularly designed for three specific pesticides commonly used in Taiwan. The materials used for experiments are single leaves of vegetable produces which are being contaminated by various amount of concentration of pesticides. Two sensors are used to collected data. One is Fourier Transform Infrared (FTIR) spectroscopy. The other is a hyperspectral sensor, called Geophysical and Environmental Research (GER) 2600 spectroradiometer which is a batteryoperated field portable spectroradiometer with full real-time data acquisition from 350 nm to 2500 nm. In order to quantify data with different levels of pesticide residue concentration, several measures for spectral discrimination are developed. Mores specifically, new measures for calculating relative power between two sensors are particularly designed to be able to evaluate effectiveness of each of sensors in quantifying the used pesticide residues. The experimental results show that the GER is a better sensor than FTIR in the sense of pesticide residue quantification.

INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES

Directory of Open Access Journals (Sweden)

H. Shen

2012-08-01

Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.

Ageing effects on image sensors due to terrestrial cosmic radiation

NARCIS (Netherlands)

Nampoothiri, G.G.; Horemans, M.L.R.; Theuwissen, A.J.P.

2011-01-01

We analyze the “ageing” effect on image sensors introduced by neutrons present in natural (terrestrial) cosmic environment. The results obtained at sea level are corroborated for the first time with accelerated neutron beam tests and for various image sensor operation conditions. The results reveal

CMOS Imaging of Temperature Effects on Pin-Printed Xerogel Sensor Microarrays.

Science.gov (United States)

Lei Yao; Ka Yi Yung; Chodavarapu, Vamsy P; Bright, Frank V

2011-04-01

In this paper, we study the effect of temperature on the operation and performance of a xerogel-based sensor microarrays coupled to a complementary metal-oxide semiconductor (CMOS) imager integrated circuit (IC) that images the photoluminescence response from the sensor microarray. The CMOS imager uses a 32 × 32 (1024 elements) array of active pixel sensors and each pixel includes a high-gain phototransistor to convert the detected optical signals into electrical currents. A correlated double sampling circuit and pixel address/digital control/signal integration circuit are also implemented on-chip. The CMOS imager data are read out as a serial coded signal. The sensor system uses a light-emitting diode to excite target analyte responsive organometallic luminophores doped within discrete xerogel-based sensor elements. As a proto type, we developed a 3 × 3 (9 elements) array of oxygen (O2) sensors. Each group of three sensor elements in the array (arranged in a column) is designed to provide a different and specific sensitivity to the target gaseous O2 concentration. This property of multiple sensitivities is achieved by using a mix of two O2 sensitive luminophores in each pin-printed xerogel sensor element. The CMOS imager is designed to be low noise and consumes a static power of 320.4 μW and an average dynamic power of 624.6 μW when operating at 100-Hz sampling frequency and 1.8-V dc power supply.

Characterization of modulated time-of-flight range image sensors

Science.gov (United States)

Payne, Andrew D.; Dorrington, Adrian A.; Cree, Michael J.; Carnegie, Dale A.

2009-01-01

A number of full field image sensors have been developed that are capable of simultaneously measuring intensity and distance (range) for every pixel in a given scene using an indirect time-of-flight measurement technique. A light source is intensity modulated at a frequency between 10-100 MHz, and an image sensor is modulated at the same frequency, synchronously sampling light reflected from objects in the scene (homodyne detection). The time of flight is manifested as a phase shift in the illumination modulation envelope, which can be determined from the sampled data simultaneously for each pixel in the scene. This paper presents a method of characterizing the high frequency modulation response of these image sensors, using a pico-second laser pulser. The characterization results allow the optimal operating parameters, such as the modulation frequency, to be identified in order to maximize the range measurement precision for a given sensor. A number of potential sources of error exist when using these sensors, including deficiencies in the modulation waveform shape, duty cycle, or phase, resulting in contamination of the resultant range data. From the characterization data these parameters can be identified and compensated for by modifying the sensor hardware or through post processing of the acquired range measurements.

X-ray spectral decomposition imaging system

Energy Technology Data Exchange (ETDEWEB)

1977-07-27

Projection measurements are made of the transmitted X-ray beam in low and high energy regions. These are combined in a non-linear processor to produce atomic-number-dependent and density-dependent projection information. This information is used to provide cross-sectional images which are free of spectral-shift artifacts and completely define the specific material properties. The invention described herein was made in the course of work under a grant from the Department of Health, Education, and Welfare.

A spatial-spectral approach for deriving high signal quality eigenvectors for remote sensing image transformations

DEFF Research Database (Denmark)

Rogge, Derek; Bachmann, Martin; Rivard, Benoit

2014-01-01

Spectral decorrelation (transformations) methods have long been used in remote sensing. Transformation of the image data onto eigenvectors that comprise physically meaningful spectral properties (signal) can be used to reduce the dimensionality of hyperspectral images as the number of spectrally...... distinct signal sources composing a given hyperspectral scene is generally much less than the number of spectral bands. Determining eigenvectors dominated by signal variance as opposed to noise is a difficult task. Problems also arise in using these transformations on large images, multiple flight...... and spectral subsampling to the data, which is accomplished by deriving a limited set of eigenvectors for spatially contiguous subsets. These subset eigenvectors are compiled together to form a new noise reduced data set, which is subsequently used to derive a set of global orthogonal eigenvectors. Data from...

Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: Wavelength adaptive spectral mixture analysis

Science.gov (United States)

Somers, B.; Asner, G. P.

2014-09-01

The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phenological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach in MESMA, our modified Wavelength Adaptive Spectral Mixture Analysis (WASMA) approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a Cohen's Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA (Kappa = 0.54; p-value < 0.05. The flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.

Multispectral simulation environment for modeling low-light-level sensor systems

Science.gov (United States)

Ientilucci, Emmett J.; Brown, Scott D.; Schott, John R.; Raqueno, Rolando V.

1998-11-01

Image intensifying cameras have been found to be extremely useful in low-light-level (LLL) scenarios including military night vision and civilian rescue operations. These sensors utilize the available visible region photons and an amplification process to produce high contrast imagery. It has been demonstrated that processing techniques can further enhance the quality of this imagery. For example, fusion with matching thermal IR imagery can improve image content when very little visible region contrast is available. To aid in the improvement of current algorithms and the development of new ones, a high fidelity simulation environment capable of producing radiometrically correct multi-band imagery for low- light-level conditions is desired. This paper describes a modeling environment attempting to meet these criteria by addressing the task as two individual components: (1) prediction of a low-light-level radiance field from an arbitrary scene, and (2) simulation of the output from a low- light-level sensor for a given radiance field. The radiance prediction engine utilized in this environment is the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model which is a first principles based multi-spectral synthetic image generation model capable of producing an arbitrary number of bands in the 0.28 to 20 micrometer region. The DIRSIG model is utilized to produce high spatial and spectral resolution radiance field images. These images are then processed by a user configurable multi-stage low-light-level sensor model that applies the appropriate noise and modulation transfer function (MTF) at each stage in the image processing chain. This includes the ability to reproduce common intensifying sensor artifacts such as saturation and 'blooming.' Additionally, co-registered imagery in other spectral bands may be simultaneously generated for testing fusion and exploitation algorithms. This paper discusses specific aspects of the DIRSIG radiance prediction for low

Spectral CT imaging in patients with Budd-Chiari syndrome: investigation of image quality.

Science.gov (United States)

Su, Lei; Dong, Junqiang; Sun, Qiang; Liu, Jie; Lv, Peijie; Hu, Lili; Yan, Liangliang; Gao, Jianbo

2014-11-01

To assess the image quality of monochromatic imaging from spectral CT in patients with Budd-Chiari syndrome (BCS), fifty patients with BCS underwent spectral CT to generate conventional 140 kVp polychromatic images (group A) and monochromatic images, with energy levels from 40 to 80, 40 + 70, and 50 + 70 keV fusion images (group B) during the portal venous phase (PVP) and the hepatic venous phase (HVP). Two-sample t tests compared vessel-to-liver contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) for the portal vein (PV), hepatic vein (HV), inferior vena cava. Readers' subjective evaluations of the image quality were recorded. The highest SNR values in group B were distributed at 50 keV; the highest CNR values in group B were distributed at 40 keV. The higher CNR values and SNR values were obtained though PVP of PV (SNR 18.39 ± 6.13 vs. 10.56 ± 3.31, CNR 7.81 ± 3.40 vs. 3.58 ± 1.31) and HVP of HV (3.89 ± 2.08 vs. 1.27 ± 1.55) in the group B; the lower image noise for group B was at 70 keV and 50 + 70 keV (15.54 ± 8.39 vs. 18.40 ± 4.97, P = 0.0004 and 18.97 ± 7.61 vs. 18.40 ± 4.97, P = 0.0691); the results show that the 50 + 70 keV fusion image quality was better than that in group A. Monochromatic energy levels of 40-70, 40 + 70, and 50 + 70 keV fusion image can increase vascular contrast and that will be helpful for the diagnosis of BCS, we select the 50 + 70 keV fusion image to acquire the best BCS images.

