A comparison of select image-compression algorithms for an electronic still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

This effort is a study of image-compression algorithms for an electronic still camera. An electronic still camera can record and transmit high-quality images without the use of film, because images are stored digitally in computer memory. However, high-resolution images contain an enormous amount of information, and will strain the camera's data-storage system. Image compression will allow more images to be stored in the camera's memory. For the electronic still camera, a compression algorithm that produces a reconstructed image of high fidelity is most important. Efficiency of the algorithm is the second priority. High fidelity and efficiency are more important than a high compression ratio. Several algorithms were chosen for this study and judged on fidelity, efficiency and compression ratio. The transform method appears to be the best choice. At present, the method is compressing images to a ratio of 5.3:1 and producing high-fidelity reconstructed images.

Compressive sensing in medical imaging

PubMed Central

Graff, Christian G.; Sidky, Emil Y.

2015-01-01

The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed. PMID:25968400

Web surveillance system using platform-based design

NASA Astrophysics Data System (ADS)

Lin, Shin-Yo; Tsai, Tsung-Han

2004-04-01

A revolutionary methodology of SOPC platform-based design environment for multimedia communications will be developed. We embed a softcore processor to perform the image compression in FPGA. Then, we plug-in an Ethernet daughter board in the SOPC development platform system. Afterward, a web surveillance platform system is presented. The web surveillance system consists of three parts: image capture, web server and JPEG compression. In this architecture, user can control the surveillance system by remote. By the IP address configures to Ethernet daughter board, the user can access the surveillance system via browser. When user access the surveillance system, the CMOS sensor presently capture the remote image. After that, it will feed the captured image with the embedded processor. The embedded processor immediately performs the JPEG compression. Afterward, the user receives the compressed data via Ethernet. To sum up of the above mentioned, the all system will be implemented on APEX20K200E484-2X device.

JP3D compressed-domain watermarking of volumetric medical data sets

NASA Astrophysics Data System (ADS)

Ouled Zaid, Azza; Makhloufi, Achraf; Olivier, Christian

2010-01-01

Increasing transmission of medical data across multiple user systems raises concerns for medical image watermarking. Additionaly, the use of volumetric images triggers the need for efficient compression techniques in picture archiving and communication systems (PACS), or telemedicine applications. This paper describes an hybrid data hiding/compression system, adapted to volumetric medical imaging. The central contribution is to integrate blind watermarking, based on turbo trellis-coded quantization (TCQ), to JP3D encoder. Results of our method applied to Magnetic Resonance (MR) and Computed Tomography (CT) medical images have shown that our watermarking scheme is robust to JP3D compression attacks and can provide relative high data embedding rate whereas keep a relative lower distortion.

Intelligent bandwith compression

NASA Astrophysics Data System (ADS)

Tseng, D. Y.; Bullock, B. L.; Olin, K. E.; Kandt, R. K.; Olsen, J. D.

1980-02-01

The feasibility of a 1000:1 bandwidth compression ratio for image transmission has been demonstrated using image-analysis algorithms and a rule-based controller. Such a high compression ratio was achieved by first analyzing scene content using auto-cueing and feature-extraction algorithms, and then transmitting only the pertinent information consistent with mission requirements. A rule-based controller directs the flow of analysis and performs priority allocations on the extracted scene content. The reconstructed bandwidth-compressed image consists of an edge map of the scene background, with primary and secondary target windows embedded in the edge map. The bandwidth-compressed images are updated at a basic rate of 1 frame per second, with the high-priority target window updated at 7.5 frames per second. The scene-analysis algorithms used in this system together with the adaptive priority controller are described. Results of simulated 1000:1 band width-compressed images are presented. A video tape simulation of the Intelligent Bandwidth Compression system has been produced using a sequence of video input from the data base.

A zero-error operational video data compression system

NASA Technical Reports Server (NTRS)

Kutz, R. L.

1973-01-01

A data compression system has been operating since February 1972, using ATS spin-scan cloud cover data. With the launch of ITOS 3 in October 1972, this data compression system has become the only source of near-realtime very high resolution radiometer image data at the data processing facility. The VHRR image data are compressed and transmitted over a 50 kilobit per second wideband ground link. The goal of the data compression experiment was to send data quantized to six bits at twice the rate possible when no compression is used, while maintaining zero error between the transmitted and reconstructed data. All objectives of the data compression experiment were met, and thus a capability of doubling the data throughput of the system has been achieved.

Toward an image compression algorithm for the high-resolution electronic still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

Taking pictures with a camera that uses a digital recording medium instead of film has the advantage of recording and transmitting images without the use of a darkroom or a courier. However, high-resolution images contain an enormous amount of information and strain data-storage systems. Image compression will allow multiple images to be stored in the High-Resolution Electronic Still Camera. The camera is under development at Johnson Space Center. Fidelity of the reproduced image and compression speed are of tantamount importance. Lossless compression algorithms are fast and faithfully reproduce the image, but their compression ratios will be unacceptably low due to noise in the front end of the camera. Future efforts will include exploring methods that will reduce the noise in the image and increase the compression ratio.

Design of a Lossless Image Compression System for Video Capsule Endoscopy and Its Performance in In-Vivo Trials

PubMed Central

Khan, Tareq H.; Wahid, Khan A.

2014-01-01

In this paper, a new low complexity and lossless image compression system for capsule endoscopy (CE) is presented. The compressor consists of a low-cost YEF color space converter and variable-length predictive with a combination of Golomb-Rice and unary encoding. All these components have been heavily optimized for low-power and low-cost and lossless in nature. As a result, the entire compression system does not incur any loss of image information. Unlike transform based algorithms, the compressor can be interfaced with commercial image sensors which send pixel data in raster-scan fashion that eliminates the need of having large buffer memory. The compression algorithm is capable to work with white light imaging (WLI) and narrow band imaging (NBI) with average compression ratio of 78% and 84% respectively. Finally, a complete capsule endoscopy system is developed on a single, low-power, 65-nm field programmable gate arrays (FPGA) chip. The prototype is developed using circular PCBs having a diameter of 16 mm. Several in-vivo and ex-vivo trials using pig's intestine have been conducted using the prototype to validate the performance of the proposed lossless compression algorithm. The results show that, compared with all other existing works, the proposed algorithm offers a solution to wireless capsule endoscopy with lossless and yet acceptable level of compression. PMID:25375753

Iris Recognition: The Consequences of Image Compression

NASA Astrophysics Data System (ADS)

Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig

2010-12-01

Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

Digital compression algorithms for HDTV transmission

NASA Technical Reports Server (NTRS)

Adkins, Kenneth C.; Shalkhauser, Mary JO; Bibyk, Steven B.

1990-01-01

Digital compression of video images is a possible avenue for high definition television (HDTV) transmission. Compression needs to be optimized while picture quality remains high. Two techniques for compression the digital images are explained and comparisons are drawn between the human vision system and artificial compression techniques. Suggestions for improving compression algorithms through the use of neural and analog circuitry are given.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1990-01-01

A process is disclosed for x ray registration and differencing which results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

Digital Data Registration and Differencing Compression System

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1996-01-01

A process for X-ray registration and differencing results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic X-ray digital images.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1992-01-01

A process for x ray registration and differencing results in more efficient compression is discussed. Differencing of registered modeled subject image with a modeled reference image forms a differential image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three dimensional model, which three dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

Lossless medical image compression with a hybrid coder

NASA Astrophysics Data System (ADS)

Way, Jing-Dar; Cheng, Po-Yuen

1998-10-01

The volume of medical image data is expected to increase dramatically in the next decade due to the large use of radiological image for medical diagnosis. The economics of distributing the medical image dictate that data compression is essential. While there is lossy image compression, the medical image must be recorded and transmitted lossless before it reaches the users to avoid wrong diagnosis due to the image data lost. Therefore, a low complexity, high performance lossless compression schematic that can approach the theoretic bound and operate in near real-time is needed. In this paper, we propose a hybrid image coder to compress the digitized medical image without any data loss. The hybrid coder is constituted of two key components: an embedded wavelet coder and a lossless run-length coder. In this system, the medical image is compressed with the lossy wavelet coder first, and the residual image between the original and the compressed ones is further compressed with the run-length coder. Several optimization schemes have been used in these coders to increase the coding performance. It is shown that the proposed algorithm is with higher compression ratio than run-length entropy coders such as arithmetic, Huffman and Lempel-Ziv coders.

Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

NASA Astrophysics Data System (ADS)

Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian

2017-04-01

Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.

Two-dimensional compression of surface electromyographic signals using column-correlation sorting and image encoders.

PubMed

Costa, Marcus V C; Carvalho, Joao L A; Berger, Pedro A; Zaghetto, Alexandre; da Rocha, Adson F; Nascimento, Francisco A O

2009-01-01

We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature.

Using irreversible compression in digital radiology: a preliminary study of the opinions of radiologists

NASA Astrophysics Data System (ADS)

Seeram, Euclid

2006-03-01

The large volumes of digital images produced by digital imaging modalities in Radiology have provided the motivation for the development of picture archiving and communication systems (PACS) in an effort to provide an organized mechanism for digital image management. The development of more sophisticated methods of digital image acquisition (Multislice CT and Digital Mammography, for example), as well as the implementation and performance of PACS and Teleradiology systems in a health care environment, have created challenges in the area of image compression with respect to storing and transmitting digital images. Image compression can be reversible (lossless) or irreversible (lossy). While in the former, there is no loss of information, the latter presents concerns since there is a loss of information. This loss of information from diagnostic medical images is of primary concern not only to radiologists, but also to patients and their physicians. In 1997, Goldberg pointed out that "there is growing evidence that lossy compression can be applied without significantly affecting the diagnostic content of images... there is growing consensus in the radiologic community that some forms of lossy compression are acceptable". The purpose of this study was to explore the opinions of expert radiologists, and related professional organizations on the use of irreversible compression in routine practice The opinions of notable radiologists in the US and Canada are varied indicating no consensus of opinion on the use of irreversible compression in primary diagnosis, however, they are generally positive on the notion of the image storage and transmission advantages. Almost all radiologists are concerned with the litigation potential of an incorrect diagnosis based on irreversible compressed images. The survey of several radiology professional and related organizations reveals that no professional practice standards exist for the use of irreversible compression. Currently, the only standard for image compression is stated in the ACR's Technical Standards for Teleradiology and Digital Image Management.

An adaptive technique to maximize lossless image data compression of satellite images

NASA Technical Reports Server (NTRS)

Stewart, Robert J.; Lure, Y. M. Fleming; Liou, C. S. Joe

1994-01-01

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

End-to-end imaging information rate advantages of various alternative communication systems

NASA Technical Reports Server (NTRS)

Rice, R. F.

1982-01-01

The efficiency of various deep space communication systems which are required to transmit both imaging and a typically error sensitive class of data called general science and engineering (gse) are compared. The approach jointly treats the imaging and gse transmission problems, allowing comparisons of systems which include various channel coding and data compression alternatives. Actual system comparisons include an advanced imaging communication system (AICS) which exhibits the rather significant advantages of sophisticated data compression coupled with powerful yet practical channel coding. For example, under certain conditions the improved AICS efficiency could provide as much as two orders of magnitude increase in imaging information rate compared to a single channel uncoded, uncompressed system while maintaining the same gse data rate in both systems. Additional details describing AICS compression and coding concepts as well as efforts to apply them are provided in support of the system analysis.

Edge-preserving image compression for magnetic-resonance images using dynamic associative neural networks (DANN)-based neural networks

NASA Astrophysics Data System (ADS)

Wan, Tat C.; Kabuka, Mansur R.

1994-05-01

With the tremendous growth in imaging applications and the development of filmless radiology, the need for compression techniques that can achieve high compression ratios with user specified distortion rates becomes necessary. Boundaries and edges in the tissue structures are vital for detection of lesions and tumors, which in turn requires the preservation of edges in the image. The proposed edge preserving image compressor (EPIC) combines lossless compression of edges with neural network compression techniques based on dynamic associative neural networks (DANN), to provide high compression ratios with user specified distortion rates in an adaptive compression system well-suited to parallel implementations. Improvements to DANN-based training through the use of a variance classifier for controlling a bank of neural networks speed convergence and allow the use of higher compression ratios for `simple' patterns. The adaptation and generalization capabilities inherent in EPIC also facilitate progressive transmission of images through varying the number of quantization levels used to represent compressed patterns. Average compression ratios of 7.51:1 with an averaged average mean squared error of 0.0147 were achieved.

On use of image quality metrics for perceptual blur modeling: image/video compression case

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

2018-02-01

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

Potential end-to-end imaging information rate advantages of various alternative communication systems

NASA Technical Reports Server (NTRS)

Rice, R. F.

1978-01-01

Various communication systems were considered which are required to transmit both imaging and a typically error sensitive, class of data called general science/engineering (gse) over a Gaussian channel. The approach jointly treats the imaging and gse transmission problems, allowing comparisons of systems which include various channel coding and data compression alternatives. Actual system comparisons include an Advanced Imaging Communication System (AICS) which exhibits the rather significant potential advantages of sophisticated data compression coupled with powerful yet practical channel coding.

Alaska SAR Facility (ASF5) SAR Communications (SARCOM) Data Compression System

NASA Technical Reports Server (NTRS)

Mango, Stephen A.

1989-01-01

The real-time operational requirements for SARCOM translation into a high speed image data handler and processor to achieve the desired compression ratios and the selection of a suitable image data compression technique with as low as possible fidelity (information) losses and which can be implemented in an algorithm placing a relatively low arithmetic load on the system are described.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2016-03-23

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.

Image reconstruction of dynamic infrared single-pixel imaging system

NASA Astrophysics Data System (ADS)

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

2018-03-01

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

Subjective evaluation of compressed image quality

NASA Astrophysics Data System (ADS)

Lee, Heesub; Rowberg, Alan H.; Frank, Mark S.; Choi, Hyung-Sik; Kim, Yongmin

1992-05-01

Lossy data compression generates distortion or error on the reconstructed image and the distortion becomes visible as the compression ratio increases. Even at the same compression ratio, the distortion appears differently depending on the compression method used. Because of the nonlinearity of the human visual system and lossy data compression methods, we have evaluated subjectively the quality of medical images compressed with two different methods, an intraframe and interframe coding algorithms. The evaluated raw data were analyzed statistically to measure interrater reliability and reliability of an individual reader. Also, the analysis of variance was used to identify which compression method is better statistically, and from what compression ratio the quality of a compressed image is evaluated as poorer than that of the original. Nine x-ray CT head images from three patients were used as test cases. Six radiologists participated in reading the 99 images (some were duplicates) compressed at four different compression ratios, original, 5:1, 10:1, and 15:1. The six readers agree more than by chance alone and their agreement was statistically significant, but there were large variations among readers as well as within a reader. The displacement estimated interframe coding algorithm is significantly better in quality than that of the 2-D block DCT at significance level 0.05. Also, 10:1 compressed images with the interframe coding algorithm do not show any significant differences from the original at level 0.05.

A Posteriori Restoration of Block Transform-Compressed Data

NASA Technical Reports Server (NTRS)

Brown, R.; Boden, A. F.

1995-01-01

The Galileo spacecraft will use lossy data compression for the transmission of its science imagery over the low-bandwidth communication system. The technique chosen for image compression is a block transform technique based on the Integer Cosine Transform, a derivative of the JPEG image compression standard. Considered here are two known a posteriori enhancement techniques, which are adapted.

Fast computational scheme of image compression for 32-bit microprocessors

NASA Technical Reports Server (NTRS)

Kasperovich, Leonid

1994-01-01

This paper presents a new computational scheme of image compression based on the discrete cosine transform (DCT), underlying JPEG and MPEG International Standards. The algorithm for the 2-d DCT computation uses integer operations (register shifts and additions / subtractions only); its computational complexity is about 8 additions per image pixel. As a meaningful example of an on-board image compression application we consider the software implementation of the algorithm for the Mars Rover (Marsokhod, in Russian) imaging system being developed as a part of Mars-96 International Space Project. It's shown that fast software solution for 32-bit microprocessors may compete with the DCT-based image compression hardware.