Three dimensional multi perspective imaging with randomly distributed sensors

International Nuclear Information System (INIS)

DaneshPanah, Mehdi; Javidi, Bahrain

2008-01-01

In this paper, we review a three dimensional (3D) passive imaging system that exploits the visual information captured from the scene from multiple perspectives to reconstruct the scene voxel by voxel in 3D space. The primary contribution of this work is to provide a computational reconstruction scheme based on randomly distributed sensor locations in space. In virtually all of multi perspective techniques (e.g. integral imaging, synthetic aperture integral imaging, etc), there is an implicit assumption that the sensors lie on a simple, regular pickup grid. Here, we relax this assumption and suggest a computational reconstruction framework that unifies the available methods as its special cases. The importance of this work is that it enables three dimensional imaging technology to be implemented in a multitude of novel application domains such as 3D aerial imaging, collaborative imaging, long range 3D imaging and etc, where sustaining a regular pickup grid is not possible and/or the parallax requirements call for a irregular or sparse synthetic aperture mode. Although the sensors can be distributed in any random arrangement, we assume that the pickup position is measured at the time of capture of each elemental image. We demonstrate the feasibility of the methods proposed here by experimental results.

SENSOR CORRECTION AND RADIOMETRIC CALIBRATION OF A 6-BAND MULTISPECTRAL IMAGING SENSOR FOR UAV REMOTE SENSING

Directory of Open Access Journals (Sweden)

J. Kelcey

2012-07-01

Full Text Available The increased availability of unmanned aerial vehicles (UAVs has resulted in their frequent adoption for a growing range of remote sensing tasks which include precision agriculture, vegetation surveying and fine-scale topographic mapping. The development and utilisation of UAV platforms requires broad technical skills covering the three major facets of remote sensing: data acquisition, data post-processing, and image analysis. In this study, UAV image data acquired by a miniature 6-band multispectral imaging sensor was corrected and calibrated using practical image-based data post-processing techniques. Data correction techniques included dark offset subtraction to reduce sensor noise, flat-field derived per-pixel look-up-tables to correct vignetting, and implementation of the Brown- Conrady model to correct lens distortion. Radiometric calibration was conducted with an image-based empirical line model using pseudo-invariant features (PIFs. Sensor corrections and radiometric calibration improve the quality of the data, aiding quantitative analysis and generating consistency with other calibrated datasets.

Accurate reconstruction of hyperspectral images from compressive sensing measurements

Science.gov (United States)

Greer, John B.; Flake, J. C.

2013-05-01

The emerging field of Compressive Sensing (CS) provides a new way to capture data by shifting the heaviest burden of data collection from the sensor to the computer on the user-end. This new means of sensing requires fewer measurements for a given amount of information than traditional sensors. We investigate the efficacy of CS for capturing HyperSpectral Imagery (HSI) remotely. We also introduce a new family of algorithms for constructing HSI from CS measurements with Split Bregman Iteration [Goldstein and Osher,2009]. These algorithms combine spatial Total Variation (TV) with smoothing in the spectral dimension. We examine models for three different CS sensors: the Coded Aperture Snapshot Spectral Imager-Single Disperser (CASSI-SD) [Wagadarikar et al.,2008] and Dual Disperser (CASSI-DD) [Gehm et al.,2007] cameras, and a hypothetical random sensing model closer to CS theory, but not necessarily implementable with existing technology. We simulate the capture of remotely sensed images by applying the sensor forward models to well-known HSI scenes - an AVIRIS image of Cuprite, Nevada and the HYMAP Urban image. To measure accuracy of the CS models, we compare the scenes constructed with our new algorithm to the original AVIRIS and HYMAP cubes. The results demonstrate the possibility of accurately sensing HSI remotely with significantly fewer measurements than standard hyperspectral cameras.

Study of x-ray CCD image sensor and application

Science.gov (United States)

Wang, Shuyun; Li, Tianze

2008-12-01

In this paper, we expounded the composing, specialty, parameter, its working process, key techniques and methods for charge coupled devices (CCD) twice value treatment. Disposal process for CCD video signal quantification was expatiated; X-ray image intensifier's constitutes, function of constitutes, coupling technique of X-ray image intensifier and CCD were analyzed. We analyzed two effective methods to reduce the harm to human beings when X-ray was used in the medical image. One was to reduce X-ray's radiation and adopt to intensify the image penetrated by X-ray to gain the same effect. The other was to use the image sensor to transfer the images to the safe area for observation. On this base, a new method was presented that CCD image sensor and X-ray image intensifier were combined organically. A practical medical X-ray photo electricity system was designed which can be used in the records and time of the human's penetrating images. The system was mainly made up with the medical X-ray, X-ray image intensifier, CCD vidicon with high resolution, image processor, display and so on. Its characteristics are: change the invisible X-ray into the visible light image; output the vivid images; short image recording time etc. At the same time we analyzed the main aspects which affect the system's resolution. Medical photo electricity system using X-ray image sensor can reduce the X-ray harm to human sharply when it is used in the medical diagnoses. At last we analyzed and looked forward the system's application in medical engineering and the related fields.

Element-specific spectral imaging of multiple contrast agents: a phantom study

Science.gov (United States)

Panta, R. K.; Bell, S. T.; Healy, J. L.; Aamir, R.; Bateman, C. J.; Moghiseh, M.; Butler, A. P. H.; Anderson, N. G.

2018-02-01

This work demonstrates the feasibility of simultaneous discrimination of multiple contrast agents based on their element-specific and energy-dependent X-ray attenuation properties using a pre-clinical photon-counting spectral CT. We used a photon-counting based pre-clinical spectral CT scanner with four energy thresholds to measure the X-ray attenuation properties of various concentrations of iodine (9, 18 and 36 mg/ml), gadolinium (2, 4 and 8 mg/ml) and gold (2, 4 and 8 mg/ml) based contrast agents, calcium chloride (140 and 280 mg/ml) and water. We evaluated the spectral imaging performances of different energy threshold schemes between 25 to 82 keV at 118 kVp, based on K-factor and signal-to-noise ratio and ranked them. K-factor was defined as the X-ray attenuation in the K-edge containing energy range divided by the X-ray attenuation in the preceding energy range, expressed as a percentage. We evaluated the effectiveness of the optimised energy selection to discriminate all three contrast agents in a phantom of 33 mm diameter. A photon-counting spectral CT using four energy thresholds of 27, 33, 49 and 81 keV at 118 kVp simultaneously discriminated three contrast agents based on iodine, gadolinium and gold at various concentrations using their K-edge and energy-dependent X-ray attenuation features in a single scan. A ranking method to evaluate spectral imaging performance enabled energy thresholds to be optimised to discriminate iodine, gadolinium and gold contrast agents in a single spectral CT scan. Simultaneous discrimination of multiple contrast agents in a single scan is likely to open up new possibilities of improving the accuracy of disease diagnosis by simultaneously imaging multiple bio-markers each labelled with a nano-contrast agent.

A Wireless Sensor Network for Vineyard Monitoring That Uses Image Processing

Science.gov (United States)

Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

2011-01-01

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis. PMID:22163948

A wireless sensor network for vineyard monitoring that uses image processing.

Science.gov (United States)

Lloret, Jaime; Bosch, Ignacio; Sendra, Sandra; Serrano, Arturo

2011-01-01

The first step to detect when a vineyard has any type of deficiency, pest or disease is to observe its stems, its grapes and/or its leaves. To place a sensor in each leaf of every vineyard is obviously not feasible in terms of cost and deployment. We should thus look for new methods to detect these symptoms precisely and economically. In this paper, we present a wireless sensor network where each sensor node takes images from the field and internally uses image processing techniques to detect any unusual status in the leaves. This symptom could be caused by a deficiency, pest, disease or other harmful agent. When it is detected, the sensor node sends a message to a sink node through the wireless sensor network in order to notify the problem to the farmer. The wireless sensor uses the IEEE 802.11 a/b/g/n standard, which allows connections from large distances in open air. This paper describes the wireless sensor network design, the wireless sensor deployment, how the node processes the images in order to monitor the vineyard, and the sensor network traffic obtained from a test bed performed in a flat vineyard in Spain. Although the system is not able to distinguish between deficiency, pest, disease or other harmful agents, a symptoms image database and a neuronal network could be added in order learn from the experience and provide an accurate problem diagnosis.

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

Science.gov (United States)

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

Low-power high-accuracy micro-digital sun sensor by means of a CMOS image sensor

NARCIS (Netherlands)

Xie, N.; Theuwissen, A.J.P.

2013-01-01

A micro-digital sun sensor (?DSS) is a sun detector which senses a satellite’s instant attitude angle with respect to the sun. The core of this sensor is a system-on-chip imaging chip which is referred to as APS+. The APS+ integrates a CMOS active pixel sensor (APS) array of 368×368??pixels , a

Camera sensor arrangement for crop/weed detection accuracy in agronomic images.

Science.gov (United States)

Romeo, Juan; Guerrero, José Miguel; Montalvo, Martín; Emmi, Luis; Guijarro, María; Gonzalez-de-Santos, Pablo; Pajares, Gonzalo

2013-04-02

In Precision Agriculture, images coming from camera-based sensors are commonly used for weed identification and crop line detection, either to apply specific treatments or for vehicle guidance purposes. Accuracy of identification and detection is an important issue to be addressed in image processing. There are two main types of parameters affecting the accuracy of the images, namely: (a) extrinsic, related to the sensor's positioning in the tractor; (b) intrinsic, related to the sensor specifications, such as CCD resolution, focal length or iris aperture, among others. Moreover, in agricultural applications, the uncontrolled illumination, existing in outdoor environments, is also an important factor affecting the image accuracy. This paper is exclusively focused on two main issues, always with the goal to achieve the highest image accuracy in Precision Agriculture applications, making the following two main contributions: (a) camera sensor arrangement, to adjust extrinsic parameters and (b) design of strategies for controlling the adverse illumination effects.

Development of low-dose photon-counting contrast-enhanced tomosynthesis with spectral imaging.

Science.gov (United States)

Schmitzberger, Florian F; Fallenberg, Eva Maria; Lawaczeck, Rüdiger; Hemmendorff, Magnus; Moa, Elin; Danielsson, Mats; Bick, Ulrich; Diekmann, Susanne; Pöllinger, Alexander; Engelken, Florian J; Diekmann, Felix

2011-05-01

To demonstrate the feasibility of low-dose photon-counting tomosynthesis in combination with a contrast agent (contrast material-enhanced tomographic mammography) for the differentiation of breast cancer. All studies were approved by the institutional review board, and all patients provided written informed consent. A phantom model with wells of iodinated contrast material (3 mg of iodine per milliliter) 1, 2, 5, 10, and 15 mm in diameter was assessed. Nine patients with malignant lesions and one with a high-risk lesion (atypical papilloma) were included (all women; mean age, 60.7 years). A multislit photon-counting tomosynthesis system was utilized (spectral imaging) to produce both low- and high-energy tomographic data (below and above the k edge of iodine, respectively) in a single scan, which allowed for dual-energy visualization of iodine. Images were obtained prior to contrast material administration and 120 and 480 seconds after contrast material administration. Four readers independently assessed the images along with conventional mammograms, ultrasonographic images, and magnetic resonance images. Glandular dose was estimated. Contrast agent was visible in the phantom model with simulated spherical tumor diameters as small as 5 mm. The average glandular dose was measured as 0.42 mGy per complete spectral imaging tomosynthesis scan of one breast. Because there were three time points (prior to contrast medium administration and 120 and 480 seconds after contrast medium administration), this resulted in a total dose of 1.26 mGy for the whole procedure in the breast with the abnormality. Seven of 10 cases were categorized as Breast Imaging Reporting and Data System score of 4 or higher by all four readers when reviewing spectral images in combination with mammograms. One lesion near the chest wall was not captured on the spectral image because of a positioning problem. The use of contrast-enhanced tomographic mammography has been demonstrated successfully in

Evaluating visibility of age spot and freckle based on simulated spectral reflectance distribution and facial color image

Science.gov (United States)

Hirose, Misa; Toyota, Saori; Tsumura, Norimichi

2018-02-01

In this research, we evaluate the visibility of age spot and freckle with changing the blood volume based on simulated spectral reflectance distribution and the actual facial color images, and compare these results. First, we generate three types of spatial distribution of age spot and freckle in patch-like images based on the simulated spectral reflectance. The spectral reflectance is simulated using Monte Carlo simulation of light transport in multi-layered tissue. Next, we reconstruct the facial color image with changing the blood volume. We acquire the concentration distribution of melanin, hemoglobin and shading components by applying the independent component analysis on a facial color image. We reproduce images using the obtained melanin and shading concentration and the changed hemoglobin concentration. Finally, we evaluate the visibility of pigmentations using simulated spectral reflectance distribution and facial color images. In the result of simulated spectral reflectance distribution, we found that the visibility became lower as the blood volume increases. However, we can see that a specific blood volume reduces the visibility of the actual pigmentations from the result of the facial color images.

Space-based infrared sensors of space target imaging effect analysis

Science.gov (United States)

Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang

2018-02-01

Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.

Single Photon Counting Performance and Noise Analysis of CMOS SPAD-Based Image Sensors

Science.gov (United States)

Dutton, Neale A. W.; Gyongy, Istvan; Parmesan, Luca; Henderson, Robert K.

2016-01-01

SPAD-based solid state CMOS image sensors utilising analogue integrators have attained deep sub-electron read noise (DSERN) permitting single photon counting (SPC) imaging. A new method is proposed to determine the read noise in DSERN image sensors by evaluating the peak separation and width (PSW) of single photon peaks in a photon counting histogram (PCH). The technique is used to identify and analyse cumulative noise in analogue integrating SPC SPAD-based pixels. The DSERN of our SPAD image sensor is exploited to confirm recent multi-photon threshold quanta image sensor (QIS) theory. Finally, various single and multiple photon spatio-temporal oversampling techniques are reviewed. PMID:27447643

ANALYZING SPECTRAL CHARACTERISTICS OF SHADOW AREA FROM ADS-40 HIGH RADIOMETRIC RESOLUTION AERIAL IMAGES

Directory of Open Access Journals (Sweden)

Y.-T. Hsieh

2016-06-01

Full Text Available The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i The DN values in shadow area are much lower than in nonshadow area; (ii DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv The shadow area NIR of vegetation category also shows a strong reflection; (v Generally, vegetation indexes (NDVI still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40 is potential for the extract land cover information of shadow areas.

The lucky image-motion prediction for simple scene observation based soft-sensor technology

Science.gov (United States)

Li, Yan; Su, Yun; Hu, Bin

2015-08-01

High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

Fusion of MODIS Images Using Kriging With External Drift

NARCIS (Netherlands)

Ribeiro Sales, M.H.; Souza, C.M.; Kyriakidis, P.C.

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) has been used in several remote sensing studies, including land, ocean, and atmospheric applications. The advantages of this sensor are its high spectral resolution, with 36 spectral bands; its high revisiting frequency; and its public domain

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

Science.gov (United States)

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Metabolic Mapping of Breast Cancer with Multiphoton Spectral and Lifetime Imaging

Science.gov (United States)

2007-03-01

2002. Spectrally resolved fluorescence lifetime imaging microscopy. Appl. Spec- trosc. 56 :155-166. 38. Becker, W., A. Bergmann, E. Haustein , Z...photon fluores- cence lifetime imaging microscopy of macrophage-mediated antigen processing. J. Microsc. 185 :339-353. 45. Lin, H.J., P. Herman , and

Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

Directory of Open Access Journals (Sweden)

YANG Zhaoxia

2015-07-01

Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing

Directory of Open Access Journals (Sweden)

Cally Gill

2013-09-01

Full Text Available The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.