Steganographic optical image encryption system based on reversible data hiding and double random phase encoding

NASA Astrophysics Data System (ADS)

Chuang, Cheng-Hung; Chen, Yen-Lin

2013-02-01

This study presents a steganographic optical image encryption system based on reversible data hiding and double random phase encoding (DRPE) techniques. Conventional optical image encryption systems can securely transmit valuable images using an encryption method for possible application in optical transmission systems. The steganographic optical image encryption system based on the DRPE technique has been investigated to hide secret data in encrypted images. However, the DRPE techniques vulnerable to attacks and many of the data hiding methods in the DRPE system can distort the decrypted images. The proposed system, based on reversible data hiding, uses a JBIG2 compression scheme to achieve lossless decrypted image quality and perform a prior encryption process. Thus, the DRPE technique enables a more secured optical encryption process. The proposed method extracts and compresses the bit planes of the original image using the lossless JBIG2 technique. The secret data are embedded in the remaining storage space. The RSA algorithm can cipher the compressed binary bits and secret data for advanced security. Experimental results show that the proposed system achieves a high data embedding capacity and lossless reconstruction of the original images.

Digitized hand-wrist radiographs: comparison of subjective and software-derived image quality at various compression ratios.

PubMed

McCord, Layne K; Scarfe, William C; Naylor, Rachel H; Scheetz, James P; Silveira, Anibal; Gillespie, Kevin R

2007-05-01

The objectives of this study were to compare the effect of JPEG 2000 compression of hand-wrist radiographs on observer image quality qualitative assessment and to compare with a software-derived quantitative image quality index. Fifteen hand-wrist radiographs were digitized and saved as TIFF and JPEG 2000 images at 4 levels of compression (20:1, 40:1, 60:1, and 80:1). The images, including rereads, were viewed by 13 orthodontic residents who determined the image quality rating on a scale of 1 to 5. A quantitative analysis was also performed by using a readily available software based on the human visual system (Image Quality Measure Computer Program, version 6.2, Mitre, Bedford, Mass). ANOVA was used to determine the optimal compression level (P < or =.05). When we compared subjective indexes, JPEG compression greater than 60:1 significantly reduced image quality. When we used quantitative indexes, the JPEG 2000 images had lower quality at all compression ratios compared with the original TIFF images. There was excellent correlation (R2 >0.92) between qualitative and quantitative indexes. Image Quality Measure indexes are more sensitive than subjective image quality assessments in quantifying image degradation with compression. There is potential for this software-based quantitative method in determining the optimal compression ratio for any image without the use of subjective raters.

Motion video compression system with neural network having winner-take-all function

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi (Inventor); Sheu, Bing J. (Inventor)

1997-01-01

A motion video data system includes a compression system, including an image compressor, an image decompressor correlative to the image compressor having an input connected to an output of the image compressor, a feedback summing node having one input connected to an output of the image decompressor, a picture memory having an input connected to an output of the feedback summing node, apparatus for comparing an image stored in the picture memory with a received input image and deducing therefrom pixels having differences between the stored image and the received image and for retrieving from the picture memory a partial image including the pixels only and applying the partial image to another input of the feedback summing node, whereby to produce at the output of the feedback summing node an updated decompressed image, a subtraction node having one input connected to received the received image and another input connected to receive the partial image so as to generate a difference image, the image compressor having an input connected to receive the difference image whereby to produce a compressed difference image at the output of the image compressor.

Assessment of low-contrast detectability for compressed digital chest images

NASA Astrophysics Data System (ADS)

Cook, Larry T.; Insana, Michael F.; McFadden, Michael A.; Hall, Timothy J.; Cox, Glendon G.

1994-04-01

The ability of human observers to detect low-contrast targets in screen-film (SF) images, computed radiographic (CR) images, and compressed CR images was measured using contrast detail (CD) analysis. The results of these studies were used to design a two- alternative forced-choice (2AFC) experiment to investigate the detectability of nodules in adult chest radiographs. CD curves for a common screen-film system were compared with CR images compressed up to 125:1. Data from clinical chest exams were used to define a CD region of clinical interest that sufficiently challenged the observer. From that data, simulated lesions were introduced into 100 normal CR chest films, and forced-choice observer performance studies were performed. CR images were compressed using a full-frame discrete cosine transform (FDCT) technique, where the 2D Fourier space was divided into four areas of different quantization depending on the cumulative power spectrum (energy) of each image. The characteristic curve of the CR images was adjusted so that optical densities matched those of the SF system. The CD curves for SF and uncompressed CR systems were statistically equivalent. The slope of the CD curve for each was - 1.0 as predicted by the Rose model. There was a significant degradation in detection found for CR images compressed to 125:1. Furthermore, contrast-detail analysis demonstrated that many pulmonary nodules encountered in clinical practice are significantly above the average observer threshold for detection. We designed a 2AFC observer study using simulated 1-cm lesions introduced into normal CR chest radiographs. Detectability was reduced for all compressed CR radiographs.

Using compressive measurement to obtain images at ultra low-light-level

NASA Astrophysics Data System (ADS)

Ke, Jun; Wei, Ping

2013-08-01

In this paper, a compressive imaging architecture is used for ultra low-light-level imaging. In such a system, features, instead of object pixels, are imaged onto a photocathode, and then magnified by an image intensifier. By doing so, system measurement SNR is increased significantly. Therefore, the new system can image objects at ultra low-ligh-level, while a conventional system has difficulty. PCA projection is used to collect feature measurements in this work. Linear Wiener operator and nonlinear method based on FoE model are used to reconstruct objects. Root mean square error (RMSE) is used to quantify system reconstruction quality.

GPU Lossless Hyperspectral Data Compression System

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh I.; Keymeulen, Didier; Kiely, Aaron B.; Klimesh, Matthew A.

2014-01-01

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

High-performance compression and double cryptography based on compressive ghost imaging with the fast Fourier transform

NASA Astrophysics Data System (ADS)

Leihong, Zhang; Zilan, Pan; Luying, Wu; Xiuhua, Ma

2016-11-01

To solve the problem that large images can hardly be retrieved for stringent hardware restrictions and the security level is low, a method based on compressive ghost imaging (CGI) with Fast Fourier Transform (FFT) is proposed, named FFT-CGI. Initially, the information is encrypted by the sender with FFT, and the FFT-coded image is encrypted by the system of CGI with a secret key. Then the receiver decrypts the image with the aid of compressive sensing (CS) and FFT. Simulation results are given to verify the feasibility, security, and compression of the proposed encryption scheme. The experiment suggests the method can improve the quality of large images compared with conventional ghost imaging and achieve the imaging for large-sized images, further the amount of data transmitted largely reduced because of the combination of compressive sensing and FFT, and improve the security level of ghost images through ciphertext-only attack (COA), chosen-plaintext attack (CPA), and noise attack. This technique can be immediately applied to encryption and data storage with the advantages of high security, fast transmission, and high quality of reconstructed information.

SAR data compression: Application, requirements, and designs

NASA Technical Reports Server (NTRS)

Curlander, John C.; Chang, C. Y.

1991-01-01

The feasibility of reducing data volume and data rate is evaluated for the Earth Observing System (EOS) Synthetic Aperture Radar (SAR). All elements of data stream from the sensor downlink data stream to electronic delivery of browse data products are explored. The factors influencing design of a data compression system are analyzed, including the signal data characteristics, the image quality requirements, and the throughput requirements. The conclusion is that little or no reduction can be achieved in the raw signal data using traditional data compression techniques (e.g., vector quantization, adaptive discrete cosine transform) due to the induced phase errors in the output image. However, after image formation, a number of techniques are effective for data compression.

Perceptually lossless fractal image compression

NASA Astrophysics Data System (ADS)

Lin, Huawu; Venetsanopoulos, Anastasios N.

1996-02-01

According to the collage theorem, the encoding distortion for fractal image compression is directly related to the metric used in the encoding process. In this paper, we introduce a perceptually meaningful distortion measure based on the human visual system's nonlinear response to luminance and the visual masking effects. Blackwell's psychophysical raw data on contrast threshold are first interpolated as a function of background luminance and visual angle, and are then used as an error upper bound for perceptually lossless image compression. For a variety of images, experimental results show that the algorithm produces a compression ratio of 8:1 to 10:1 without introducing visual artifacts.

Perceptual Image Compression in Telemedicine

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ahumada, Albert J., Jr.; Eckstein, Miguel; Null, Cynthia H. (Technical Monitor)

1996-01-01

The next era of space exploration, especially the "Mission to Planet Earth" will generate immense quantities of image data. For example, the Earth Observing System (EOS) is expected to generate in excess of one terabyte/day. NASA confronts a major technical challenge in managing this great flow of imagery: in collection, pre-processing, transmission to earth, archiving, and distribution to scientists at remote locations. Expected requirements in most of these areas clearly exceed current technology. Part of the solution to this problem lies in efficient image compression techniques. For much of this imagery, the ultimate consumer is the human eye. In this case image compression should be designed to match the visual capacities of the human observer. We have developed three techniques for optimizing image compression for the human viewer. The first consists of a formula, developed jointly with IBM and based on psychophysical measurements, that computes a DCT quantization matrix for any specified combination of viewing distance, display resolution, and display brightness. This DCT quantization matrix is used in most recent standards for digital image compression (JPEG, MPEG, CCITT H.261). The second technique optimizes the DCT quantization matrix for each individual image, based on the contents of the image. This is accomplished by means of a model of visual sensitivity to compression artifacts. The third technique extends the first two techniques to the realm of wavelet compression. Together these two techniques will allow systematic perceptual optimization of image compression in NASA imaging systems. Many of the image management challenges faced by NASA are mirrored in the field of telemedicine. Here too there are severe demands for transmission and archiving of large image databases, and the imagery is ultimately used primarily by human observers, such as radiologists. In this presentation I will describe some of our preliminary explorations of the applications of our technology to the special problems of telemedicine.

Influence of video compression on the measurement error of the television system

NASA Astrophysics Data System (ADS)

Sotnik, A. V.; Yarishev, S. N.; Korotaev, V. V.

2015-05-01

Video data require a very large memory capacity. Optimal ratio quality / volume video encoding method is one of the most actual problem due to the urgent need to transfer large amounts of video over various networks. The technology of digital TV signal compression reduces the amount of data used for video stream representation. Video compression allows effective reduce the stream required for transmission and storage. It is important to take into account the uncertainties caused by compression of the video signal in the case of television measuring systems using. There are a lot digital compression methods. The aim of proposed work is research of video compression influence on the measurement error in television systems. Measurement error of the object parameter is the main characteristic of television measuring systems. Accuracy characterizes the difference between the measured value abd the actual parameter value. Errors caused by the optical system can be selected as a source of error in the television systems measurements. Method of the received video signal processing is also a source of error. Presence of error leads to large distortions in case of compression with constant data stream rate. Presence of errors increases the amount of data required to transmit or record an image frame in case of constant quality. The purpose of the intra-coding is reducing of the spatial redundancy within a frame (or field) of television image. This redundancy caused by the strong correlation between the elements of the image. It is possible to convert an array of image samples into a matrix of coefficients that are not correlated with each other, if one can find corresponding orthogonal transformation. It is possible to apply entropy coding to these uncorrelated coefficients and achieve a reduction in the digital stream. One can select such transformation that most of the matrix coefficients will be almost zero for typical images . Excluding these zero coefficients also possible reducing of the digital stream. Discrete cosine transformation is most widely used among possible orthogonal transformation. Errors of television measuring systems and data compression protocols analyzed In this paper. The main characteristics of measuring systems and detected sources of their error detected. The most effective methods of video compression are determined. The influence of video compression error on television measuring systems was researched. Obtained results will increase the accuracy of the measuring systems. In television image quality measuring system reduces distortion identical distortion in analog systems and specific distortions resulting from the process of coding / decoding digital video signal and errors in the transmission channel. By the distortions associated with encoding / decoding signal include quantization noise, reducing resolution, mosaic effect, "mosquito" effect edging on sharp drops brightness, blur colors, false patterns, the effect of "dirty window" and other defects. The size of video compression algorithms used in television measuring systems based on the image encoding with intra- and inter prediction individual fragments. The process of encoding / decoding image is non-linear in space and in time, because the quality of the playback of a movie at the reception depends on the pre- and post-history of a random, from the preceding and succeeding tracks, which can lead to distortion of the inadequacy of the sub-picture and a corresponding measuring signal.

Intelligent bandwidth compression

NASA Astrophysics Data System (ADS)

Tseng, D. Y.; Bullock, B. L.; Olin, K. E.; Kandt, R. K.; Olsen, J. D.

1980-02-01

The feasibility of a 1000:1 bandwidth compression ratio for image transmission has been demonstrated using image-analysis algorithms and a rule-based controller. Such a high compression ratio was achieved by first analyzing scene content using auto-cueing and feature-extraction algorithms, and then transmitting only the pertinent information consistent with mission requirements. A rule-based controller directs the flow of analysis and performs priority allocations on the extracted scene content. The reconstructed bandwidth-compressed image consists of an edge map of the scene background, with primary and secondary target windows embedded in the edge map. The bandwidth-compressed images are updated at a basic rate of 1 frame per second, with the high-priority target window updated at 7.5 frames per second. The scene-analysis algorithms used in this system together with the adaptive priority controller are described. Results of simulated 1000:1 bandwidth-compressed images are presented.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

The development of machine technology processing for earth resource survey

NASA Technical Reports Server (NTRS)

Landgrebe, D. A.

1970-01-01

The following technologies are considered for automatic processing of earth resources data: (1) registration of multispectral and multitemporal images, (2) digital image display systems, (3) data system parameter effects on satellite remote sensing systems, and (4) data compression techniques based on spectral redundancy. The importance of proper spectral band and compression algorithm selections is pointed out.

A novel color image compression algorithm using the human visual contrast sensitivity characteristics

NASA Astrophysics Data System (ADS)

Yao, Juncai; Liu, Guizhong

2017-03-01

In order to achieve higher image compression ratio and improve visual perception of the decompressed image, a novel color image compression scheme based on the contrast sensitivity characteristics of the human visual system (HVS) is proposed. In the proposed scheme, firstly the image is converted into the YCrCb color space and divided into sub-blocks. Afterwards, the discrete cosine transform is carried out for each sub-block, and three quantization matrices are built to quantize the frequency spectrum coefficients of the images by combining the contrast sensitivity characteristics of HVS. The Huffman algorithm is used to encode the quantized data. The inverse process involves decompression and matching to reconstruct the decompressed color image. And simulations are carried out for two color images. The results show that the average structural similarity index measurement (SSIM) and peak signal to noise ratio (PSNR) under the approximate compression ratio could be increased by 2.78% and 5.48%, respectively, compared with the joint photographic experts group (JPEG) compression. The results indicate that the proposed compression algorithm in the text is feasible and effective to achieve higher compression ratio under ensuring the encoding and image quality, which can fully meet the needs of storage and transmission of color images in daily life.

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Optical image encryption using chaos-based compressed sensing and phase-shifting interference in fractional wavelet domain

NASA Astrophysics Data System (ADS)

Liu, Qi; Wang, Ying; Wang, Jun; Wang, Qiong-Hua

2018-02-01

In this paper, a novel optical image encryption system combining compressed sensing with phase-shifting interference in fractional wavelet domain is proposed. To improve the encryption efficiency, the volume data of original image are decreased by compressed sensing. Then the compacted image is encoded through double random phase encoding in asymmetric fractional wavelet domain. In the encryption system, three pseudo-random sequences, generated by three-dimensional chaos map, are used as the measurement matrix of compressed sensing and two random-phase masks in the asymmetric fractional wavelet transform. It not only simplifies the keys to storage and transmission, but also enhances our cryptosystem nonlinearity to resist some common attacks. Further, holograms make our cryptosystem be immune to noises and occlusion attacks, which are obtained by two-step-only quadrature phase-shifting interference. And the compression and encryption can be achieved in the final result simultaneously. Numerical experiments have verified the security and validity of the proposed algorithm.

Low-Speed Fingerprint Image Capture System User`s Guide, June 1, 1993

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitus, B.R.; Goddard, J.S.; Jatko, W.B.