Science.gov (United States)

He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P

2013-09-18

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Radiometric Correction of Close-Range Spectral Image Blocks Captured Using an Unmanned Aerial Vehicle with a Radiometric Block Adjustment

Directory of Open Access Journals (Sweden)

Eija Honkavaara

2018-02-01

Full Text Available Unmanned airborne vehicles (UAV equipped with novel, miniaturized, 2D frame format hyper- and multispectral cameras make it possible to conduct remote sensing measurements cost-efficiently, with greater accuracy and detail. In the mapping process, the area of interest is covered by multiple, overlapping, small-format 2D images, which provide redundant information about the object. Radiometric correction of spectral image data is important for eliminating any external disturbance from the captured data. Corrections should include sensor, atmosphere and view/illumination geometry (bidirectional reflectance distribution function—BRDF related disturbances. An additional complication is that UAV remote sensing campaigns are often carried out under difficult conditions, with varying illumination conditions and cloudiness. We have developed a global optimization approach for the radiometric correction of UAV image blocks, a radiometric block adjustment. The objective of this study was to implement and assess a combined adjustment approach, including comprehensive consideration of weighting of various observations. An empirical study was carried out using imagery captured using a hyperspectral 2D frame format camera of winter wheat crops. The dataset included four separate flights captured during a 2.5 h time period under sunny weather conditions. As outputs, we calculated orthophoto mosaics using the most nadir images and sampled multiple-view hyperspectral spectra for vegetation sample points utilizing multiple images in the dataset. The method provided an automated tool for radiometric correction, compensating for efficiently radiometric disturbances in the images. The global homogeneity factor improved from 12–16% to 4–6% with the corrections, and a reduction in disturbances could be observed in the spectra of the object points sampled from multiple overlapping images. Residuals in the grey and white reflectance panels were less than 5% of the

Wireless image-data transmission from an implanted image sensor through a living mouse brain by intra body communication

Science.gov (United States)

Hayami, Hajime; Takehara, Hiroaki; Nagata, Kengo; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

2016-04-01

Intra body communication technology allows the fabrication of compact implantable biomedical sensors compared with RF wireless technology. In this paper, we report the fabrication of an implantable image sensor of 625 µm width and 830 µm length and the demonstration of wireless image-data transmission through a brain tissue of a living mouse. The sensor was designed to transmit output signals of pixel values by pulse width modulation (PWM). The PWM signals from the sensor transmitted through a brain tissue were detected by a receiver electrode. Wireless data transmission of a two-dimensional image was successfully demonstrated in a living mouse brain. The technique reported here is expected to provide useful methods of data transmission using micro sized implantable biomedical sensors.

CMOS SPAD-based image sensor for single photon counting and time of flight imaging

OpenAIRE

Dutton, Neale Arthur William

2016-01-01

The facility to capture the arrival of a single photon, is the fundamental limit to the detection of quantised electromagnetic radiation. An image sensor capable of capturing a picture with this ultimate optical and temporal precision is the pinnacle of photo-sensing. The creation of high spatial resolution, single photon sensitive, and time-resolved image sensors in complementary metal oxide semiconductor (CMOS) technology offers numerous benefits in a wide field of applications....

Global Learning Spectral Archive- A new Way to deal with Unknown Urban Spectra -

Science.gov (United States)

Jilge, M.; Heiden, U.; Habermeyer, M.; Jürgens, C.

2015-12-01

Rapid urbanization processes and the need of identifying urban materials demand urban planners and the remote sensing community since years. Urban planners cannot overcome the issue of up-to-date information of urban materials due to time-intensive fieldwork. Hyperspectral remote sensing can facilitate this issue by interpreting spectral signals to provide information of occurring materials. However, the complexity of urban areas and the occurrence of diverse urban materials vary due to regional and cultural aspects as well as the size of a city, which makes identification of surface materials a challenging analysis task. For the various surface material identification approaches, spectral libraries containing pure material spectra are commonly used, which are derived from field, laboratory or the hyperspectral image itself. One of the requirements for successful image analysis is that all spectrally different surface materials are represented by the library. Currently, a universal library, applicable in every urban area worldwide and taking each spectral variability into account, is and will not be existent. In this study, the issue of unknown surface material spectra and the demand of an urban site-specific spectral library is tackled by the development of a learning spectral archive tool. Starting with an incomplete library of labelled image spectra from several German cities, surface materials of pure image pixels will be identified in a hyperspectral image based on a similarity measure (e.g. SID-SAM). Additionally, unknown image spectra of urban objects are identified based on an object- and spectral-based-rule set. The detected unknown surface material spectra are entered with additional metadata, such as regional occurrence into the existing spectral library and thus, are reusable for further studies. Our approach is suitable for pure surface material detection of urban hyperspectral images that is globally applicable by taking incompleteness into account

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

Science.gov (United States)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Quantitative spectral K-edge imaging in preclinical photon-counting x-ray computed tomography.

Science.gov (United States)

de Vries, Anke; Roessl, Ewald; Kneepkens, Esther; Thran, Axel; Brendel, Bernhard; Martens, Gerhard; Proska, Roland; Nicolay, Klaas; Grüll, Holger

2015-04-01

The objective of this study was to investigate the feasibility and the accuracy of spectral computed tomography (spectral CT) to determine the tissue concentrations and localization of high-attenuation, iodine-based contrast agents in mice. Iodine tissue concentrations determined with spectral CT are compared with concentrations measured with single-photon emission computed tomography (SPECT) and inductively coupled plasma mass spectrometry (ICP-MS). All animal procedures were performed according to the US National Institutes of Health principles of laboratory animal care and were approved by the ethical review committee of Maastricht, The Netherlands. Healthy Swiss mice (n = 4) were injected with an iodinated emulsion radiolabeled with indium as multimodal contrast agent for CT and SPECT. The CT and SPECT scans were acquired using a dedicated small-animal SPECT/CT system. Subsequently, scans were performed with a preclinical spectral CT scanner equipped with a photon-counting detector and 6 energy threshold levels. Quantitative data analysis of SPECT and spectral CT scans were obtained using 3-dimensional volumes-of-interest drawing methods. The ICP-MS on dissected organs was performed to determine iodine uptake per organ and was compared with the amounts determined from spectral CT and SPECT. Iodine concentrations obtained with image-processed spectral CT data correlated well with data obtained either with noninvasive SPECT imaging (slope = 0.96, r = 0.75) or with ICP-MS (slope = 0.99, r = 0.89) in tissue samples. This preclinical proof-of-concept study shows the in vivo quantification of iodine concentrations in tissues using spectral CT. Our multimodal imaging approach with spectral CT and SPECT using radiolabeled iodinated emulsions together with ICP-based quantification allows a direct comparison of all methods. Benchmarked against ICP-MS data, spectral CT in the present implementation shows a slight underestimation of organ iodine concentrations compared

Multispectral atmospheric mapping sensor of mesoscale water vapor features

Science.gov (United States)

Menzel, P.; Jedlovec, G.; Wilson, G.; Atkinson, R.; Smith, W.

1985-01-01

The Multispectral atmospheric mapping sensor was checked out for specified spectral response and detector noise performance in the eight visible and three infrared (6.7, 11.2, 12.7 micron) spectral bands. A calibration algorithm was implemented for the infrared detectors. Engineering checkout flights on board the ER-2 produced imagery at 50 m resolution in which water vapor features in the 6.7 micron spectral band are most striking. These images were analyzed on the Man computer Interactive Data Access System (McIDAS). Ground truth and ancillary data was accessed to verify the calibration.

Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance.

Science.gov (United States)

Bautista, Pinky A; Yagi, Yukako

2012-05-01

Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.

Simulation and analysis of Au-MgF2 structure in plasmonic sensor in near infrared spectral region

Science.gov (United States)

Sharma, Anuj K.

2018-05-01

Plasmonic sensor based on metal-dielectric combination of gold and MgF2 layers is studied in near infrared (NIR) spectral region. An emphasis is given on the effect of variable thickness of MgF2 layer in combination with operating wavelength and gold layer thickness on the sensor's performance in NIR. It is established that the variation in MgF2 thickness in connection with plasmon penetration depth leads to significant variation in sensor's performance. The analysis leads to a conclusion that taking smaller values of MgF2 layer thickness and operating at longer NIR wavelength leads to enhanced sensing performance. Also, fluoride glass can provide better sensing performance than chalcogenide glass and silicon substrate.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis

OpenAIRE

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-01-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in can...

Integrated optics refractometry: sensitivity in relation to spectral shifts

NARCIS (Netherlands)

Hoekstra, Hugo; Hammer, M.

2013-01-01

A new variant of the Vernier-effect based sensor reported in ref. 1 is introduced. Both sensor types may show a huge index induced spectral shift. It will be shown in a poster presentation that with such sensors, as well as with surface plasmon based sensors, the constraints on the spectral

Image quality of conventional images of dual-layer SPECTRAL CT: a phantom study.

Science.gov (United States)

van Ommen, F; Bennink, E; Vlassenbroek, A; Dankbaar, J W; Schilham, A M R; Viergever, M A; de Jong, H W A M

2018-05-10

Spectral CT using a dual layer detector offers the possibility of retrospectively introducing spectral information to conventional CT images. In theory, the dual-layer technology should not come with a dose or image quality penalty for conventional images. In this study, we evaluate the influence of a dual-layer detector (IQon Spectral CT, Philips) on the image quality of conventional CT images, by comparing these images with those of a conventional but otherwise technically comparable single-layer CT scanner (Brilliance iCT, Philips), by means of phantom experiments. For both CT scanners conventional CT images were acquired using four adult scanning protocols: i) body helical, ii) body axial, iii) head helical and iv) head axial. A CATPHAN 600 phantom was scanned to conduct an assessment of image quality metrics at equivalent (CTDI) dose levels. Noise was characterized by means of noise power spectra (NPS) and standard deviation (SD) of a uniform region, and spatial resolution was evaluated with modulation transfer functions (MTF) of a tungsten wire. In addition, contrast-to-noise ratio (CNR), image uniformity, CT number linearity, slice thickness, slice spacing, and spatial linearity were measured and evaluated. Additional measurements of CNR, resolution and noise were performed in two larger phantoms. The resolution levels at 50%, 10% and 5% MTF of the iCT and IQon showed small but significant differences up to 0.25 lp/cm for body scans, and up to 0.2 lp/cm for head scans in favor of the IQon. The iCT and IQon showed perfect CT linearity for body scans, but for head scans both scanners showed an underestimation of the CT numbers of materials with a high opacity. Slice thickness was slightly overestimated for both scanners. Slice spacing was comparable and reconstructed correctly. In addition, spatial linearity was excellent for both scanners, with a maximum error of 0.11 mm. CNR was higher on the IQon compared to the iCT for both normal and larger phantoms with

Validation of Spectral Unmixing Results from Informed Non-Negative Matrix Factorization (INMF) of Hyperspectral Imagery

Science.gov (United States)

Wright, L.; Coddington, O.; Pilewskie, P.

2017-12-01

Hyperspectral instruments are a growing class of Earth observing sensors designed to improve remote sensing capabilities beyond discrete multi-band sensors by providing tens to hundreds of continuous spectral channels. Improved spectral resolution, range and radiometric accuracy allow the collection of large amounts of spectral data, facilitating thorough characterization of both atmospheric and surface properties. We describe the development of an Informed Non-Negative Matrix Factorization (INMF) spectral unmixing method to exploit this spectral information and separate atmospheric and surface signals based on their physical sources. INMF offers marked benefits over other commonly employed techniques including non-negativity, which avoids physically impossible results; and adaptability, which tailors the method to hyperspectral source separation. The INMF algorithm is adapted to separate contributions from physically distinct sources using constraints on spectral and spatial variability, and library spectra to improve the initial guess. Using this INMF algorithm we decompose hyperspectral imagery from the NASA Hyperspectral Imager for the Coastal Ocean (HICO), with a focus on separating surface and atmospheric signal contributions. HICO's coastal ocean focus provides a dataset with a wide range of atmospheric and surface conditions. These include atmospheres with varying aerosol optical thicknesses and cloud cover. HICO images also provide a range of surface conditions including deep ocean regions, with only minor contributions from the ocean surfaces; and more complex shallow coastal regions with contributions from the seafloor or suspended sediments. We provide extensive comparison of INMF decomposition results against independent measurements of physical properties. These include comparison against traditional model-based retrievals of water-leaving, aerosol, and molecular scattering radiances and other satellite products, such as aerosol optical thickness from

A Biologically Inspired CMOS Image Sensor

CERN Document Server

Sarkar, Mukul

2013-01-01

Biological systems are a source of inspiration in the development of small autonomous sensor nodes. The two major types of optical vision systems found in nature are the single aperture human eye and the compound eye of insects. The latter are among the most compact and smallest vision sensors. The eye is a compound of individual lenses with their own photoreceptor arrays.  The visual system of insects allows them to fly with a limited intelligence and brain processing power. A CMOS image sensor replicating the perception of vision in insects is discussed and designed in this book for industrial (machine vision) and medical applications. The CMOS metal layer is used to create an embedded micro-polarizer able to sense polarization information. This polarization information is shown to be useful in applications like real time material classification and autonomous agent navigation. Further the sensor is equipped with in pixel analog and digital memories which allow variation of the dynamic range and in-pixel b...

Quantitative imaging of excised osteoarthritic cartilage using spectral CT

Energy Technology Data Exchange (ETDEWEB)

Rajendran, Kishore; Bateman, Christopher J.; Younis, Raja Aamir; De Ruiter, Niels J.A.; Ramyar, Mohsen; Anderson, Nigel G. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); Loebker, Caroline [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); University of Twente, Department of Developmental BioEngineering, Enschede (Netherlands); Schon, Benjamin S.; Hooper, Gary J.; Woodfield, Tim B.F. [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); Chernoglazov, Alex I. [University of Canterbury, Human Interface Technology Laboratory New Zealand, Christchurch (New Zealand); Butler, Anthony P.H. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); MARS Bioimaging, Christchurch (New Zealand)

2017-01-15

To quantify iodine uptake in articular cartilage as a marker of glycosaminoglycan (GAG) content using multi-energy spectral CT. We incubated a 25-mm strip of excised osteoarthritic human tibial plateau in 50 % ionic iodine contrast and imaged it using a small-animal spectral scanner with a cadmium telluride photon-processing detector to quantify the iodine through the thickness of the articular cartilage. We imaged both spectroscopic phantoms and osteoarthritic tibial plateau samples. The iodine distribution as an inverse marker of GAG content was presented in the form of 2D and 3D images after applying a basis material decomposition technique to separate iodine in cartilage from bone. We compared this result with a histological section stained for GAG. The iodine in cartilage could be distinguished from subchondral bone and quantified using multi-energy CT. The articular cartilage showed variation in iodine concentration throughout its thickness which appeared to be inversely related to GAG distribution observed in histological sections. Multi-energy CT can quantify ionic iodine contrast (as a marker of GAG content) within articular cartilage and distinguish it from bone by exploiting the energy-specific attenuation profiles of the associated materials. (orig.)

Technical guidance for the development of a solid state image sensor for human low vision image warping

Science.gov (United States)

Vanderspiegel, Jan

1994-01-01

This report surveys different technologies and approaches to realize sensors for image warping. The goal is to study the feasibility, technical aspects, and limitations of making an electronic camera with special geometries which implements certain transformations for image warping. This work was inspired by the research done by Dr. Juday at NASA Johnson Space Center on image warping. The study has looked into different solid-state technologies to fabricate image sensors. It is found that among the available technologies, CMOS is preferred over CCD technology. CMOS provides more flexibility to design different functions into the sensor, is more widely available, and is a lower cost solution. By using an architecture with row and column decoders one has the added flexibility of addressing the pixels at random, or read out only part of the image.

Sparse Detector Imaging Sensor with Two-Class Silhouette Classification

Directory of Open Access Journals (Sweden)

David Russomanno

2008-12-01

Full Text Available This paper presents the design and test of a simple active near-infrared sparse detector imaging sensor. The prototype of the sensor is novel in that it can capture remarkable silhouettes or profiles of a wide-variety of moving objects, including humans, animals, and vehicles using a sparse detector array comprised of only sixteen sensing elements deployed in a vertical configuration. The prototype sensor was built to collect silhouettes for a variety of objects and to evaluate several algorithms for classifying the data obtained from the sensor into two classes: human versus non-human. Initial tests show that the classification of individually sensed objects into two classes can be achieved with accuracy greater than ninety-nine percent (99% with a subset of the sixteen detectors using a representative dataset consisting of 512 signatures. The prototype also includes a Webservice interface such that the sensor can be tasked in a network-centric environment. The sensor appears to be a low-cost alternative to traditional, high-resolution focal plane array imaging sensors for some applications. After a power optimization study, appropriate packaging, and testing with more extensive datasets, the sensor may be a good candidate for deployment in vast geographic regions for a myriad of intelligent electronic fence and persistent surveillance applications, including perimeter security scenarios.

Highly curved image sensors: a practical approach for improved optical performance.