1993-06-01

The Low-Speed Fingerprint Image Capture System (LS-FICS) uses a Sun workstation controlling a Lenzar ElectroOptics Opacity 1000 imaging system to digitize fingerprint card images to support the Federal Bureau of Investigation`s (FBI`s) Automated Fingerprint Identification System (AFIS) program. The system also supports the operations performed by the Oak Ridge National Laboratory- (ORNL-) developed Image Transmission Network (ITN) prototype card scanning system. The input to the system is a single FBI fingerprint card of the agreed-upon standard format and a user-specified identification number. The output is a file formatted to be compatible with the National Institute of Standards and Technology (NIST)more » draft standard for fingerprint data exchange dated June 10, 1992. These NIST compatible files contain the required print and text images. The LS-FICS is designed to provide the FBI with the capability of scanning fingerprint cards into a digital format. The FBI will replicate the system to generate a data base of test images. The Host Workstation contains the image data paths and the compression algorithm. A local area network interface, disk storage, and tape drive are used for the image storage and retrieval, and the Lenzar Opacity 1000 scanner is used to acquire the image. The scanner is capable of resolving 500 pixels/in. in both x and y directions. The print images are maintained in full 8-bit gray scale and compressed with an FBI-approved wavelet-based compression algorithm. The text fields are downsampled to 250 pixels/in. and 2-bit gray scale. The text images are then compressed using a lossless Huffman coding scheme. The text fields retrieved from the output files are easily interpreted when displayed on the screen. Detailed procedures are provided for system calibration and operation. Software tools are provided to verify proper system operation.« less

Multi-rate, real time image compression for images dominated by point sources

NASA Technical Reports Server (NTRS)

Huber, A. Kris; Budge, Scott E.; Harris, Richard W.

1993-01-01

An image compression system recently developed for compression of digital images dominated by point sources is presented. Encoding consists of minimum-mean removal, vector quantization, adaptive threshold truncation, and modified Huffman encoding. Simulations are presented showing that the peaks corresponding to point sources can be transmitted losslessly for low signal-to-noise ratios (SNR) and high point source densities while maintaining a reduced output bit rate. Encoding and decoding hardware has been built and tested which processes 552,960 12-bit pixels per second at compression rates of 10:1 and 4:1. Simulation results are presented for the 10:1 case only.

Technology study of quantum remote sensing imaging

NASA Astrophysics Data System (ADS)

Bi, Siwen; Lin, Xuling; Yang, Song; Wu, Zhiqiang

2016-02-01

According to remote sensing science and technology development and application requirements, quantum remote sensing is proposed. First on the background of quantum remote sensing, quantum remote sensing theory, information mechanism, imaging experiments and prototype principle prototype research situation, related research at home and abroad are briefly introduced. Then we expounds compress operator of the quantum remote sensing radiation field and the basic principles of single-mode compression operator, quantum quantum light field of remote sensing image compression experiment preparation and optical imaging, the quantum remote sensing imaging principle prototype, Quantum remote sensing spaceborne active imaging technology is brought forward, mainly including quantum remote sensing spaceborne active imaging system composition and working principle, preparation and injection compression light active imaging device and quantum noise amplification device. Finally, the summary of quantum remote sensing research in the past 15 years work and future development are introduced.

Space communication system for compressed data with a concatenated Reed-Solomon-Viterbi coding channel

NASA Technical Reports Server (NTRS)

Rice, R. F.; Hilbert, E. E. (Inventor)

1976-01-01

A space communication system incorporating a concatenated Reed Solomon Viterbi coding channel is discussed for transmitting compressed and uncompressed data from a spacecraft to a data processing center on Earth. Imaging (and other) data are first compressed into source blocks which are then coded by a Reed Solomon coder and interleaver, followed by a convolutional encoder. The received data is first decoded by a Viterbi decoder, followed by a Reed Solomon decoder and deinterleaver. The output of the latter is then decompressed, based on the compression criteria used in compressing the data in the spacecraft. The decompressed data is processed to reconstruct an approximation of the original data-producing condition or images.

National Information Systems Security Conference (19th) held in Baltimore, Maryland on October 22-25, 1996. Volume 1

DTIC Science & Technology

1996-10-25

been demonstrated that steganography is ineffective 195 when images are stored using this compression algorithm [2]. Difficulty in designing a general...Despite the relative ease of employing steganography to covertly transport data in an uncompressed 24-bit image , lossy compression algorithms based on... image , the security threat that steganography poses cannot be completely eliminated by application of a transform-based lossy compression algorithm

Data compression techniques applied to high resolution high frame rate video technology

NASA Technical Reports Server (NTRS)

Hartz, William G.; Alexovich, Robert E.; Neustadter, Marc S.

1989-01-01

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended.

Storage and retrieval of large digital images

DOEpatents

Bradley, J.N.

1998-01-20

Image compression and viewing are implemented with (1) a method for performing DWT-based compression on a large digital image with a computer system possessing a two-level system of memory and (2) a method for selectively viewing areas of the image from its compressed representation at multiple resolutions and, if desired, in a client-server environment. The compression of a large digital image I(x,y) is accomplished by first defining a plurality of discrete tile image data subsets T{sub ij}(x,y) that, upon superposition, form the complete set of image data I(x,y). A seamless wavelet-based compression process is effected on I(x,y) that is comprised of successively inputting the tiles T{sub ij}(x,y) in a selected sequence to a DWT routine, and storing the resulting DWT coefficients in a first primary memory. These coefficients are periodically compressed and transferred to a secondary memory to maintain sufficient memory in the primary memory for data processing. The sequence of DWT operations on the tiles T{sub ij}(x,y) effectively calculates a seamless DWT of I(x,y). Data retrieval consists of specifying a resolution and a region of I(x,y) for display. The subset of stored DWT coefficients corresponding to each requested scene is determined and then decompressed for input to an inverse DWT, the output of which forms the image display. The repeated process whereby image views are specified may take the form an interaction with a computer pointing device on an image display from a previous retrieval. 6 figs.

Storage and retrieval of large digital images

DOEpatents

Bradley, Jonathan N.

1998-01-01

Image compression and viewing are implemented with (1) a method for performing DWT-based compression on a large digital image with a computer system possessing a two-level system of memory and (2) a method for selectively viewing areas of the image from its compressed representation at multiple resolutions and, if desired, in a client-server environment. The compression of a large digital image I(x,y) is accomplished by first defining a plurality of discrete tile image data subsets T.sub.ij (x,y) that, upon superposition, form the complete set of image data I(x,y). A seamless wavelet-based compression process is effected on I(x,y) that is comprised of successively inputting the tiles T.sub.ij (x,y) in a selected sequence to a DWT routine, and storing the resulting DWT coefficients in a first primary memory. These coefficients are periodically compressed and transferred to a secondary memory to maintain sufficient memory in the primary memory for data processing. The sequence of DWT operations on the tiles T.sub.ij (x,y) effectively calculates a seamless DWT of I(x,y). Data retrieval consists of specifying a resolution and a region of I(x,y) for display. The subset of stored DWT coefficients corresponding to each requested scene is determined and then decompressed for input to an inverse DWT, the output of which forms the image display. The repeated process whereby image views are specified may take the form an interaction with a computer pointing device on an image display from a previous retrieval.

Assessment of the impact of modeling axial compression on PET image reconstruction.

PubMed

Belzunce, Martin A; Reader, Andrew J

2017-10-01

To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher frequencies. Modeling the axial compression also achieved a lower coefficient of variation but with an increase of intervoxel correlations. The unmatched projector/backprojector achieved similar contrast values to the matched version at considerably lower reconstruction times, but at the cost of noisier images. For a line source scan, the reconstructions with modeling of the axial compression achieved similar resolution to the span 1 reconstructions. Axial compression applied to PET sinograms was found to have a negligible impact for span values lower than 7. For span values up to 21, the spatial resolution degradation due to the axial compression can be almost completely compensated for by modeling this effect in the system matrix at the expense of considerably larger processing times and higher intervoxel correlations, while retaining the storage benefit of compressed data. For even higher span values, the resolution loss cannot be completely compensated possibly due to an effective null space in the system. The use of an unmatched projector/backprojector proved to be a practical solution to compensate for the spatial resolution degradation at a reasonable computational cost but can lead to noisier images. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Distributed Compressive Sensing vs. Dynamic Compressive Sensing: Improving the Compressive Line Sensing Imaging System through Their Integration

DTIC Science & Technology

2015-01-01

streak tube imaging Lidar [15]. Nevertheless, instead of one- dimensional (1D) fan beam, a laser source modulates the digital micromirror device DMD and...Trans. Inform. Theory, vol. 52, pp. 1289-1306, 2006. [10] D. Dudley, W. Duncan and J. Slaughter, "Emerging Digital Micromirror Device (DMD) Applications

Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy

NASA Astrophysics Data System (ADS)

Dumas, John P.; Lodhi, Muhammad A.; Bajwa, Waheed U.; Pierce, Mark C.

2017-02-01

We are investigating compressive sensing architectures for applications in endomicroscopy, where the narrow diameter probes required for tissue access can limit the achievable spatial resolution. We hypothesize that the compressive sensing framework can be used to overcome the fundamental pixel number limitation in fiber-bundle based endomicroscopy by reconstructing images with more resolvable points than fibers in the bundle. An experimental test platform was assembled to evaluate and compare two candidate architectures, based on introducing a coded amplitude mask at either a conjugate image or Fourier plane within the optical system. The benchtop platform consists of a common illumination and object path followed by separate imaging arms for each compressive architecture. The imaging arms contain a digital micromirror device (DMD) as a reprogrammable mask, with a CCD camera for image acquisition. One arm has the DMD positioned at a conjugate image plane ("IP arm"), while the other arm has the DMD positioned at a Fourier plane ("FP arm"). Lenses were selected and positioned within each arm to achieve an element-to-pixel ratio of 16 (230,400 mask elements mapped onto 14,400 camera pixels). We discuss our mathematical model for each system arm and outline the importance of accounting for system non-idealities. Reconstruction of a 1951 USAF resolution target using optimization-based compressive sensing algorithms produced images with higher spatial resolution than bicubic interpolation for both system arms when system non-idealities are included in the model. Furthermore, images generated with image plane coding appear to exhibit higher spatial resolution, but more noise, than images acquired through Fourier plane coding.

Graphics processing unit-assisted lossless decompression

DOEpatents

Loughry, Thomas A.

2016-04-12

Systems and methods for decompressing compressed data that has been compressed by way of a lossless compression algorithm are described herein. In a general embodiment, a graphics processing unit (GPU) is programmed to receive compressed data packets and decompress such packets in parallel. The compressed data packets are compressed representations of an image, and the lossless compression algorithm is a Rice compression algorithm.

Remote driving with reduced bandwidth communication

NASA Technical Reports Server (NTRS)

Depiero, Frederick W.; Noell, Timothy E.; Gee, Timothy F.

1993-01-01

Oak Ridge National Laboratory has developed a real-time video transmission system for low bandwidth remote operations. The system supports both continuous transmission of video for remote driving and progressive transmission of still images. Inherent in the system design is a spatiotemporal limitation to the effects of channel errors. The average data rate of the system is 64,000 bits/s, a compression of approximately 1000:1 for the black and white National Television Standard Code video. The image quality of the transmissions is maintained at a level that supports teleoperation of a high mobility multipurpose wheeled vehicle at speeds up to 15 mph on a moguled dirt track. Video compression is achieved by using Laplacian image pyramids and a combination of classical techniques. Certain subbands of the image pyramid are transmitted by using interframe differencing with a periodic refresh to aid in bandwidth reduction. Images are also foveated to concentrate image detail in a steerable region. The system supports dynamic video quality adjustments between frame rate, image detail, and foveation rate. A typical configuration for the system used during driving has a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of less than 1s.

Privacy protection in surveillance systems based on JPEG DCT baseline compression and spectral domain watermarking

NASA Astrophysics Data System (ADS)

Sablik, Thomas; Velten, Jörg; Kummert, Anton

2015-03-01

An novel system for automatic privacy protection in digital media based on spectral domain watermarking and JPEG compression is described in the present paper. In a first step private areas are detected. Therefore a detection method is presented. The implemented method uses Haar cascades to detects faces. Integral images are used to speed up calculations and the detection. Multiple detections of one face are combined. Succeeding steps comprise embedding the data into the image as part of JPEG compression using spectral domain methods and protecting the area of privacy. The embedding process is integrated into and adapted to JPEG compression. A Spread Spectrum Watermarking method is used to embed the size and position of the private areas into the cover image. Different methods for embedding regarding their robustness are compared. Moreover the performance of the method concerning tampered images is presented.

Subband/transform functions for image processing

NASA Technical Reports Server (NTRS)

Glover, Daniel

1993-01-01

Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.

Feasibility of spatial frequency-domain imaging for monitoring palpable breast lesions

NASA Astrophysics Data System (ADS)

Robbins, Constance M.; Raghavan, Guruprasad; Antaki, James F.; Kainerstorfer, Jana M.

2017-12-01

In breast cancer diagnosis and therapy monitoring, there is a need for frequent, noninvasive disease progression evaluation. Breast tumors differ from healthy tissue in mechanical stiffness as well as optical properties, which allows optical methods to detect and monitor breast lesions noninvasively. Spatial frequency-domain imaging (SFDI) is a reflectance-based diffuse optical method that can yield two-dimensional images of absolute optical properties of tissue with an inexpensive and portable system, although depth penetration is limited. Since the absorption coefficient of breast tissue is relatively low and the tissue is quite flexible, there is an opportunity for compression of tissue to bring stiff, palpable breast lesions within the detection range of SFDI. Sixteen breast tissue-mimicking phantoms were fabricated containing stiffer, more highly absorbing tumor-mimicking inclusions of varying absorption contrast and depth. These phantoms were imaged with an SFDI system at five levels of compression. An increase in absorption contrast was observed with compression, and reliable detection of each inclusion was achieved when compression was sufficient to bring the inclusion center within ˜12 mm of the phantom surface. At highest compression level, contrasts achieved with this system were comparable to those measured with single source-detector near-infrared spectroscopy.

High-speed real-time image compression based on all-optical discrete cosine transformation

NASA Astrophysics Data System (ADS)

Guo, Qiang; Chen, Hongwei; Wang, Yuxi; Chen, Minghua; Yang, Sigang; Xie, Shizhong

2017-02-01

In this paper, we present a high-speed single-pixel imaging (SPI) system based on all-optical discrete cosine transform (DCT) and demonstrate its capability to enable noninvasive imaging of flowing cells in a microfluidic channel. Through spectral shaping based on photonic time stretch (PTS) and wavelength-to-space conversion, structured illumination patterns are generated at a rate (tens of MHz) which is three orders of magnitude higher than the switching rate of a digital micromirror device (DMD) used in a conventional single-pixel camera. Using this pattern projector, high-speed image compression based on DCT can be achieved in the optical domain. In our proposed system, a high compression ratio (approximately 10:1) and a fast image reconstruction procedure are both achieved, which implicates broad applications in industrial quality control and biomedical imaging.

Transform-Based Channel-Data Compression to Improve the Performance of a Real-Time GPU-Based Software Beamformer.

PubMed

Lok, U-Wai; Li, Pai-Chi

2016-03-01

Graphics processing unit (GPU)-based software beamforming has advantages over hardware-based beamforming of easier programmability and a faster design cycle, since complicated imaging algorithms can be efficiently programmed and modified. However, the need for a high data rate when transferring ultrasound radio-frequency (RF) data from the hardware front end to the software back end limits the real-time performance. Data compression methods can be applied to the hardware front end to mitigate the data transfer issue. Nevertheless, most decompression processes cannot be performed efficiently on a GPU, thus becoming another bottleneck of the real-time imaging. Moreover, lossless (or nearly lossless) compression is desirable to avoid image quality degradation. In a previous study, we proposed a real-time lossless compression-decompression algorithm and demonstrated that it can reduce the overall processing time because the reduction in data transfer time is greater than the computation time required for compression/decompression. This paper analyzes the lossless compression method in order to understand the factors limiting the compression efficiency. Based on the analytical results, a nearly lossless compression is proposed to further enhance the compression efficiency. The proposed method comprises a transformation coding method involving modified lossless compression that aims at suppressing amplitude data. The simulation results indicate that the compression ratio (CR) of the proposed approach can be enhanced from nearly 1.8 to 2.5, thus allowing a higher data acquisition rate at the front end. The spatial and contrast resolutions with and without compression were almost identical, and the process of decompressing the data of a single frame on a GPU took only several milliseconds. Moreover, the proposed method has been implemented in a 64-channel system that we built in-house to demonstrate the feasibility of the proposed algorithm in a real system. It was found that channel data from a 64-channel system can be transferred using the standard USB 3.0 interface in most practical imaging applications.