Science.gov (United States)

Guenter, Brian; Joshi, Neel; Stoakley, Richard; Keefe, Andrew; Geary, Kevin; Freeman, Ryan; Hundley, Jake; Patterson, Pamela; Hammon, David; Herrera, Guillermo; Sherman, Elena; Nowak, Andrew; Schubert, Randall; Brewer, Peter; Yang, Louis; Mott, Russell; McKnight, Geoff

2017-06-12

The significant optical and size benefits of using a curved focal surface for imaging systems have been well studied yet never brought to market for lack of a high-quality, mass-producible, curved image sensor. In this work we demonstrate that commercial silicon CMOS image sensors can be thinned and formed into accurate, highly curved optical surfaces with undiminished functionality. Our key development is a pneumatic forming process that avoids rigid mechanical constraints and suppresses wrinkling instabilities. A combination of forming-mold design, pressure membrane elastic properties, and controlled friction forces enables us to gradually contact the die at the corners and smoothly press the sensor into a spherical shape. Allowing the die to slide into the concave target shape enables a threefold increase in the spherical curvature over prior approaches having mechanical constraints that resist deformation, and create a high-stress, stretch-dominated state. Our process creates a bridge between the high precision and low-cost but planar CMOS process, and ideal non-planar component shapes such as spherical imagers for improved optical systems. We demonstrate these curved sensors in prototype cameras with custom lenses, measuring exceptional resolution of 3220 line-widths per picture height at an aperture of f/1.2 and nearly 100% relative illumination across the field. Though we use a 1/2.3" format image sensor in this report, we also show this process is generally compatible with many state of the art imaging sensor formats. By example, we report photogrammetry test data for an APS-C sized silicon die formed to a 30° subtended spherical angle. These gains in sharpness and relative illumination enable a new generation of ultra-high performance, manufacturable, digital imaging systems for scientific, industrial, and artistic use.

X-ray imaging characterization of active edge silicon pixel sensors

International Nuclear Information System (INIS)

Ponchut, C; Ruat, M; Kalliopuska, J

2014-01-01

The aim of this work was the experimental characterization of edge effects in active-edge silicon pixel sensors, in the frame of X-ray pixel detectors developments for synchrotron experiments. We produced a set of active edge pixel sensors with 300 to 500 μm thickness, edge widths ranging from 100 μm to 150 μm, and n or p pixel contact types. The sensors with 256 × 256 pixels and 55 × 55 μm 2 pixel pitch were then bump-bonded to Timepix readout chips for X-ray imaging measurements. The reduced edge widths makes the edge pixels more sensitive to the electrical field distribution at the sensor boundaries. We characterized this effect by mapping the spatial response of the sensor edges with a finely focused X-ray synchrotron beam. One of the samples showed a distortion-free response on all four edges, whereas others showed variable degrees of distortions extending at maximum to 300 micron from the sensor edge. An application of active edge pixel sensors to coherent diffraction imaging with synchrotron beams is described

Terrain Extraction by Integrating Terrestrial Laser Scanner Data and Spectral Information

Science.gov (United States)

Lau, C. L.; Halim, S.; Zulkepli, M.; Azwan, A. M.; Tang, W. L.; Chong, A. K.

2015-10-01

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction.

Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

Science.gov (United States)

Lazcano, R.; Madroñal, D.; Fabelo, H.; Ortega, S.; Salvador, R.; Callicó, G. M.; Juárez, E.; Sanz, C.

2017-10-01

Hyperspectral Imaging (HI) assembles high resolution spectral information from hundreds of narrow bands across the electromagnetic spectrum, thus generating 3D data cubes in which each pixel gathers the spectral information of the reflectance of every spatial pixel. As a result, each image is composed of large volumes of data, which turns its processing into a challenge, as performance requirements have been continuously tightened. For instance, new HI applications demand real-time responses. Hence, parallel processing becomes a necessity to achieve this requirement, so the intrinsic parallelism of the algorithms must be exploited. In this paper, a spatial-spectral classification approach has been implemented using a dataflow language known as RVCCAL. This language represents a system as a set of functional units, and its main advantage is that it simplifies the parallelization process by mapping the different blocks over different processing units. The spatial-spectral classification approach aims at refining the classification results previously obtained by using a K-Nearest Neighbors (KNN) filtering process, in which both the pixel spectral value and the spatial coordinates are considered. To do so, KNN needs two inputs: a one-band representation of the hyperspectral image and the classification results provided by a pixel-wise classifier. Thus, spatial-spectral classification algorithm is divided into three different stages: a Principal Component Analysis (PCA) algorithm for computing the one-band representation of the image, a Support Vector Machine (SVM) classifier, and the KNN-based filtering algorithm. The parallelization of these algorithms shows promising results in terms of computational time, as the mapping of them over different cores presents a speedup of 2.69x when using 3 cores. Consequently, experimental results demonstrate that real-time processing of hyperspectral images is achievable.

Spectral measurements of muzzle flash with multispectral and hyperspectral sensor

Science.gov (United States)

Kastek, M.; Dulski, R.; Trzaskawka, P.; Piątkowski, T.; Polakowski, H.

2011-08-01

The paper presents some practical aspects of the measurements of muzzle flash signatures. Selected signatures of sniper shot in typical scenarios has been presented. Signatures registered during all phases of muzzle flash were analyzed. High precision laboratory measurements were made in a special ballistic laboratory and as a result several flash patterns were registered. The field measurements of a muzzle flash were also performed. During the tests several infrared cameras were used, including the measurement class devices with high accuracy and frame rates. The registrations were made in NWIR, SWIR and LWIR spectral bands simultaneously. An ultra fast visual camera was also used for visible spectra registration. Some typical infrared shot signatures were presented. Beside the cameras, the LWIR imaging spectroradiometer HyperCam was also used during the laboratory experiments and the field tests. The signatures collected by the HyperCam device were useful for the determination of spectral characteristics of the muzzle flash, whereas the analysis of thermal images registered during the tests provided the data on temperature distribution in the flash area. As a result of the measurement session the signatures of several types handguns, machine guns and sniper rifles were obtained which will be used in the development of passive infrared systems for sniper detection.

Chest CT using spectral filtration: radiation dose, image quality, and spectrum of clinical utility

Energy Technology Data Exchange (ETDEWEB)

Braun, Franziska M.; Johnson, Thorsten R.C.; Sommer, Wieland H.; Thierfelder, Kolja M.; Meinel, Felix G. [University Hospital Munich, Institute for Clinical Radiology, Munich (Germany)

2015-06-01

To determine the radiation dose, image quality, and clinical utility of non-enhanced chest CT with spectral filtration. We retrospectively analysed 25 non-contrast chest CT examinations acquired with spectral filtration (tin-filtered Sn100 kVp spectrum) compared to 25 examinations acquired without spectral filtration (120 kV). Radiation metrics were compared. Image noise was measured. Contrast-to-noise-ratio (CNR) and figure-of-merit (FOM) were calculated. Diagnostic confidence for the assessment of various thoracic pathologies was rated by two independent readers. Effective chest diameters were comparable between groups (P = 0.613). In spectral filtration CT, median CTDI{sub vol}, DLP, and size-specific dose estimate (SSDE) were reduced (0.46 vs. 4.3 mGy, 16 vs. 141 mGy*cm, and 0.65 vs. 5.9 mGy, all P < 0.001). Spectral filtration CT had higher image noise (21.3 vs. 13.2 HU, P < 0.001) and lower CNR (47.2 vs. 75.3, P < 0.001), but was more dose-efficient (FOM 10,659 vs. 2,231/mSv, P < 0.001). Diagnostic confidence for parenchymal lung disease and osseous pathologies was lower with spectral filtration CT, but no significant difference was found for pleural pathologies, pulmonary nodules, or pneumonia. Non-contrast chest CT using spectral filtration appears to be sufficient for the assessment of a considerable spectrum of thoracic pathologies, while providing superior dose efficiency, allowing for substantial radiation dose reduction. (orig.)

AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

NARCIS (Netherlands)

Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

2008-01-01

The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

Tomato sorting using independent component analysis on spectral images

NARCIS (Netherlands)

Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

2003-01-01

Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

RADIOMETRIC NORMALIZATION OF LARGE AIRBORNE IMAGE DATA SETS ACQUIRED BY DIFFERENT SENSOR TYPES

Directory of Open Access Journals (Sweden)

S. Gehrke

2016-06-01

Full Text Available Generating seamless mosaics of aerial images is a particularly challenging task when the mosaic comprises a large number of im-ages, collected over longer periods of time and with different sensors under varying imaging conditions. Such large mosaics typically consist of very heterogeneous image data, both spatially (different terrain types and atmosphere and temporally (unstable atmo-spheric properties and even changes in land coverage. We present a new radiometric normalization or, respectively, radiometric aerial triangulation approach that takes advantage of our knowledge about each sensor’s properties. The current implementation supports medium and large format airborne imaging sensors of the Leica Geosystems family, namely the ADS line-scanner as well as DMC and RCD frame sensors. A hierarchical modelling – with parameters for the overall mosaic, the sensor type, different flight sessions, strips and individual images – allows for adaptation to each sensor’s geometric and radiometric properties. Additional parameters at different hierarchy levels can compensate radiome-tric differences of various origins to compensate for shortcomings of the preceding radiometric sensor calibration as well as BRDF and atmospheric corrections. The final, relative normalization is based on radiometric tie points in overlapping images, absolute radiometric control points and image statistics. It is computed in a global least squares adjustment for the entire mosaic by altering each image’s histogram using a location-dependent mathematical model. This model involves contrast and brightness corrections at radiometric fix points with bilinear interpolation for corrections in-between. The distribution of the radiometry fixes is adaptive to each image and generally increases with image size, hence enabling optimal local adaptation even for very long image strips as typi-cally captured by a line-scanner sensor. The normalization approach is implemented in

Photon detection with CMOS sensors for fast imaging

International Nuclear Information System (INIS)

Baudot, J.; Dulinski, W.; Winter, M.; Barbier, R.; Chabanat, E.; Depasse, P.; Estre, N.

2009-01-01

Pixel detectors employed in high energy physics aim to detect single minimum ionizing particle with micrometric positioning resolution. Monolithic CMOS sensors succeed in this task thanks to a low equivalent noise charge per pixel of around 10 to 15 e - , and a pixel pitch varying from 10 to a few 10 s of microns. Additionally, due to the possibility for integration of some data treatment in the sensor itself, readout times of 100μs have been reached for 100 kilo-pixels sensors. These aspects of CMOS sensors are attractive for applications in photon imaging. For X-rays of a few keV, the efficiency is limited to a few % due to the thin sensitive volume. For visible photons, the back-thinned version of CMOS sensor is sensitive to low intensity sources, of a few hundred photons. When a back-thinned CMOS sensor is combined with a photo-cathode, a new hybrid detector results (EBCMOS) and operates as a fast single photon imager. The first EBCMOS was produced in 2007 and demonstrated single photon counting with low dark current capability in laboratory conditions. It has been compared, in two different biological laboratories, with existing CCD-based 2D cameras for fluorescence microscopy. The current EBCMOS sensitivity and frame rate is comparable to existing EMCCDs. On-going developments aim at increasing this frame rate by, at least, an order of magnitude. We report in conclusion, the first test of a new CMOS sensor, LUCY, which reaches 1000 frames per second.

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

Science.gov (United States)

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: Comparison with conventional tube-voltage images.

Science.gov (United States)

Sakabe, Daisuke; Funama, Yoshinori; Taguchi, Katsuyuki; Nakaura, Takeshi; Utsunomiya, Daisuke; Oda, Seitaro; Kidoh, Masafumi; Nagayama, Yasunori; Yamashita, Yasuyuki

2018-05-01

To investigate the image quality characteristics for virtual monoenergetic images compared with conventional tube-voltage image with dual-layer spectral CT (DLCT). Helical scans were performed using a first-generation DLCT scanner, two different sizes of acrylic cylindrical phantoms, and a Catphan phantom. Three different iodine concentrations were inserted into the phantom center. The single-tube voltage for obtaining virtual monoenergetic images was set to 120 or 140 kVp. Conventional 120- and 140-kVp images and virtual monoenergetic images (40-200-keV images) were reconstructed from slice thicknesses of 1.0 mm. The CT number and image noise were measured for each iodine concentration and water on the 120-kVp images and virtual monoenergetic images. The noise power spectrum (NPS) was also calculated. The iodine CT numbers for the iodinated enhancing materials were similar regardless of phantom size and acquisition method. Compared with the iodine CT numbers of the conventional 120-kVp images, those for the monoenergetic 40-, 50-, and 60-keV images increased by approximately 3.0-, 1.9-, and 1.3-fold, respectively. The image noise values for each virtual monoenergetic image were similar (for example, 24.6 HU at 40 keV and 23.3 HU at 200 keV obtained at 120 kVp and 30-cm phantom size). The NPS curves of the 70-keV and 120-kVp images for a 1.0-mm slice thickness over the entire frequency range were similar. Virtual monoenergetic images represent stable image noise over the entire energy spectrum and improved the contrast-to-noise ratio than conventional tube voltage using the dual-layer spectral detector CT. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Open architecture of smart sensor suites

Science.gov (United States)

Müller, Wilmuth; Kuwertz, Achim; Grönwall, Christina; Petersson, Henrik; Dekker, Rob; Reinert, Frank; Ditzel, Maarten

2017-10-01

Experiences from recent conflicts show the strong need for smart sensor suites comprising different multi-spectral imaging sensors as core elements as well as additional non-imaging sensors. Smart sensor suites should be part of a smart sensor network - a network of sensors, databases, evaluation stations and user terminals. Its goal is to optimize the use of various information sources for military operations such as situation assessment, intelligence, surveillance, reconnaissance, target recognition and tracking. Such a smart sensor network will enable commanders to achieve higher levels of situational awareness. Within the study at hand, an open system architecture was developed in order to increase the efficiency of sensor suites. The open system architecture for smart sensor suites, based on a system-of-systems approach, enables combining different sensors in multiple physical configurations, such as distributed sensors, co-located sensors combined in a single package, tower-mounted sensors, sensors integrated in a mobile platform, and trigger sensors. The architecture was derived from a set of system requirements and relevant scenarios. Its mode of operation is adaptable to a series of scenarios with respect to relevant objects of interest, activities to be observed, available transmission bandwidth, etc. The presented open architecture is designed in accordance with the NATO Architecture Framework (NAF). The architecture allows smart sensor suites to be part of a surveillance network, linked e.g. to a sensor planning system and a C4ISR center, and to be used in combination with future RPAS (Remotely Piloted Aircraft Systems) for supporting a more flexible dynamic configuration of RPAS payloads.

Evaluation of a HDR image sensor with logarithmic response for mobile video-based applications

Science.gov (United States)

Tektonidis, Marco; Pietrzak, Mateusz; Monnin, David

2017-10-01

The performance of mobile video-based applications using conventional LDR (Low Dynamic Range) image sensors highly depends on the illumination conditions. As an alternative, HDR (High Dynamic Range) image sensors with logarithmic response are capable to acquire illumination-invariant HDR images in a single shot. We have implemented a complete image processing framework for a HDR sensor, including preprocessing methods (nonuniformity correction (NUC), cross-talk correction (CTC), and demosaicing) as well as tone mapping (TM). We have evaluated the HDR sensor for video-based applications w.r.t. the display of images and w.r.t. image analysis techniques. Regarding the display we have investigated the image intensity statistics over time, and regarding image analysis we assessed the number of feature correspondences between consecutive frames of temporal image sequences. For the evaluation we used HDR image data recorded from a vehicle on outdoor or combined outdoor/indoor itineraries, and we performed a comparison with corresponding conventional LDR image data.

Snapshot hyperspectral imaging and practical applications

International Nuclear Information System (INIS)

Wong, G

2009-01-01

Traditional broadband imaging involves the digital representation of a remote scene within a reduced colour space. Hyperspectral imaging exploits the full spectral dimension, which better reflects the continuous nature of actual spectra. Conventional techniques are all time-delayed whereby spatial or spectral scanning is required for hypercube generation. An innovative and patented technique developed at Heriot-Watt University offers significant potential as a snapshot sensor, to enable benefits for the wider public beyond aerospace imaging. This student-authored paper seeks to promote awareness of this field within the photonic community and its potential advantages for real-time practical applications.