The New CCSDS Image Compression Recommendation

NASA Technical Reports Server (NTRS)

Yeh, Pen-Shu; Armbruster, Philippe; Kiely, Aaron; Masschelein, Bart; Moury, Gilles; Schaefer, Christoph

2005-01-01

The Consultative Committee for Space Data Systems (CCSDS) data compression working group has recently adopted a recommendation for image data compression, with a final release expected in 2005. The algorithm adopted in the recommendation consists of a two-dimensional discrete wavelet transform of the image, followed by progressive bit-plane coding of the transformed data. The algorithm can provide both lossless and lossy compression, and allows a user to directly control the compressed data volume or the fidelity with which the wavelet-transformed data can be reconstructed. The algorithm is suitable for both frame-based image data and scan-based sensor data, and has applications for near-Earth and deep-space missions. The standard will be accompanied by free software sources on a future web site. An Application-Specific Integrated Circuit (ASIC) implementation of the compressor is currently under development. This paper describes the compression algorithm along with the requirements that drove the selection of the algorithm. Performance results and comparisons with other compressors are given for a test set of space images.

Compressive spectral testbed imaging system based on thin-film color-patterned filter arrays.

PubMed

Rueda, Hoover; Arguello, Henry; Arce, Gonzalo R

2016-11-20

Compressive spectral imaging systems can reliably capture multispectral data using far fewer measurements than traditional scanning techniques. In this paper, a thin-film patterned filter array-based compressive spectral imager is demonstrated, including its optical design and implementation. The use of a patterned filter array entails a single-step three-dimensional spatial-spectral coding on the input data cube, which provides higher flexibility on the selection of voxels being multiplexed on the sensor. The patterned filter array is designed and fabricated with micrometer pitch size thin films, referred to as pixelated filters, with three different wavelengths. The performance of the system is evaluated in terms of references measured by a commercially available spectrometer and the visual quality of the reconstructed images. Different distributions of the pixelated filters, including random and optimized structures, are explored.

Efficient image acquisition design for a cancer detection system

NASA Astrophysics Data System (ADS)

Nguyen, Dung; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

2013-09-01

Modern imaging modalities, such as Computed Tomography (CT), Digital Breast Tomosynthesis (DBT) or Magnetic Resonance Tomography (MRT) are able to acquire volumetric images with an isotropic resolution in micrometer (um) or millimeter (mm) range. When used in interactive telemedicine applications, these raw images need a huge storage unit, thereby necessitating the use of high bandwidth data communication link. To reduce the cost of transmission and enable archiving, especially for medical applications, image compression is performed. Recent advances in compression algorithms have resulted in a vast array of data compression techniques, but because of the characteristics of these images, there are challenges to overcome to transmit these images efficiently. In addition, the recent studies raise the low dose mammography risk on high risk patient. Our preliminary studies indicate that by bringing the compression before the analog-to-digital conversion (ADC) stage is more efficient than other compression techniques after the ADC. The linearity characteristic of the compressed sensing and ability to perform the digital signal processing (DSP) during data conversion open up a new area of research regarding the roles of sparsity in medical image registration, medical image analysis (for example, automatic image processing algorithm to efficiently extract the relevant information for the clinician), further Xray dose reduction for mammography, and contrast enhancement.

Pulse-compression ghost imaging lidar via coherent detection.

PubMed

Deng, Chenjin; Gong, Wenlin; Han, Shensheng

2016-11-14

Ghost imaging (GI) lidar, as a novel remote sensing technique, has been receiving increasing interest in recent years. By combining pulse-compression technique and coherent detection with GI, we propose a new lidar system called pulse-compression GI lidar. Our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar can obtain the target's spatial intensity distribution, range and moving velocity. Compared with conventional pulsed GI lidar system, pulse-compression GI lidar, without decreasing the range resolution, is easy to obtain high single pulse energy with the use of a long pulse, and the mechanism of coherent detection can eliminate the influence of the stray light, which is helpful to improve the detection sensitivity and detection range.

JPIC-Rad-Hard JPEG2000 Image Compression ASIC

NASA Astrophysics Data System (ADS)

Zervas, Nikos; Ginosar, Ran; Broyde, Amitai; Alon, Dov

2010-08-01

JPIC is a rad-hard high-performance image compression ASIC for the aerospace market. JPIC implements tier 1 of the ISO/IEC 15444-1 JPEG2000 (a.k.a. J2K) image compression standard [1] as well as the post compression rate-distortion algorithm, which is part of tier 2 coding. A modular architecture enables employing a single JPIC or multiple coordinated JPIC units. JPIC is designed to support wide data sources of imager in optical, panchromatic and multi-spectral space and airborne sensors. JPIC has been developed as a collaboration of Alma Technologies S.A. (Greece), MBT/IAI Ltd (Israel) and Ramon Chips Ltd (Israel). MBT IAI defined the system architecture requirements and interfaces, The JPEG2K-E IP core from Alma implements the compression algorithm [2]. Ramon Chips adds SERDES interfaces and host interfaces and integrates the ASIC. MBT has demonstrated the full chip on an FPGA board and created system boards employing multiple JPIC units. The ASIC implementation, based on Ramon Chips' 180nm CMOS RadSafe[TM] RH cell library enables superior radiation hardness.

Image and Video Compression with VLSI Neural Networks

NASA Technical Reports Server (NTRS)

Fang, W.; Sheu, B.

1993-01-01

An advanced motion-compensated predictive video compression system based on artificial neural networks has been developed to effectively eliminate the temporal and spatial redundancy of video image sequences and thus reduce the bandwidth and storage required for the transmission and recording of the video signal. The VLSI neuroprocessor for high-speed high-ratio image compression based upon a self-organization network and the conventional algorithm for vector quantization are compared. The proposed method is quite efficient and can achieve near-optimal results.

Design of a video capsule endoscopy system with low-power ASIC for monitoring gastrointestinal tract.

PubMed

Liu, Gang; Yan, Guozheng; Zhu, Bingquan; Lu, Li

2016-11-01

In recent years, wireless capsule endoscopy (WCE) has been a state-of-the-art tool to examine disorders of the human gastrointestinal tract painlessly. However, system miniaturization, enhancement of the image-data transfer rate and power consumption reduction for the capsule are still key challenges. In this paper, a video capsule endoscopy system with a low-power controlling and processing application-specific integrated circuit (ASIC) is designed and fabricated. In the design, these challenges are resolved by employing a microimage sensor, a novel radio frequency transmitter with an on-off keying modulation rate of 20 Mbps, and an ASIC structure that includes a clock management module, a power-efficient image compression module and a power management unit. An ASIC-based prototype capsule, which measures Φ11 mm × 25 mm, has been developed here. Test results show that the designed ASIC consumes much less power than most of the other WCE systems and that its total power consumption per frame is the least. The image compression module can realize high near-lossless compression rate (3.69) and high image quality (46.2 dB). The proposed system supports multi-spectral imaging, including white light imaging and autofluorescence imaging, at a maximum frame rate of 24 fps and with a resolution of 400 × 400. Tests and in vivo trials in pigs have proved the feasibility of the entire system, but further improvements in capsule control and compression performance inside the ASIC are needed in the future.

A new simultaneous compression and encryption method for images suitable to recognize form by optical correlation

NASA Astrophysics Data System (ADS)

Alfalou, Ayman; Elbouz, Marwa; Jridi, Maher; Loussert, Alain

2009-09-01

In some recognition form applications (which require multiple images: facial identification or sign-language), many images should be transmitted or stored. This requires the use of communication systems with a good security level (encryption) and an acceptable transmission rate (compression rate). In the literature, several encryption and compression techniques can be found. In order to use optical correlation, encryption and compression techniques cannot be deployed independently and in a cascade manner. Otherwise, our system will suffer from two major problems. In fact, we cannot simply use these techniques in a cascade manner without considering the impact of one technique over another. Secondly, a standard compression can affect the correlation decision, because the correlation is sensitive to the loss of information. To solve both problems, we developed a new technique to simultaneously compress & encrypt multiple images using a BPOF optimized filter. The main idea of our approach consists in multiplexing the spectrums of different transformed images by a Discrete Cosine Transform (DCT). To this end, the spectral plane should be divided into several areas and each of them corresponds to the spectrum of one image. On the other hand, Encryption is achieved using the multiplexing, a specific rotation functions, biometric encryption keys and random phase keys. A random phase key is widely used in optical encryption approaches. Finally, many simulations have been conducted. Obtained results corroborate the good performance of our approach. We should also mention that the recording of the multiplexed and encrypted spectra is optimized using an adapted quantification technique to improve the overall compression rate.

Image Quality Assessment of JPEG Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Kerner, H. R.; Bell, J. F., III; Ben Amor, H.

2017-12-01

The Mastcam color imaging system on the Mars Science Laboratory Curiosity rover acquires images within Gale crater for a variety of geologic and atmospheric studies. Images are often JPEG compressed before being downlinked to Earth. While critical for transmitting images on a low-bandwidth connection, this compression can result in image artifacts most noticeable as anomalous brightness or color changes within or near JPEG compression block boundaries. In images with significant high-frequency detail (e.g., in regions showing fine layering or lamination in sedimentary rocks), the image might need to be re-transmitted losslessly to enable accurate scientific interpretation of the data. The process of identifying which images have been adversely affected by compression artifacts is performed manually by the Mastcam science team, costing significant expert human time. To streamline the tedious process of identifying which images might need to be re-transmitted, we present an input-efficient neural network solution for predicting the perceived quality of a compressed Mastcam image. Most neural network solutions require large amounts of hand-labeled training data for the model to learn the target mapping between input (e.g. distorted images) and output (e.g. quality assessment). We propose an automatic labeling method using joint entropy between a compressed and uncompressed image to avoid the need for domain experts to label thousands of training examples by hand. We use automatically labeled data to train a convolutional neural network to estimate the probability that a Mastcam user would find the quality of a given compressed image acceptable for science analysis. We tested our model on a variety of Mastcam images and found that the proposed method correlates well with image quality perception by science team members. When assisted by our proposed method, we estimate that a Mastcam investigator could reduce the time spent reviewing images by a minimum of 70%.

Effects of compression and individual variability on face recognition performance

NASA Astrophysics Data System (ADS)

McGarry, Delia P.; Arndt, Craig M.; McCabe, Steven A.; D'Amato, Donald P.

2004-08-01

The Enhanced Border Security and Visa Entry Reform Act of 2002 requires that the Visa Waiver Program be available only to countries that have a program to issue to their nationals machine-readable passports incorporating biometric identifiers complying with applicable standards established by the International Civil Aviation Organization (ICAO). In June 2002, the New Technologies Working Group of ICAO unanimously endorsed the use of face recognition (FR) as the globally interoperable biometric for machine-assisted identity confirmation with machine-readable travel documents (MRTDs), although Member States may elect to use fingerprint and/or iris recognition as additional biometric technologies. The means and formats are still being developed through which biometric information might be stored in the constrained space of integrated circuit chips embedded within travel documents. Such information will be stored in an open, yet unalterable and very compact format, probably as digitally signed and efficiently compressed images. The objective of this research is to characterize the many factors that affect FR system performance with respect to the legislated mandates concerning FR. A photograph acquisition environment and a commercial face recognition system have been installed at Mitretek, and over 1,400 images have been collected of volunteers. The image database and FR system are being used to analyze the effects of lossy image compression, individual differences, such as eyeglasses and facial hair, and the acquisition environment on FR system performance. Images are compressed by varying ratios using JPEG2000 to determine the trade-off points between recognition accuracy and compression ratio. The various acquisition factors that contribute to differences in FR system performance among individuals are also being measured. The results of this study will be used to refine and test efficient face image interchange standards that ensure highly accurate recognition, both for automated FR systems and human inspectors. Working within the M1-Biometrics Technical Committee of the InterNational Committee for Information Technology Standards (INCITS) organization, a standard face image format will be tested and submitted to organizations such as ICAO.

End-to-end communication test on variable length packet structures utilizing AOS testbed

NASA Technical Reports Server (NTRS)

Miller, Warner H.; Sank, V.; Fong, Wai; Miko, J.; Powers, M.; Folk, John; Conaway, B.; Michael, K.; Yeh, Pen-Shu

1994-01-01

This paper describes a communication test, which successfully demonstrated the transfer of losslessly compressed images in an end-to-end system. These compressed images were first formatted into variable length Consultative Committee for Space Data Systems (CCSDS) packets in the Advanced Orbiting System Testbed (AOST). The CCSDS data Structures were transferred from the AOST to the Radio Frequency Simulations Operations Center (RFSOC), via a fiber optic link, where data was then transmitted through the Tracking and Data Relay Satellite System (TDRSS). The received data acquired at the White Sands Complex (WSC) was transferred back to the AOST where the data was captured and decompressed back to the original images. This paper describes the compression algorithm, the AOST configuration, key flight components, data formats, and the communication link characteristics and test results.

Roundness variation in JPEG images affects the automated process of nuclear immunohistochemical quantification: correction with a linear regression model.

PubMed

López, Carlos; Jaén Martinez, Joaquín; Lejeune, Marylène; Escrivà, Patricia; Salvadó, Maria T; Pons, Lluis E; Alvaro, Tomás; Baucells, Jordi; García-Rojo, Marcial; Cugat, Xavier; Bosch, Ramón

2009-10-01

The volume of digital image (DI) storage continues to be an important problem in computer-assisted pathology. DI compression enables the size of files to be reduced but with the disadvantage of loss of quality. Previous results indicated that the efficiency of computer-assisted quantification of immunohistochemically stained cell nuclei may be significantly reduced when compressed DIs are used. This study attempts to show, with respect to immunohistochemically stained nuclei, which morphometric parameters may be altered by the different levels of JPEG compression, and the implications of these alterations for automated nuclear counts, and further, develops a method for correcting this discrepancy in the nuclear count. For this purpose, 47 DIs from different tissues were captured in uncompressed TIFF format and converted to 1:3, 1:23 and 1:46 compression JPEG images. Sixty-five positive objects were selected from these images, and six morphological parameters were measured and compared for each object in TIFF images and those of the different compression levels using a set of previously developed and tested macros. Roundness proved to be the only morphological parameter that was significantly affected by image compression. Factors to correct the discrepancy in the roundness estimate were derived from linear regression models for each compression level, thereby eliminating the statistically significant differences between measurements in the equivalent images. These correction factors were incorporated in the automated macros, where they reduced the nuclear quantification differences arising from image compression. Our results demonstrate that it is possible to carry out unbiased automated immunohistochemical nuclear quantification in compressed DIs with a methodology that could be easily incorporated in different systems of digital image analysis.

Channel coding and data compression system considerations for efficient communication of planetary imaging data

NASA Technical Reports Server (NTRS)

Rice, R. F.

1974-01-01

End-to-end system considerations involving channel coding and data compression which could drastically improve the efficiency in communicating pictorial information from future planetary spacecraft are presented.

Compressive Sensing Image Sensors-Hardware Implementation

PubMed Central

Dadkhah, Mohammadreza; Deen, M. Jamal; Shirani, Shahram

2013-01-01

The compressive sensing (CS) paradigm uses simultaneous sensing and compression to provide an efficient image acquisition technique. The main advantages of the CS method include high resolution imaging using low resolution sensor arrays and faster image acquisition. Since the imaging philosophy in CS imagers is different from conventional imaging systems, new physical structures have been developed for cameras that use the CS technique. In this paper, a review of different hardware implementations of CS encoding in optical and electrical domains is presented. Considering the recent advances in CMOS (complementary metal–oxide–semiconductor) technologies and the feasibility of performing on-chip signal processing, important practical issues in the implementation of CS in CMOS sensors are emphasized. In addition, the CS coding for video capture is discussed. PMID:23584123

High-speed reconstruction of compressed images

NASA Astrophysics Data System (ADS)

Cox, Jerome R., Jr.; Moore, Stephen M.

1990-07-01

A compression scheme is described that allows high-definition radiological images with greater than 8-bit intensity resolution to be represented by 8-bit pixels. Reconstruction of the images with their original intensity resolution can be carried out by means of a pipeline architecture suitable for compact, high-speed implementation. A reconstruction system is described that can be fabricated according to this approach and placed between an 8-bit display buffer and the display's video system thereby allowing contrast control of images at video rates. Results for 50 CR chest images are described showing that error-free reconstruction of the original 10-bit CR images can be achieved.

Optimization of compressive 4D-spatio-spectral snapshot imaging

NASA Astrophysics Data System (ADS)

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.

Compressive hyperspectral and multispectral imaging fusion

NASA Astrophysics Data System (ADS)

Espitia, Óscar; Castillo, Sergio; Arguello, Henry

2016-05-01

Image fusion is a valuable framework which combines two or more images of the same scene from one or multiple sensors, allowing to improve the resolution of the images and increase the interpretable content. In remote sensing a common fusion problem consists of merging hyperspectral (HS) and multispectral (MS) images that involve large amount of redundant data, which ignores the highly correlated structure of the datacube along the spatial and spectral dimensions. Compressive HS and MS systems compress the spectral data in the acquisition step allowing to reduce the data redundancy by using different sampling patterns. This work presents a compressed HS and MS image fusion approach, which uses a high dimensional joint sparse model. The joint sparse model is formulated by combining HS and MS compressive acquisition models. The high spectral and spatial resolution image is reconstructed by using sparse optimization algorithms. Different fusion spectral image scenarios are used to explore the performance of the proposed scheme. Several simulations with synthetic and real datacubes show promising results as the reliable reconstruction of a high spectral and spatial resolution image can be achieved by using as few as just the 50% of the datacube.

Video bandwidth compression system

NASA Astrophysics Data System (ADS)

Ludington, D.

1980-08-01

The objective of this program was the development of a Video Bandwidth Compression brassboard model for use by the Air Force Avionics Laboratory, Wright-Patterson Air Force Base, in evaluation of bandwidth compression techniques for use in tactical weapons and to aid in the selection of particular operational modes to be implemented in an advanced flyable model. The bandwidth compression system is partitioned into two major divisions: the encoder, which processes the input video with a compression algorithm and transmits the most significant information; and the decoder where the compressed data is reconstructed into a video image for display.

Texture characterization for joint compression and classification based on human perception in the wavelet domain.

PubMed

Fahmy, Gamal; Black, John; Panchanathan, Sethuraman

2006-06-01

Today's multimedia applications demand sophisticated compression and classification techniques in order to store, transmit, and retrieve audio-visual information efficiently. Over the last decade, perceptually based image compression methods have been gaining importance. These methods take into account the abilities (and the limitations) of human visual perception (HVP) when performing compression. The upcoming MPEG 7 standard also addresses the need for succinct classification and indexing of visual content for efficient retrieval. However, there has been no research that has attempted to exploit the characteristics of the human visual system to perform both compression and classification jointly. One area of HVP that has unexplored potential for joint compression and classification is spatial frequency perception. Spatial frequency content that is perceived by humans can be characterized in terms of three parameters, which are: 1) magnitude; 2) phase; and 3) orientation. While the magnitude of spatial frequency content has been exploited in several existing image compression techniques, the novel contribution of this paper is its focus on the use of phase coherence for joint compression and classification in the wavelet domain. Specifically, this paper describes a human visual system-based method for measuring the degree to which an image contains coherent (perceptible) phase information, and then exploits that information to provide joint compression and classification. Simulation results that demonstrate the efficiency of this method are presented.

Subband/Transform MATLAB Functions For Processing Images

NASA Technical Reports Server (NTRS)

Glover, D.

1995-01-01

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

NASA Astrophysics Data System (ADS)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Observer detection of image degradation caused by irreversible data compression processes

NASA Astrophysics Data System (ADS)

Chen, Ji; Flynn, Michael J.; Gross, Barry; Spizarny, David

1991-05-01

Irreversible data compression methods have been proposed to reduce the data storage and communication requirements of digital imaging systems. In general, the error produced by compression increases as an algorithm''s compression ratio is increased. We have studied the relationship between compression ratios and the detection of induced error using radiologic observers. The nature of the errors was characterized by calculating the power spectrum of the difference image. In contrast with studies designed to test whether detected errors alter diagnostic decisions, this study was designed to test whether observers could detect the induced error. A paired-film observer study was designed to test whether induced errors were detected. The study was conducted with chest radiographs selected and ranked for subtle evidence of interstitial disease, pulmonary nodules, or pneumothoraces. Images were digitized at 86 microns (4K X 5K) and 2K X 2K regions were extracted. A full-frame discrete cosine transform method was used to compress images at ratios varying between 6:1 and 60:1. The decompressed images were reprinted next to the original images in a randomized order with a laser film printer. The use of a film digitizer and a film printer which can reproduce all of the contrast and detail in the original radiograph makes the results of this study insensitive to instrument performance and primarily dependent on radiographic image quality. The results of this study define conditions for which errors associated with irreversible compression cannot be detected by radiologic observers. The results indicate that an observer can detect the errors introduced by this compression algorithm for compression ratios of 10:1 (1.2 bits/pixel) or higher.

A real-time chirp-coded imaging system with tissue attenuation compensation.

PubMed

Ramalli, A; Guidi, F; Boni, E; Tortoli, P

2015-07-01

In ultrasound imaging, pulse compression methods based on the transmission (TX) of long coded pulses and matched receive filtering can be used to improve the penetration depth while preserving the axial resolution (coded-imaging). The performance of most of these methods is affected by the frequency dependent attenuation of tissue, which causes mismatch of the receiver filter. This, together with the involved additional computational load, has probably so far limited the implementation of pulse compression methods in real-time imaging systems. In this paper, a real-time low-computational-cost coded-imaging system operating on the beamformed and demodulated data received by a linear array probe is presented. The system has been implemented by extending the firmware and the software of the ULA-OP research platform. In particular, pulse compression is performed by exploiting the computational resources of a single digital signal processor. Each image line is produced in less than 20 μs, so that, e.g., 192-line frames can be generated at up to 200 fps. Although the system may work with a large class of codes, this paper has been focused on the test of linear frequency modulated chirps. The new system has been used to experimentally investigate the effects of tissue attenuation so that the design of the receive compression filter can be accordingly guided. Tests made with different chirp signals confirm that, although the attainable compression gain in attenuating media is lower than the theoretical value expected for a given TX Time-Bandwidth product (BT), good SNR gains can be obtained. For example, by using a chirp signal having BT=19, a 13 dB compression gain has been measured. By adapting the frequency band of the receiver to the band of the received echo, the signal-to-noise ratio and the penetration depth have been further increased, as shown by real-time tests conducted on phantoms and in vivo. In particular, a 2.7 dB SNR increase has been measured through a novel attenuation compensation scheme, which only requires to shift the demodulation frequency by 1 MHz. The proposed method characterizes for its simplicity and easy implementation. Copyright © 2015 Elsevier B.V. All rights reserved.

Terahertz imaging with compressed sensing and phase retrieval.

PubMed

Chan, Wai Lam; Moravec, Matthew L; Baraniuk, Richard G; Mittleman, Daniel M

2008-05-01

We describe a novel, high-speed pulsed terahertz (THz) Fourier imaging system based on compressed sensing (CS), a new signal processing theory, which allows image reconstruction with fewer samples than traditionally required. Using CS, we successfully reconstruct a 64 x 64 image of an object with pixel size 1.4 mm using a randomly chosen subset of the 4096 pixels, which defines the image in the Fourier plane, and observe improved reconstruction quality when we apply phase correction. For our chosen image, only about 12% of the pixels are required for reassembling the image. In combination with phase retrieval, our system has the capability to reconstruct images with only a small subset of Fourier amplitude measurements and thus has potential application in THz imaging with cw sources.

Study of communications data compression methods

NASA Technical Reports Server (NTRS)

Jones, H. W.

1978-01-01

A simple monochrome conditional replenishment system was extended to higher compression and to higher motion levels, by incorporating spatially adaptive quantizers and field repeating. Conditional replenishment combines intraframe and interframe compression, and both areas are investigated. The gain of conditional replenishment depends on the fraction of the image changing, since only changed parts of the image need to be transmitted. If the transmission rate is set so that only one fourth of the image can be transmitted in each field, greater change fractions will overload the system. A computer simulation was prepared which incorporated (1) field repeat of changes, (2) a variable change threshold, (3) frame repeat for high change, and (4) two mode, variable rate Hadamard intraframe quantizers. The field repeat gives 2:1 compression in moving areas without noticeable degradation. Variable change threshold allows some flexibility in dealing with varying change rates, but the threshold variation must be limited for acceptable performance.

Context dependent prediction and category encoding for DPCM image compression

NASA Technical Reports Server (NTRS)

Beaudet, Paul R.

1989-01-01

Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.

TU-CD-207-09: Analysis of the 3-D Shape of Patients’ Breast for Breast Imaging and Surgery Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agasthya, G; Sechopoulos, I

2015-06-15

Purpose: Develop a method to accurately capture the 3-D shape of patients’ external breast surface before and during breast compression for mammography/tomosynthesis. Methods: During this IRB-approved, HIPAA-compliant study, 50 women were recruited to undergo 3-D breast surface imaging during breast compression and imaging for the cranio-caudal (CC) view on a digital mammography/breast tomosynthesis system. Digital projectors and cameras mounted on tripods were used to acquire 3-D surface images of the breast, in three conditions: (a) positioned on the support paddle before compression, (b) during compression by the compression paddle and (c) the anterior-posterior view with the breast in its natural,more » unsupported position. The breast was compressed to standard full compression with the compression paddle and a tomosynthesis image was acquired simultaneously with the 3-D surface. The 3-D surface curvature and deformation with respect to the uncompressed surface was analyzed using contours. The 3-D surfaces were voxelized to capture breast shape in a format that can be manipulated for further analysis. Results: A protocol was developed to accurately capture the 3-D shape of patients’ breast before and during compression for mammography. Using a pair of 3-D scanners, the 50 patient breasts were scanned in three conditions, resulting in accurate representations of the breast surfaces. The surfaces were post processed, analyzed using contours and voxelized, with 1 mm{sup 3} voxels, converting the breast shape into a format that can be easily modified as required. Conclusion: Accurate characterization of the breast curvature and shape for the generation of 3-D models is possible. These models can be used for various applications such as improving breast dosimetry, accurate scatter estimation, conducting virtual clinical trials and validating compression algorithms. Ioannis Sechopoulos is consultant for Fuji Medical Systems USA.« less

Data compression for full motion video transmission

NASA Technical Reports Server (NTRS)

Whyte, Wayne A., Jr.; Sayood, Khalid

1991-01-01

Clearly transmission of visual information will be a major, if not dominant, factor in determining the requirements for, and assessing the performance of the Space Exploration Initiative (SEI) communications systems. Projected image/video requirements which are currently anticipated for SEI mission scenarios are presented. Based on this information and projected link performance figures, the image/video data compression requirements which would allow link closure are identified. Finally several approaches which could satisfy some of the compression requirements are presented and possible future approaches which show promise for more substantial compression performance improvement are discussed.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

Entropy reduction via simplified image contourization

NASA Technical Reports Server (NTRS)

Turner, Martin J.

1993-01-01

The process of contourization is presented which converts a raster image into a set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimizes noticeable artifacts in the simplified image.

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

NASA Astrophysics Data System (ADS)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

Digital image compression for a 2f multiplexing optical setup

NASA Astrophysics Data System (ADS)

Vargas, J.; Amaya, D.; Rueda, E.

2016-07-01

In this work a virtual 2f multiplexing system was implemented in combination with digital image compression techniques and redundant information elimination. Depending on the image type to be multiplexed, a memory-usage saving of as much as 99% was obtained. The feasibility of the system was tested using three types of images, binary characters, QR codes, and grey level images. A multiplexing step was implemented digitally, while a demultiplexing step was implemented in a virtual 2f optical setup following real experimental parameters. To avoid cross-talk noise, each image was codified with a specially designed phase diffraction carrier that would allow the separation and relocation of the multiplexed images on the observation plane by simple light propagation. A description of the system is presented together with simulations that corroborate the method. The present work may allow future experimental implementations that will make use of all the parallel processing capabilities of optical systems.

Efficient image compression algorithm for computer-animated images

NASA Astrophysics Data System (ADS)

Yfantis, Evangelos A.; Au, Matthew Y.; Miel, G.

1992-10-01

An image compression algorithm is described. The algorithm is an extension of the run-length image compression algorithm and its implementation is relatively easy. This algorithm was implemented and compared with other existing popular compression algorithms and with the Lempel-Ziv (LZ) coding. The Lempel-Ziv algorithm is available as a utility in the UNIX operating system and is also referred to as the UNIX uncompress. Sometimes our algorithm is best in terms of saving memory space, and sometimes one of the competing algorithms is best. The algorithm is lossless, and the intent is for the algorithm to be used in computer graphics animated images. Comparisons made with the LZ algorithm indicate that the decompression time using our algorithm is faster than that using the LZ algorithm. Once the data are in memory, a relatively simple and fast transformation is applied to uncompress the file.

NIR hyperspectral compressive imager based on a modified Fabry–Perot resonator

NASA Astrophysics Data System (ADS)

Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Stern, Adrian

2018-04-01

The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonator spectroscopy technique. Within the framework of CS, and by using a modified Fabry–Perot resonator, a sequence of spectrally modulated images is used to recover NIR HS datacubes. Owing to the innovative CS design, we demonstrate the ability to reconstruct NIR HS images with hundreds of spectral bands from an order of magnitude fewer measurements, i.e. with a compression ratio of about 10:1. This high compression ratio, together with the high optical throughput of the system, facilitates fast acquisition of large HS datacubes.

Compression of electromyographic signals using image compression techniques.

PubMed

Costa, Marcus Vinícius Chaffim; Berger, Pedro de Azevedo; da Rocha, Adson Ferreira; de Carvalho, João Luiz Azevedo; Nascimento, Francisco Assis de Oliveira

2008-01-01

Despite the growing interest in the transmission and storage of electromyographic signals for long periods of time, few studies have addressed the compression of such signals. In this article we present an algorithm for compression of electromyographic signals based on the JPEG2000 coding system. Although the JPEG2000 codec was originally designed for compression of still images, we show that it can also be used to compress EMG signals for both isotonic and isometric contractions. For EMG signals acquired during isometric contractions, the proposed algorithm provided compression factors ranging from 75 to 90%, with an average PRD ranging from 3.75% to 13.7%. For isotonic EMG signals, the algorithm provided compression factors ranging from 75 to 90%, with an average PRD ranging from 3.4% to 7%. The compression results using the JPEG2000 algorithm were compared to those using other algorithms based on the wavelet transform.

Complementary compressive imaging for the telescopic system

PubMed Central

Yu, Wen-Kai; Liu, Xue-Feng; Yao, Xu-Ri; Wang, Chao; Zhai, Yun; Zhai, Guang-Jie

2014-01-01

Conventional single-pixel cameras recover images only from the data recorded in one arm of the digital micromirror device, with the light reflected to the other direction not to be collected. Actually, the sampling in these two reflection orientations is correlated with each other, in view of which we propose a sampling concept of complementary compressive imaging, for the first time to our knowledge. We use this method in a telescopic system and acquire images of a target at about 2.0 km range with 20 cm resolution, with the variance of the noise decreasing by half. The influence of the sampling rate and the integration time of photomultiplier tubes on the image quality is also investigated experimentally. It is evident that this technique has advantages of large field of view over a long distance, high-resolution, high imaging speed, high-quality imaging capabilities, and needs fewer measurements in total than any single-arm sampling, thus can be used to improve the performance of all compressive imaging schemes and opens up possibilities for new applications in the remote-sensing area. PMID:25060569

[Remote access to a web-based image distribution system].