Characterisation methods for the hyperspectral sensor HySpex at DLR's calibration home base

Science.gov (United States)

Baumgartner, Andreas; Gege, Peter; Köhler, Claas; Lenhard, Karim; Schwarzmaier, Thomas

2012-09-01

The German Aerospace Center's (DLR) Remote Sensing Technology Institute (IMF) operates a laboratory for the characterisation of imaging spectrometers. Originally designed as Calibration Home Base (CHB) for the imaging spectrometer APEX, the laboratory can be used to characterise nearly every airborne hyperspectral system. Characterisation methods will be demonstrated exemplarily with HySpex, an airborne imaging spectrometer system from Norsk Elektro Optikks A/S (NEO). Consisting of two separate devices (VNIR-1600 and SWIR-320me) the setup covers the spectral range from 400 nm to 2500 nm. Both airborne sensors have been characterised at NEO. This includes measurement of spectral and spatial resolution and misregistration, polarisation sensitivity, signal to noise ratios and the radiometric response. The same parameters have been examined at the CHB and were used to validate the NEO measurements. Additionally, the line spread functions (LSF) in across and along track direction and the spectral response functions (SRF) for certain detector pixels were measured. The high degree of lab automation allows the determination of the SRFs and LSFs for a large amount of sampling points. Despite this, the measurement of these functions for every detector element would be too time-consuming as typical detectors have 105 elements. But with enough sampling points it is possible to interpolate the attributes of the remaining pixels. The knowledge of these properties for every detector element allows the quantification of spectral and spatial misregistration (smile and keystone) and a better calibration of airborne data. Further laboratory measurements are used to validate the models for the spectral and spatial properties of the imaging spectrometers. Compared to the future German spaceborne hyperspectral Imager EnMAP, the HySpex sensors have the same or higher spectral and spatial resolution. Therefore, airborne data will be used to prepare for and validate the spaceborne system

Model-based satellite image fusion

DEFF Research Database (Denmark)

Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

2008-01-01

A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals

Directory of Open Access Journals (Sweden)

Jiping Xiong

2017-03-01

Full Text Available Although wrist-type photoplethysmographic (hereafter referred to as WPPG sensor signals can measure heart rate quite conveniently, the subjects’ hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Implementation of large area CMOS image sensor module using the precision align inspection

International Nuclear Information System (INIS)

Kim, Byoung Wook; Kim, Toung Ju; Ryu, Cheol Woo; Lee, Kyung Yong; Kim, Jin Soo; Kim, Myung Soo; Cho, Gyu Seong

2014-01-01

This paper describes a large area CMOS image sensor module Implementation using the precision align inspection program. This work is needed because wafer cutting system does not always have high precision. The program check more than 8 point of sensor edges and align sensors with moving table. The size of a 2×1 butted CMOS image sensor module which except for the size of PCB is 170 mm×170 mm. And the pixel size is 55 μm×55 μm and the number of pixels is 3,072×3,072. The gap between the two CMOS image sensor module was arranged in less than one pixel size

Implementation of large area CMOS image sensor module using the precision align inspection

Energy Technology Data Exchange (ETDEWEB)

Kim, Byoung Wook; Kim, Toung Ju; Ryu, Cheol Woo [Radiation Imaging Technology Center, JBTP, Iksan (Korea, Republic of); Lee, Kyung Yong; Kim, Jin Soo [Nano Sol-Tech INC., Iksan (Korea, Republic of); Kim, Myung Soo; Cho, Gyu Seong [Dept. of Nuclear and Quantum Engineering, KAIST, Daejeon (Korea, Republic of)

2014-12-15

This paper describes a large area CMOS image sensor module Implementation using the precision align inspection program. This work is needed because wafer cutting system does not always have high precision. The program check more than 8 point of sensor edges and align sensors with moving table. The size of a 2×1 butted CMOS image sensor module which except for the size of PCB is 170 mm×170 mm. And the pixel size is 55 μm×55 μm and the number of pixels is 3,072×3,072. The gap between the two CMOS image sensor module was arranged in less than one pixel size.

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications

Directory of Open Access Journals (Sweden)

Kiyotaka Sasagawa

2010-12-01

Full Text Available In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors’ architecture on the basis of the type of electric measurement or imaging functionalities.

Evaluation of the data of vegetable covering using fraction images and multitemporal vegetation index, derived of orbital data of moderate resolution of the sensor MODIS

International Nuclear Information System (INIS)

Murillo Mejia, Mario Humberto

2006-01-01

The objective was to evaluate the data obtained by sensor MODIS onboard the EOS terra satellite land cover units. The study area is the republic of Colombia in South America. The methodology consisted of analyzing the multitemporal (vegetation, soil and shade-water) fraction images and vegetation indices (NDVI) apply the lineal spectral mixture model to products derived from derived images by sensor MODIS data obtained in years 2001 and 2003. The mosaics of the original and the transformed vegetation (soil and shade-water) bands were generated for the whole study area using SPRING 4. 0 software, developed by INPE then these mosaics were segmented, classified, mapped, and edited to obtain a moderate resolution land cover map. The results derived from MODIS analysis were compared with Landsat ETM+ data acquire for a single test site. The results of the project showed the usefulness of MODIS images for large-scale land cover mapping and monitoring studies

A New Pansharpening Method Based on Spatial and Spectral Sparsity Priors.

Science.gov (United States)

He, Xiyan; Condat, Laurent; Bioucas-Diaz, Jose; Chanussot, Jocelyn; Xia, Junshi

2014-06-27

The development of multisensor systems in recent years has led to great increase in the amount of available remote sensing data. Image fusion techniques aim at inferring high quality images of a given area from degraded versions of the same area obtained by multiple sensors. This paper focuses on pansharpening, which is the inference of a high spatial resolution multispectral image from two degraded versions with complementary spectral and spatial resolution characteristics: a) a low spatial resolution multispectral image; and b) a high spatial resolution panchromatic image. We introduce a new variational model based on spatial and spectral sparsity priors for the fusion. In the spectral domain we encourage low-rank structure, whereas in the spatial domain we promote sparsity on the local differences. Given the fact that both panchromatic and multispectral images are integrations of the underlying continuous spectra using different channel responses, we propose to exploit appropriate regularizations based on both spatial and spectral links between panchromatic and the fused multispectral images. A weighted version of the vector Total Variation (TV) norm of the data matrix is employed to align the spatial information of the fused image with that of the panchromatic image. With regard to spectral information, two different types of regularization are proposed to promote a soft constraint on the linear dependence between the panchromatic and the fused multispectral images. The first one estimates directly the linear coefficients from the observed panchromatic and low resolution multispectral images by Linear Regression (LR) while the second one employs the Principal Component Pursuit (PCP) to obtain a robust recovery of the underlying low-rank structure. We also show that the two regularizers are strongly related. The basic idea of both regularizers is that the fused image should have low-rank and preserve edge locations. We use a variation of the recently proposed

Time Series of Images to Improve Tree Species Classification

Science.gov (United States)

Miyoshi, G. T.; Imai, N. N.; de Moraes, M. V. A.; Tommaselli, A. M. G.; Näsi, R.

2017-10-01

Tree species classification provides valuable information to forest monitoring and management. The high floristic variation of the tree species appears as a challenging issue in the tree species classification because the vegetation characteristics changes according to the season. To help to monitor this complex environment, the imaging spectroscopy has been largely applied since the development of miniaturized sensors attached to Unmanned Aerial Vehicles (UAV). Considering the seasonal changes in forests and the higher spectral and spatial resolution acquired with sensors attached to UAV, we present the use of time series of images to classify four tree species. The study area is an Atlantic Forest area located in the western part of São Paulo State. Images were acquired in August 2015 and August 2016, generating three data sets of images: only with the image spectra of 2015; only with the image spectra of 2016; with the layer stacking of images from 2015 and 2016. Four tree species were classified using Spectral angle mapper (SAM), Spectral information divergence (SID) and Random Forest (RF). The results showed that SAM and SID caused an overfitting of the data whereas RF showed better results and the use of the layer stacking improved the classification achieving a kappa coefficient of 18.26 %.

Using Non-Invasive Multi-Spectral Imaging to Quantitatively Assess Tissue Vasculature

Energy Technology Data Exchange (ETDEWEB)

Vogel, A; Chernomordik, V; Riley, J; Hassan, M; Amyot, F; Dasgeb, B; Demos, S G; Pursley, R; Little, R; Yarchoan, R; Tao, Y; Gandjbakhche, A H

2007-10-04

This research describes a non-invasive, non-contact method used to quantitatively analyze the functional characteristics of tissue. Multi-spectral images collected at several near-infrared wavelengths are input into a mathematical optical skin model that considers the contributions from different analytes in the epidermis and dermis skin layers. Through a reconstruction algorithm, we can quantify the percent of blood in a given area of tissue and the fraction of that blood that is oxygenated. Imaging normal tissue confirms previously reported values for the percent of blood in tissue and the percent of blood that is oxygenated in tissue and surrounding vasculature, for the normal state and when ischemia is induced. This methodology has been applied to assess vascular Kaposi's sarcoma lesions and the surrounding tissue before and during experimental therapies. The multi-spectral imaging technique has been combined with laser Doppler imaging to gain additional information. Results indicate that these techniques are able to provide quantitative and functional information about tissue changes during experimental drug therapy and investigate progression of disease before changes are visibly apparent, suggesting a potential for them to be used as complementary imaging techniques to clinical assessment.