PubMed

Bergh, B; Schlaefke, A; Frankenbach, R; Vogl, T J

2004-06-01

To assess different network and security technologies for remote access to a web-based image distribution system of a hospital intranet. Following preparatory testing, the time-to-display (TTD) was measured for three image types (CR, CT, MR). The evaluation included two remote access technologies consisting of direct ISDN-Dial-Up or VPN connection (Virtual Private Network), with three different connection speeds of 64, 128 (ISDN) and 768 Kbit/s (ADSL-Asymmetric Digital Subscriber Line), as well as with lossless and lossy compression. Depending on the image type, the TTD with lossless compression for 64 Kbit/s varied from 1 : 00 to 2 : 40 minutes, for 128 Kbit/s from 0 : 35 to 1 : 15 minutes and for ADSL from 0 : 15 to 0 : 45 minutes. The ISDN-Dial-Up connection was superior to VPN technology at 64 Kbit/s but did not allow higher connection speeds. Lossy compression reduced the TTD by half for all measurements. VPN technology is preferable to direct Dial-Up connections since it offers higher connection speeds and advantages in usage and security. For occasional usage, 128 Kbit/s (ISDN) can be considered sufficient, especially in conjunction with lossy compression. ADSL should be chosen when a more frequent usage is anticipated, whereby lossy compression may be omitted. Due to higher bandwidths and improved usability, the web-based approach appears superior to conventional teleradiology systems.

Sub-component modeling for face image reconstruction in video communications

NASA Astrophysics Data System (ADS)

Shiell, Derek J.; Xiao, Jing; Katsaggelos, Aggelos K.

2008-08-01

Emerging communications trends point to streaming video as a new form of content delivery. These systems are implemented over wired systems, such as cable or ethernet, and wireless networks, cell phones, and portable game systems. These communications systems require sophisticated methods of compression and error-resilience encoding to enable communications across band-limited and noisy delivery channels. Additionally, the transmitted video data must be of high enough quality to ensure a satisfactory end-user experience. Traditionally, video compression makes use of temporal and spatial coherence to reduce the information required to represent an image. In many communications systems, the communications channel is characterized by a probabilistic model which describes the capacity or fidelity of the channel. The implication is that information is lost or distorted in the channel, and requires concealment on the receiving end. We demonstrate a generative model based transmission scheme to compress human face images in video, which has the advantages of a potentially higher compression ratio, while maintaining robustness to errors and data corruption. This is accomplished by training an offline face model and using the model to reconstruct face images on the receiving end. We propose a sub-component AAM modeling the appearance of sub-facial components individually, and show face reconstruction results under different types of video degradation using a weighted and non-weighted version of the sub-component AAM.

Choice of word length in the design of a specialized hardware for lossless wavelet compression of medical images

NASA Astrophysics Data System (ADS)

Urriza, Isidro; Barragan, Luis A.; Artigas, Jose I.; Garcia, Jose I.; Navarro, Denis

1997-11-01

Image compression plays an important role in the archiving and transmission of medical images. Discrete cosine transform (DCT)-based compression methods are not suitable for medical images because of block-like image artifacts that could mask or be mistaken for pathology. Wavelet transforms (WTs) are used to overcome this problem. When implementing WTs in hardware, finite precision arithmetic introduces quantization errors. However, lossless compression is usually required in the medical image field. Thus, the hardware designer must look for the optimum register length that, while ensuring the lossless accuracy criteria, will also lead to a high-speed implementation with small chip area. In addition, wavelet choice is a critical issue that affects image quality as well as system design. We analyze the filters best suited to image compression that appear in the literature. For them, we obtain the maximum quantization errors produced in the calculation of the WT components. Thus, we deduce the minimum word length required for the reconstructed image to be numerically identical to the original image. The theoretical results are compared with experimental results obtained from algorithm simulations on random test images. These results enable us to compare the hardware implementation cost of the different filter banks. Moreover, to reduce the word length, we have analyzed the case of increasing the integer part of the numbers while maintaining constant the word length when the scale increases.

JPEG and wavelet compression of ophthalmic images

NASA Astrophysics Data System (ADS)

Eikelboom, Robert H.; Yogesan, Kanagasingam; Constable, Ian J.; Barry, Christopher J.

1999-05-01

This study was designed to determine the degree and methods of digital image compression to produce ophthalmic imags of sufficient quality for transmission and diagnosis. The photographs of 15 subjects, which inclined eyes with normal, subtle and distinct pathologies, were digitized to produce 1.54MB images and compressed to five different methods: (i) objectively by calculating the RMS error between the uncompressed and compressed images, (ii) semi-subjectively by assessing the visibility of blood vessels, and (iii) subjectively by asking a number of experienced observers to assess the images for quality and clinical interpretation. Results showed that as a function of compressed image size, wavelet compressed images produced less RMS error than JPEG compressed images. Blood vessel branching could be observed to a greater extent after Wavelet compression compared to JPEG compression produced better images then a JPEG compression for a given image size. Overall, it was shown that images had to be compressed to below 2.5 percent for JPEG and 1.7 percent for Wavelet compression before fine detail was lost, or when image quality was too poor to make a reliable diagnosis.

Method and algorithm for efficient calibration of compressive hyperspectral imaging system based on a liquid crystal retarder

NASA Astrophysics Data System (ADS)

Shecter, Liat; Oiknine, Yaniv; August, Isaac; Stern, Adrian

2017-09-01

Recently we presented a Compressive Sensing Miniature Ultra-spectral Imaging System (CS-MUSI)1 . This system consists of a single Liquid Crystal (LC) phase retarder as a spectral modulator and a gray scale sensor array to capture a multiplexed signal of the imaged scene. By designing the LC spectral modulator in compliance with the Compressive Sensing (CS) guidelines and applying appropriate algorithms we demonstrated reconstruction of spectral (hyper/ ultra) datacubes from an order of magnitude fewer samples than taken by conventional sensors. The LC modulator is designed to have an effective width of a few tens of micrometers, therefore it is prone to imperfections and spatial nonuniformity. In this work, we present the study of this nonuniformity and present a mathematical algorithm that allows the inference of the spectral transmission over the entire cell area from only a few calibration measurements.

Dual Resolution Images from Paired Fingerprint Cards

National Institute of Standards and Technology Data Gateway

NIST Dual Resolution Images from Paired Fingerprint Cards (Web, free access)   NIST Special Database 30 is being distributed for use in development and testing of fingerprint compression and fingerprint matching systems. The database allows the user to develop and evaluate data compression algorithms for fingerprint images scanned at both 19.7 ppmm (500 dpi) and 39.4 ppmm (1000 dpi). The data consist of 36 ten-print paired cards with both the rolled and plain images scanned at 19.7 and 39.4 pixels per mm. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

A survey of quality measures for gray-scale image compression

NASA Technical Reports Server (NTRS)

Eskicioglu, Ahmet M.; Fisher, Paul S.

1993-01-01

Although a variety of techniques are available today for gray-scale image compression, a complete evaluation of these techniques cannot be made as there is no single reliable objective criterion for measuring the error in compressed images. The traditional subjective criteria are burdensome, and usually inaccurate or inconsistent. On the other hand, being the most common objective criterion, the mean square error (MSE) does not have a good correlation with the viewer's response. It is now understood that in order to have a reliable quality measure, a representative model of the complex human visual system is required. In this paper, we survey and give a classification of the criteria for the evaluation of monochrome image quality.

Lossless Astronomical Image Compression and the Effects of Random Noise

NASA Technical Reports Server (NTRS)

Pence, William

2009-01-01

In this paper we compare a variety of modern image compression methods on a large sample of astronomical images. We begin by demonstrating from first principles how the amount of noise in the image pixel values sets a theoretical upper limit on the lossless compression ratio of the image. We derive simple procedures for measuring the amount of noise in an image and for quantitatively predicting how much compression will be possible. We then compare the traditional technique of using the GZIP utility to externally compress the image, with a newer technique of dividing the image into tiles, and then compressing and storing each tile in a FITS binary table structure. This tiled-image compression technique offers a choice of other compression algorithms besides GZIP, some of which are much better suited to compressing astronomical images. Our tests on a large sample of images show that the Rice algorithm provides the best combination of speed and compression efficiency. In particular, Rice typically produces 1.5 times greater compression and provides much faster compression speed than GZIP. Floating point images generally contain too much noise to be effectively compressed with any lossless algorithm. We have developed a compression technique which discards some of the useless noise bits by quantizing the pixel values as scaled integers. The integer images can then be compressed by a factor of 4 or more. Our image compression and uncompression utilities (called fpack and funpack) that were used in this study are publicly available from the HEASARC web site.Users may run these stand-alone programs to compress and uncompress their own images.

Improved compression technique for multipass color printers

NASA Astrophysics Data System (ADS)

Honsinger, Chris

1998-01-01

A multipass color printer prints a color image by printing one color place at a time in a prescribed order, e.g., in a four-color systems, the cyan plane may be printed first, the magenta next, and so on. It is desirable to discard the data related to each color plane once it has been printed, so that data from the next print may be downloaded. In this paper, we present a compression scheme that allows the release of a color plane memory, but still takes advantage of the correlation between the color planes. The compression scheme is based on a block adaptive technique for decorrelating the color planes followed by a spatial lossy compression of the decorrelated data. A preferred method of lossy compression is the DCT-based JPEG compression standard, as it is shown that the block adaptive decorrelation operations can be efficiently performed in the DCT domain. The result of the compression technique are compared to that of using JPEG on RGB data without any decorrelating transform. In general, the technique is shown to improve the compression performance over a practical range of compression ratios by at least 30 percent in all images, and up to 45 percent in some images.

Displaying radiologic images on personal computers: image storage and compression--Part 2.

PubMed

Gillespy, T; Rowberg, A H

1994-02-01

This is part 2 of our article on image storage and compression, the third article of our series for radiologists and imaging scientists on displaying, manipulating, and analyzing radiologic images on personal computers. Image compression is classified as lossless (nondestructive) or lossy (destructive). Common lossless compression algorithms include variable-length bit codes (Huffman codes and variants), dictionary-based compression (Lempel-Ziv variants), and arithmetic coding. Huffman codes and the Lempel-Ziv-Welch (LZW) algorithm are commonly used for image compression. All of these compression methods are enhanced if the image has been transformed into a differential image based on a differential pulse-code modulation (DPCM) algorithm. The LZW compression after the DPCM image transformation performed the best on our example images, and performed almost as well as the best of the three commercial compression programs tested. Lossy compression techniques are capable of much higher data compression, but reduced image quality and compression artifacts may be noticeable. Lossy compression is comprised of three steps: transformation, quantization, and coding. Two commonly used transformation methods are the discrete cosine transformation and discrete wavelet transformation. In both methods, most of the image information is contained in a relatively few of the transformation coefficients. The quantization step reduces many of the lower order coefficients to 0, which greatly improves the efficiency of the coding (compression) step. In fractal-based image compression, image patterns are stored as equations that can be reconstructed at different levels of resolution.

A real-time ultrasonic field mapping system using a Fabry Pérot single pixel camera for 3D photoacoustic imaging

NASA Astrophysics Data System (ADS)

Huynh, Nam; Zhang, Edward; Betcke, Marta; Arridge, Simon R.; Beard, Paul; Cox, Ben

2015-03-01

A system for dynamic mapping of broadband ultrasound fields has been designed, with high frame rate photoacoustic imaging in mind. A Fabry-Pérot interferometric ultrasound sensor was interrogated using a coherent light single-pixel camera. Scrambled Hadamard measurement patterns were used to sample the acoustic field at the sensor, and either a fast Hadamard transform or a compressed sensing reconstruction algorithm were used to recover the acoustic pressure data. Frame rates of 80 Hz were achieved for 32x32 images even though no specialist hardware was used for the on-the-fly reconstructions. The ability of the system to obtain photocacoustic images with data compressions as low as 10% was also demonstrated.

Radiological Image Compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung Benedict

The movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve, and transmit the volume of digital images. Basic research into image data compression is necessary in order to move from a film-based department to an efficient digital -based department. Digital data compression technology consists of two types of compression technique: error-free and irreversible. Error -free image compression is desired; however, present techniques can only achieve compression ratio of from 1.5:1 to 3:1, depending upon the image characteristics. Irreversible image compression can achieve a much higher compression ratio; however, the image reconstructed from the compressed data shows some difference from the original image. This dissertation studies both error-free and irreversible image compression techniques. In particular, some modified error-free techniques have been tested and the recommended strategies for various radiological images are discussed. A full-frame bit-allocation irreversible compression technique has been derived. A total of 76 images which include CT head and body, and radiographs digitized to 2048 x 2048, 1024 x 1024, and 512 x 512 have been used to test this algorithm. The normalized mean -square-error (NMSE) on the difference image, defined as the difference between the original and the reconstructed image from a given compression ratio, is used as a global measurement on the quality of the reconstructed image. The NMSE's of total of 380 reconstructed and 380 difference images are measured and the results tabulated. Three complex compression methods are also suggested to compress images with special characteristics. Finally, various parameters which would effect the quality of the reconstructed images are discussed. A proposed hardware compression module is given in the last chapter.

Side information in coded aperture compressive spectral imaging

NASA Astrophysics Data System (ADS)

Galvis, Laura; Arguello, Henry; Lau, Daniel; Arce, Gonzalo R.

2017-02-01

Coded aperture compressive spectral imagers sense a three-dimensional cube by using two-dimensional projections of the coded and spectrally dispersed source. These imagers systems often rely on FPA detectors, SLMs, micromirror devices (DMDs), and dispersive elements. The use of the DMDs to implement the coded apertures facilitates the capture of multiple projections, each admitting a different coded aperture pattern. The DMD allows not only to collect the sufficient number of measurements for spectrally rich scenes or very detailed spatial scenes but to design the spatial structure of the coded apertures to maximize the information content on the compressive measurements. Although sparsity is the only signal characteristic usually assumed for reconstruction in compressing sensing, other forms of prior information such as side information have been included as a way to improve the quality of the reconstructions. This paper presents the coded aperture design in a compressive spectral imager with side information in the form of RGB images of the scene. The use of RGB images as side information of the compressive sensing architecture has two main advantages: the RGB is not only used to improve the reconstruction quality but to optimally design the coded apertures for the sensing process. The coded aperture design is based on the RGB scene and thus the coded aperture structure exploits key features such as scene edges. Real reconstructions of noisy compressed measurements demonstrate the benefit of the designed coded apertures in addition to the improvement in the reconstruction quality obtained by the use of side information.

A head-mounted compressive three-dimensional display system with polarization-dependent focus switching

NASA Astrophysics Data System (ADS)

Lee, Chang-Kun; Moon, Seokil; Lee, Byounghyo; Jeong, Youngmo; Lee, Byoungho

2016-10-01

A head-mounted compressive three-dimensional (3D) display system is proposed by combining polarization beam splitter (PBS), fast switching polarization rotator and micro display with high pixel density. According to the polarization state of the image controlled by polarization rotator, optical path of image in the PBS can be divided into transmitted and reflected components. Since optical paths of each image are spatially separated, it is possible to independently focus both images at different depth positions. Transmitted p-polarized and reflected s-polarized images can be focused by convex lens and mirror, respectively. When the focal lengths of the convex lens and mirror are properly determined, two image planes can be located in intended positions. The geometrical relationship is easily modulated by replacement of the components. The fast switching of polarization realizes the real-time operation of multi-focal image planes with a single display panel. Since it is possible to conserve the device characteristic of single panel, the high image quality, reliability and uniformity can be retained. For generating 3D images, layer images for compressive light field display between two image planes are calculated. Since the display panel with high pixel density is adopted, high quality 3D images are reconstructed. In addition, image degradation by diffraction between physically stacked display panels can be mitigated. Simple optical configuration of the proposed system is implemented and the feasibility of the proposed method is verified through experiments.

Geostationary Imaging FTS (GIFTS) Data Processing: Measurement Simulation and Compression

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Revercomb, H. E.; Thom, J.; Antonelli, P. B.; Osborne, B.; Tobin, D.; Knuteson, R.; Garcia, R.; Dutcher, S.; Li, J.

2001-01-01

GIFTS (Geostationary Imaging Fourier Transform Spectrometer), a forerunner of next generation geostationary satellite weather observing systems, will be built to fly on the NASA EO-3 geostationary orbit mission in 2004 to demonstrate the use of large area detector arrays and readouts. Timely high spatial resolution images and quantitative soundings of clouds, water vapor, temperature, and pollutants of the atmosphere for weather prediction and air quality monitoring will be achieved. GIFTS is novel in terms of providing many scientific returns that traditionally can only be achieved by separate advanced imaging and sounding systems. GIFTS' ability to obtain half-hourly high vertical density wind over the full earth disk is revolutionary. However, these new technologies bring forth many challenges for data transmission, archiving, and geophysical data processing. In this paper, we will focus on the aspect of data volume and downlink issues by conducting a GIFTS data compression experiment. We will discuss the scenario of using principal component analysis as a foundation for atmospheric data retrieval and compression of uncalibrated and un-normalized interferograms. The effects of compression on the degradation of the signal and noise reduction in interferogram and spectral domains will be highlighted. A simulation system developed to model the GIFTS instrument measurements is described in detail.

Research on the principle and experimentation of optical compressive spectral imaging

NASA Astrophysics Data System (ADS)

Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin

2013-12-01

The optical compressive spectral imaging method is a novel spectral imaging technique that draws in the inspiration of compressed sensing, which takes on the advantages such as reducing acquisition data amount, realizing snapshot imaging, increasing signal to noise ratio and so on. Considering the influence of the sampling quality on the ultimate imaging quality, researchers match the sampling interval with the modulation interval in former reported imaging system, while the depressed sampling rate leads to the loss on the original spectral resolution. To overcome that technical defect, the demand for the matching between the sampling interval and the modulation interval is disposed of and the spectral channel number of the designed experimental device increases more than threefold comparing to that of the previous method. Imaging experiment is carried out by use of the experiment installation and the spectral data cube of the shooting target is reconstructed with the acquired compressed image by use of the two-step iterative shrinkage/thresholding algorithms. The experimental result indicates that the spectral channel number increases effectively and the reconstructed data stays high-fidelity. The images and spectral curves are able to accurately reflect the spatial and spectral character of the target.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

The integrated design and archive of space-borne signal processing and compression coding

NASA Astrophysics Data System (ADS)

He, Qiang-min; Su, Hao-hang; Wu, Wen-bo

2017-10-01

With the increasing demand of users for the extraction of remote sensing image information, it is very urgent to significantly enhance the whole system's imaging quality and imaging ability by using the integrated design to achieve its compact structure, light quality and higher attitude maneuver ability. At this present stage, the remote sensing camera's video signal processing unit and image compression and coding unit are distributed in different devices. The volume, weight and consumption of these two units is relatively large, which unable to meet the requirements of the high mobility remote sensing camera. This paper according to the high mobility remote sensing camera's technical requirements, designs a kind of space-borne integrated signal processing and compression circuit by researching a variety of technologies, such as the high speed and high density analog-digital mixed PCB design, the embedded DSP technology and the image compression technology based on the special-purpose chips. This circuit lays a solid foundation for the research of the high mobility remote sensing camera.

Clinical evaluation of JPEG2000 compression for digital mammography

NASA Astrophysics Data System (ADS)

Sung, Min-Mo; Kim, Hee-Joung; Kim, Eun-Kyung; Kwak, Jin-Young; Yoo, Jae-Kyung; Yoo, Hyung-Sik

2002-06-01

Medical images, such as computed radiography (CR), and digital mammographic images will require large storage facilities and long transmission times for picture archiving and communications system (PACS) implementation. American College of Radiology and National Equipment Manufacturers Association (ACR/NEMA) group is planning to adopt a JPEG2000 compression algorithm in digital imaging and communications in medicine (DICOM) standard to better utilize medical images. The purpose of the study was to evaluate the compression ratios of JPEG2000 for digital mammographic images using peak signal-to-noise ratio (PSNR), receiver operating characteristic (ROC) analysis, and the t-test. The traditional statistical quality measures such as PSNR, which is a commonly used measure for the evaluation of reconstructed images, measures how the reconstructed image differs from the original by making pixel-by-pixel comparisons. The ability to accurately discriminate diseased cases from normal cases is evaluated using ROC curve analysis. ROC curves can be used to compare the diagnostic performance of two or more reconstructed images. The t test can be also used to evaluate the subjective image quality of reconstructed images. The results of the t test suggested that the possible compression ratios using JPEG2000 for digital mammographic images may be as much as 15:1 without visual loss or with preserving significant medical information at a confidence level of 99%, although both PSNR and ROC analyses suggest as much as 80:1 compression ratio can be achieved without affecting clinical diagnostic performance.

Compression techniques in tele-radiology

NASA Astrophysics Data System (ADS)

Lu, Tianyu; Xiong, Zixiang; Yun, David Y.

1999-10-01

This paper describes a prototype telemedicine system for remote 3D radiation treatment planning. Due to voluminous medical image data and image streams generated in interactive frame rate involved in the application, the importance of deploying adjustable lossy to lossless compression techniques is emphasized in order to achieve acceptable performance via various kinds of communication networks. In particular, the compression of the data substantially reduces the transmission time and therefore allows large-scale radiation distribution simulation and interactive volume visualization using remote supercomputing resources in a timely fashion. The compression algorithms currently used in the software we developed are JPEG and H.263 lossy methods and Lempel-Ziv (LZ77) lossless methods. Both objective and subjective assessment of the effect of lossy compression methods on the volume data are conducted. Favorable results are obtained showing that substantial compression ratio is achievable within distortion tolerance. From our experience, we conclude that 30dB (PSNR) is about the lower bound to achieve acceptable quality when applying lossy compression to anatomy volume data (e.g. CT). For computer simulated data, much higher PSNR (up to 100dB) is expectable. This work not only introduces such novel approach for delivering medical services that will have significant impact on the existing cooperative image-based services, but also provides a platform for the physicians to assess the effects of lossy compression techniques on the diagnostic and aesthetic appearance of medical imaging.

Evaluation of Algorithms for Compressing Hyperspectral Data

NASA Technical Reports Server (NTRS)

Cook, Sid; Harsanyi, Joseph; Faber, Vance

2003-01-01

With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Dandan; Li, Houqiang

2017-12-01

Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.

1994-01-01

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Image quality (IQ) guided multispectral image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Chen, Genshe; Wang, Zhonghai; Blasch, Erik

2016-05-01

Image compression is necessary for data transportation, which saves both transferring time and storage space. In this paper, we focus on our discussion on lossy compression. There are many standard image formats and corresponding compression algorithms, for examples, JPEG (DCT -- discrete cosine transform), JPEG 2000 (DWT -- discrete wavelet transform), BPG (better portable graphics) and TIFF (LZW -- Lempel-Ziv-Welch). The image quality (IQ) of decompressed image will be measured by numerical metrics such as root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural Similarity (SSIM) Index. Given an image and a specified IQ, we will investigate how to select a compression method and its parameters to achieve an expected compression. Our scenario consists of 3 steps. The first step is to compress a set of interested images by varying parameters and compute their IQs for each compression method. The second step is to create several regression models per compression method after analyzing the IQ-measurement versus compression-parameter from a number of compressed images. The third step is to compress the given image with the specified IQ using the selected compression method (JPEG, JPEG2000, BPG, or TIFF) according to the regressed models. The IQ may be specified by a compression ratio (e.g., 100), then we will select the compression method of the highest IQ (SSIM, or PSNR). Or the IQ may be specified by a IQ metric (e.g., SSIM = 0.8, or PSNR = 50), then we will select the compression method of the highest compression ratio. Our experiments tested on thermal (long-wave infrared) images (in gray scales) showed very promising results.

High-quality JPEG compression history detection for fake uncompressed images

NASA Astrophysics Data System (ADS)

Zhang, Rong; Wang, Rang-Ding; Guo, Li-Jun; Jiang, Bao-Chuan

2017-05-01

Authenticity is one of the most important evaluation factors of images for photography competitions or journalism. Unusual compression history of an image often implies the illicit intent of its author. Our work aims at distinguishing real uncompressed images from fake uncompressed images that are saved in uncompressed formats but have been previously compressed. To detect the potential image JPEG compression, we analyze the JPEG compression artifacts based on the tetrolet covering, which corresponds to the local image geometrical structure. Since the compression can alter the structure information, the tetrolet covering indexes may be changed if a compression is performed on the test image. Such changes can provide valuable clues about the image compression history. To be specific, the test image is first compressed with different quality factors to generate a set of temporary images. Then, the test image is compared with each temporary image block-by-block to investigate whether the tetrolet covering index of each 4×4 block is different between them. The percentages of the changed tetrolet covering indexes corresponding to the quality factors (from low to high) are computed and used to form the p-curve, the local minimum of which may indicate the potential compression. Our experimental results demonstrate the advantage of our method to detect JPEG compressions of high quality, even the highest quality factors such as 98, 99, or 100 of the standard JPEG compression, from uncompressed-format images. At the same time, our detection algorithm can accurately identify the corresponding compression quality factor.

Storage, retrieval, and edit of digital video using Motion JPEG

NASA Astrophysics Data System (ADS)

Sudharsanan, Subramania I.; Lee, D. H.

1994-04-01

In a companion paper we describe a Micro Channel adapter card that can perform real-time JPEG (Joint Photographic Experts Group) compression of a 640 by 480 24-bit image within 1/30th of a second. Since this corresponds to NTSC video rates at considerably good perceptual quality, this system can be used for real-time capture and manipulation of continuously fed video. To facilitate capturing the compressed video in a storage medium, an IBM Bus master SCSI adapter with cache is utilized. Efficacy of the data transfer mechanism is considerably improved using the System Control Block architecture, an extension to Micro Channel bus masters. We show experimental results that the overall system can perform at compressed data rates of about 1.5 MBytes/second sustained and with sporadic peaks to about 1.8 MBytes/second depending on the image sequence content. We also describe mechanisms to access the compressed data very efficiently through special file formats. This in turn permits creation of simpler sequence editors. Another advantage of the special file format is easy control of forward, backward and slow motion playback. The proposed method can be extended for design of a video compression subsystem for a variety of personal computing systems.

Experimental study of a DMD based compressive line sensing imaging system in the turbulence environment

NASA Astrophysics Data System (ADS)

Ouyang, Bing; Hou, Weilin; Gong, Cuiling; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.

2016-05-01

The Compressive Line Sensing (CLS) active imaging system has been demonstrated to be effective in scattering mediums, such as turbid coastal water through simulations and test tank experiments. Since turbulence is encountered in many atmospheric and underwater surveillance applications, a new CLS imaging prototype was developed to investigate the effectiveness of the CLS concept in a turbulence environment. Compared with earlier optical bench top prototype, the new system is significantly more robust and compact. A series of experiments were conducted at the Naval Research Lab's optical turbulence test facility with the imaging path subjected to various turbulence intensities. In addition to validating the system design, we obtained some unexpected exciting results - in the strong turbulence environment, the time-averaged measurements using the new CLS imaging prototype improved both SNR and resolution of the reconstructed images. We will discuss the implications of the new findings, the challenges of acquiring data through strong turbulence environment, and future enhancements.

Experimental Studies on a Compact Storage Scheme for Wavelet-based Multiresolution Subregion Retrieval

NASA Technical Reports Server (NTRS)

Poulakidas, A.; Srinivasan, A.; Egecioglu, O.; Ibarra, O.; Yang, T.

1996-01-01

Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress images effectively. In order to use them for image library systems, a compact storage scheme for quantized coefficient wavelet data must be developed with a support for fast subregion retrieval. We have designed such a scheme and in this paper we provide experimental studies to demonstrate that it achieves good image compression ratios, while providing a natural indexing mechanism that facilitates fast retrieval of portions of the image at various resolutions.

Application of content-based image compression to telepathology

NASA Astrophysics Data System (ADS)

Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

2002-05-01

Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

Optical information authentication using compressed double-random-phase-encoded images and quick-response codes.

PubMed

Wang, Xiaogang; Chen, Wen; Chen, Xudong

2015-03-09

In this paper, we develop a new optical information authentication system based on compressed double-random-phase-encoded images and quick-response (QR) codes, where the parameters of optical lightwave are used as keys for optical decryption and the QR code is a key for verification. An input image attached with QR code is first optically encoded in a simplified double random phase encoding (DRPE) scheme without using interferometric setup. From the single encoded intensity pattern recorded by a CCD camera, a compressed double-random-phase-encoded image, i.e., the sparse phase distribution used for optical decryption, is generated by using an iterative phase retrieval technique with QR code. We compare this technique to the other two methods proposed in literature, i.e., Fresnel domain information authentication based on the classical DRPE with holographic technique and information authentication based on DRPE and phase retrieval algorithm. Simulation results show that QR codes are effective on improving the security and data sparsity of optical information encryption and authentication system.

Astronomical image data compression by morphological skeleton transformation

NASA Astrophysics Data System (ADS)

Huang, L.; Bijaoui, A.

A compression method adapted for exact restoring of the detected objects and based on the morphological skeleton transformation is presented. The morphological skeleton provides a complete and compact description of an object and gives an efficient compression rate. The flexibility of choosing a structuring element adapted to different images and the simplicity of the implementation are considered to be advantages of the method. The experiment was carried out on three typical astronomical images. The first two images were obtained by digitizing a Palomar Schmidt photographic plate in a coma field with the PDS microdensitometer at Nice Observatory. The third image was obtained by CCD camera at the Pic du Midi Observatory. Each pixel was coded by 16 bits and stored at a computer system (VAX785) with STII format. Each image is characterized by 256 x 256 pixels. It is found that first image represents a stellar field, the second represents a set of galaxies in the Coma, and the third image contains an elliptical galaxy.

Optimizing pulse compressibility in completely all-fibered Ytterbium chirped pulse amplifiers for in vivo two photon laser scanning microscopy

PubMed Central

Fernández, A.; Grüner-Nielsen, L.; Andreana, M.; Stadler, M.; Kirchberger, S.; Sturtzel, C.; Distel, M.; Zhu, L.; Kautek, W.; Leitgeb, R.; Baltuska, A.; Jespersen, K.; Verhoef, A.

2017-01-01

A simple and completely all-fiber Yb chirped pulse amplifier that uses a dispersion matched fiber stretcher and a spliced-on hollow core photonic bandgap fiber compressor is applied in nonlinear optical microscopy. This stretching-compression approach improves compressibility and helps to maximize the fluorescence signal in two-photon laser scanning microscopy as compared with approaches that use standard single mode fibers as stretcher. We also show that in femtosecond all-fiber systems, compensation of higher order dispersion terms is relevant even for pulses with relatively narrow bandwidths for applications relying on nonlinear optical effects. The completely all-fiber system was applied to image green fluorescent beads, a stained lily-of-the-valley root and rat-tail tendon. We also demonstrated in vivo imaging in zebrafish larvae, where we simultaneously measure second harmonic and fluorescence from two-photon excited red-fluorescent protein. Since the pulses are compressed in a fiber, this source is especially suited for upgrading existing laser scanning (confocal) microscopes with multiphoton imaging capabilities in space restricted settings or for incorporation in endoscope-based microscopy. PMID:28856032

Optimizing pulse compressibility in completely all-fibered Ytterbium chirped pulse amplifiers for in vivo two photon laser scanning microscopy.

PubMed

Fernández, A; Grüner-Nielsen, L; Andreana, M; Stadler, M; Kirchberger, S; Sturtzel, C; Distel, M; Zhu, L; Kautek, W; Leitgeb, R; Baltuska, A; Jespersen, K; Verhoef, A

2017-08-01

A simple and completely all-fiber Yb chirped pulse amplifier that uses a dispersion matched fiber stretcher and a spliced-on hollow core photonic bandgap fiber compressor is applied in nonlinear optical microscopy. This stretching-compression approach improves compressibility and helps to maximize the fluorescence signal in two-photon laser scanning microscopy as compared with approaches that use standard single mode fibers as stretcher. We also show that in femtosecond all-fiber systems, compensation of higher order dispersion terms is relevant even for pulses with relatively narrow bandwidths for applications relying on nonlinear optical effects. The completely all-fiber system was applied to image green fluorescent beads, a stained lily-of-the-valley root and rat-tail tendon. We also demonstrated in vivo imaging in zebrafish larvae, where we simultaneously measure second harmonic and fluorescence from two-photon excited red-fluorescent protein. Since the pulses are compressed in a fiber, this source is especially suited for upgrading existing laser scanning (confocal) microscopes with multiphoton imaging capabilities in space restricted settings or for incorporation in endoscope-based microscopy.

A joint source-channel distortion model for JPEG compressed images.

PubMed

Sabir, Muhammad F; Sheikh, Hamid Rahim; Heath, Robert W; Bovik, Alan C

2006-06-01

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.

Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh I.; Keymeulen, Didier; Kimesh, Matthew A.

2012-01-01

Modern hyperspectral imaging systems are able to acquire far more data than can be downlinked from a spacecraft. Onboard data compression helps to alleviate this problem, but requires a system capable of power efficiency and high throughput. Software solutions have limited throughput performance and are power-hungry. Dedicated hardware solutions can provide both high throughput and power efficiency, while taking the load off of the main processor. Thus a hardware compression system was developed. The implementation uses a field-programmable gate array (FPGA). The implementation is based on the fast lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral-Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which achieves excellent compression performance and has low complexity. This algorithm performs predictive compression using an adaptive filtering method, and uses adaptive Golomb coding. The implementation also packetizes the coded data. The FL algorithm is well suited for implementation in hardware. In the FPGA implementation, one sample is compressed every clock cycle, which makes for a fast and practical realtime solution for space applications. Benefits of this implementation are: 1) The underlying algorithm achieves a combination of low complexity and compression effectiveness that exceeds that of techniques currently in use. 2) The algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. 3) Hardware acceleration provides a throughput improvement of 10 to 100 times vs. the software implementation. A prototype of the compressor is available in software, but it runs at a speed that does not meet spacecraft requirements. The hardware implementation targets the Xilinx Virtex IV FPGAs, and makes the use of this compressor practical for Earth satellites as well as beyond-Earth missions with hyperspectral instruments.

Image compression/decompression based on mathematical transform, reduction/expansion, and image sharpening

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1997-01-01

An image represented in a first image array of pixels is first decimated in two dimensions before being compressed by a predefined compression algorithm such as JPEG. Another possible predefined compression algorithm can involve a wavelet technique. The compressed, reduced image is then transmitted over the limited bandwidth transmission medium, and the transmitted image is decompressed using an algorithm which is an inverse of the predefined compression algorithm (such as reverse JPEG). The decompressed, reduced image is then interpolated back to its original array size. Edges (contours) in the image are then sharpened to enhance the perceptual quality of the reconstructed image. Specific sharpening techniques are described.

Spatial compression algorithm for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R [Albuquerque, NM

2008-07-15

A method for spatially compressing data sets enables the efficient analysis of very large multivariate images. The spatial compression algorithms use a wavelet transformation to map an image into a compressed image containing a smaller number of pixels that retain the original image's information content. Image analysis can then be performed on a compressed data matrix consisting of a reduced number of significant wavelet coefficients. Furthermore, a block algorithm can be used for performing common operations more efficiently. The spatial compression algorithms can be combined with spectral compression algorithms to provide further computational efficiencies.

A Wireless Capsule Endoscope System With Low-Power Controlling and Processing ASIC.

PubMed

Xinkai Chen; Xiaoyu Zhang; Linwei Zhang; Xiaowen Li; Nan Qi; Hanjun Jiang; Zhihua Wang

2009-02-01

This paper presents the design of a wireless capsule endoscope system. The proposed system is mainly composed of a CMOS image sensor, a RF transceiver and a low-power controlling and processing application specific integrated circuit (ASIC). Several design challenges involving system power reduction, system miniaturization and wireless wake-up method are resolved by employing optimized system architecture, integration of an area and power efficient image compression module, a power management unit (PMU) and a novel wireless wake-up subsystem with zero standby current in the ASIC design. The ASIC has been fabricated in 0.18-mum CMOS technology with a die area of 3.4 mm * 3.3 mm. The digital baseband can work under a power supply down to 0.95 V with a power dissipation of 1.3 mW. The prototype capsule based on the ASIC and a data recorder has been developed. Test result shows that proposed system architecture with local image compression lead to an average of 45% energy reduction for transmitting an image frame.

Computer-aided, multi-modal, and compression diffuse optical studies of breast tissue

NASA Astrophysics Data System (ADS)

Busch, David Richard, Jr.

Diffuse Optical Tomography and Spectroscopy permit measurement of important physiological parameters non-invasively through ˜10 cm of tissue. I have applied these techniques in measurements of human breast and breast cancer. My thesis integrates three loosely connected themes in this context: multi-modal breast cancer imaging, automated data analysis of breast cancer images, and microvascular hemodynamics of breast under compression. As per the first theme, I describe construction, testing, and the initial clinical usage of two generations of imaging systems for simultaneous diffuse optical and magnetic resonance imaging. The second project develops a statistical analysis of optical breast data from many spatial locations in a population of cancers to derive a novel optical signature of malignancy; I then apply this data-derived signature for localization of cancer in additional subjects. Finally, I construct and deploy diffuse optical instrumentation to measure blood content and blood flow during breast compression; besides optics, this research has implications for any method employing breast compression, e.g., mammography.

Output MSE and PSNR prediction in DCT-based lossy compression of remote sensing images

NASA Astrophysics Data System (ADS)

Kozhemiakin, Ruslan A.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

2017-10-01

Amount and size of remote sensing (RS) images acquired by modern systems are so large that data have to be compressed in order to transfer, save and disseminate them. Lossy compression becomes more popular for aforementioned situations. But lossy compression has to be applied carefully with providing acceptable level of introduced distortions not to lose valuable information contained in data. Then introduced losses have to be controlled and predicted and this is problematic for many coders. In this paper, we analyze possibilities of predicting mean square error or, equivalently, PSNR for coders based on discrete cosine transform (DCT) applied either for compressing singlechannel RS images or multichannel data in component-wise manner. The proposed approach is based on direct dependence between distortions introduced due to DCT coefficient quantization and losses in compressed data. One more innovation deals with possibility to employ a limited number (percentage) of blocks for which DCT-coefficients have to be calculated. This accelerates prediction and makes it considerably faster than compression itself. There are two other advantages of the proposed approach. First, it is applicable for both uniform and non-uniform quantization of DCT coefficients. Second, the approach is quite general since it works for several analyzed DCT-based coders. The simulation results are obtained for standard test images and then verified for real-life RS data.

Comparison between various patch wise strategies for reconstruction of ultra-spectral cubes captured with a compressive sensing system

NASA Astrophysics Data System (ADS)

Oiknine, Yaniv; August, Isaac Y.; Revah, Liat; Stern, Adrian

2016-05-01

Recently we introduced a Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) system. The system is based on a single Liquid Crystal (LC) cell and a parallel sensor array where the liquid crystal cell performs spectral encoding. Within the framework of compressive sensing, the CS-MUSI system is able to reconstruct ultra-spectral cubes captured with only an amount of ~10% samples compared to a conventional system. Despite the compression, the technique is extremely complex computationally, because reconstruction of ultra-spectral images requires processing huge data cubes of Gigavoxel size. Fortunately, the computational effort can be alleviated by using separable operation. An additional way to reduce the reconstruction effort is to perform the reconstructions on patches. In this work, we consider processing on various patch shapes. We present an experimental comparison between various patch shapes chosen to process the ultra-spectral data captured with CS-MUSI system. The patches may be one dimensional (1D) for which the reconstruction is carried out spatially pixel-wise, or two dimensional (2D) - working on spatial rows/columns of the ultra-spectral cube, as well as three dimensional (3D).

Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

High throughput dual-wavelength temperature distribution imaging via compressive imaging

NASA Astrophysics Data System (ADS)

Yao, Xu-Ri; Lan, Ruo-Ming; Liu, Xue-Feng; Zhu, Ge; Zheng, Fu; Yu, Wen-Kai; Zhai, Guang-Jie

2018-03-01

Thermal imaging is an essential tool in a wide variety of research areas. In this work we demonstrate high-throughput double-wavelength temperature distribution imaging using a modified single-pixel camera without the requirement of a beam splitter (BS). A digital micro-mirror device (DMD) is utilized to display binary masks and split the incident radiation, which eliminates the necessity of a BS. Because the spatial resolution is dictated by the DMD, this thermal imaging system has the advantage of perfect spatial registration between the two images, which limits the need for the pixel registration and fine adjustments. Two bucket detectors, which measures the total light intensity reflected from the DMD, are employed in this system and yield an improvement in the detection efficiency of the narrow-band radiation. A compressive imaging algorithm is utilized to achieve under-sampling recovery. A proof-of-principle experiment was presented to demonstrate the feasibility of this structure.

Coding Strategies and Implementations of Compressive Sensing

NASA Astrophysics Data System (ADS)

Tsai, Tsung-Han

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

New patient-controlled abdominal compression method in radiography: radiation dose and image quality.

PubMed

Piippo-Huotari, Oili; Norrman, Eva; Anderzén-Carlsson, Agneta; Geijer, Håkan

2018-05-01

The radiation dose for patients can be reduced with many methods and one way is to use abdominal compression. In this study, the radiation dose and image quality for a new patient-controlled compression device were compared with conventional compression and compression in the prone position . To compare radiation dose and image quality of patient-controlled compression compared with conventional and prone compression in general radiography. An experimental design with quantitative approach. After obtaining the approval of the ethics committee, a consecutive sample of 48 patients was examined with the standard clinical urography protocol. The radiation doses were measured as dose-area product and analyzed with a paired t-test. The image quality was evaluated by visual grading analysis. Four radiologists evaluated each image individually by scoring nine criteria modified from the European quality criteria for diagnostic radiographic images. There was no significant difference in radiation dose or image quality between conventional and patient-controlled compression. Prone position resulted in both higher dose and inferior image quality. Patient-controlled compression gave similar dose levels as conventional compression and lower than prone compression. Image quality was similar with both patient-controlled and conventional compression and was judged to be better than in the prone position.

Volume and tissue composition preserving deformation of breast CT images to simulate breast compression in mammographic imaging

NASA Astrophysics Data System (ADS)

Han, Tao; Chen, Lingyun; Lai, Chao-Jen; Liu, Xinming; Shen, Youtao; Zhong, Yuncheng; Ge, Shuaiping; Yi, Ying; Wang, Tianpeng; Shaw, Chris C.

2009-02-01

Images of mastectomy breast specimens have been acquired with a bench top experimental Cone beam CT (CBCT) system. The resulting images have been segmented to model an uncompressed breast for simulation of various CBCT techniques. To further simulate conventional or tomosynthesis mammographic imaging for comparison with the CBCT technique, a deformation technique was developed to convert the CT data for an uncompressed breast to a compressed breast without altering the breast volume or regional breast density. With this technique, 3D breast deformation is separated into two 2D deformations in coronal and axial views. To preserve the total breast volume and regional tissue composition, each 2D deformation step was achieved by altering the square pixels into rectangular ones with the pixel areas unchanged and resampling with the original square pixels using bilinear interpolation. The compression was modeled by first stretching the breast in the superior-inferior direction in the coronal view. The image data were first deformed by distorting the voxels with a uniform distortion ratio. These deformed data were then deformed again using distortion ratios varying with the breast thickness and re-sampled. The deformation procedures were applied in the axial view to stretch the breast in the chest wall to nipple direction while shrinking it in the mediolateral to lateral direction re-sampled and converted into data for uniform cubic voxels. Threshold segmentation was applied to the final deformed image data to obtain the 3D compressed breast model. Our results show that the original segmented CBCT image data were successfully converted into those for a compressed breast with the same volume and regional density preserved. Using this compressed breast model, conventional and tomosynthesis mammograms were simulated for comparison with CBCT.

Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence.

PubMed

Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

2008-04-01

This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data.

Image splitting and remapping method for radiological image compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

1990-07-01

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

Optimization of the segmented method for optical compression and multiplexing system

NASA Astrophysics Data System (ADS)

Al Falou, Ayman

2002-05-01

Because of the constant increasing demands of images exchange, and despite the ever increasing bandwidth of the networks, compression and multiplexing of images is becoming inseparable from their generation and display. For high resolution real time motion pictures, electronic performing of compression requires complex and time-consuming processing units. On the contrary, by its inherent bi-dimensional character, coherent optics is well fitted to perform such processes that are basically bi-dimensional data handling in the Fourier domain. Additionally, the main limiting factor that was the maximum frame rate is vanishing because of the recent improvement of spatial light modulator technology. The purpose of this communication is to benefit from recent optical correlation algorithms. The segmented filtering used to store multi-references in a given space bandwidth product optical filter can be applied to networks to compress and multiplex images in a given bandwidth channel.

Image compression/decompression based on mathematical transform, reduction/expansion, and image sharpening

DOEpatents

Fu, C.Y.; Petrich, L.I.

1997-12-30

An image represented in a first image array of pixels is first decimated in two dimensions before being compressed by a predefined compression algorithm such as JPEG. Another possible predefined compression algorithm can involve a wavelet technique. The compressed, reduced image is then transmitted over the limited bandwidth transmission medium, and the transmitted image is decompressed using an algorithm which is an inverse of the predefined compression algorithm (such as reverse JPEG). The decompressed, reduced image is then interpolated back to its original array size. Edges (contours) in the image are then sharpened to enhance the perceptual quality of the reconstructed image. Specific sharpening techniques are described. 22 figs.

Advanced imaging communication system

NASA Technical Reports Server (NTRS)

Hilbert, E. E.; Rice, R. F.

1977-01-01

Key elements of system are imaging and nonimaging sensors, data compressor/decompressor, interleaved Reed-Solomon block coder, convolutional-encoded/Viterbi-decoded telemetry channel, and Reed-Solomon decoding. Data compression provides efficient representation of sensor data, and channel coding improves reliability of data transmission.

The compressed breast during mammography and breast tomosynthesis: in vivo shape characterization and modeling

NASA Astrophysics Data System (ADS)

Rodríguez-Ruiz, Alejandro; Agasthya, Greeshma A.; Sechopoulos, Ioannis

2017-09-01

To characterize and develop a patient-based 3D model of the compressed breast undergoing mammography and breast tomosynthesis. During this IRB-approved, HIPAA-compliant study, 50 women were recruited to undergo 3D breast surface imaging with structured light (SL) during breast compression, along with simultaneous acquisition of a tomosynthesis image. A pair of SL systems were used to acquire 3D surface images by projecting 24 different patterns onto the compressed breast and capturing their reflection off the breast surface in approximately 12-16 s. The 3D surface was characterized and modeled via principal component analysis. The resulting surface model was combined with a previously developed 2D model of projected compressed breast shapes to generate a full 3D model. Data from ten patients were discarded due to technical problems during image acquisition. The maximum breast thickness (found at the chest-wall) had an average value of 56 mm, and decreased 13% towards the nipple (breast tilt angle of 5.2°). The portion of the breast not in contact with the compression paddle or the support table extended on average 17 mm, 18% of the chest-wall to nipple distance. The outermost point along the breast surface lies below the midline of the total thickness. A complete 3D model of compressed breast shapes was created and implemented as a software application available for download, capable of generating new random realistic 3D shapes of breasts undergoing compression. Accurate characterization and modeling of the breast curvature and shape was achieved and will be used for various image processing and clinical tasks.

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

Real-time compression of raw computed tomography data: technology, architecture, and benefits

NASA Astrophysics Data System (ADS)

Wegener, Albert; Chandra, Naveen; Ling, Yi; Senzig, Robert; Herfkens, Robert

2009-02-01

Compression of computed tomography (CT) projection samples reduces slip ring and disk drive costs. A lowcomplexity, CT-optimized compression algorithm called Prism CTTM achieves at least 1.59:1 and up to 2.75:1 lossless compression on twenty-six CT projection data sets. We compare the lossless compression performance of Prism CT to alternative lossless coders, including Lempel-Ziv, Golomb-Rice, and Huffman coders using representative CT data sets. Prism CT provides the best mean lossless compression ratio of 1.95:1 on the representative data set. Prism CT compression can be integrated into existing slip rings using a single FPGA. Prism CT decompression operates at 100 Msamp/sec using one core of a dual-core Xeon CPU. We describe a methodology to evaluate the effects of lossy compression on image quality to achieve even higher compression ratios. We conclude that lossless compression of raw CT signals provides significant cost savings and performance improvements for slip rings and disk drive subsystems in all CT machines. Lossy compression should be considered in future CT data acquisition subsystems because it provides even more system benefits above lossless compression while achieving transparent diagnostic image quality. This result is demonstrated on a limited dataset using appropriately selected compression ratios and an experienced radiologist.

Low bit-rate image compression via adaptive down-sampling and constrained least squares upconversion.

PubMed

Wu, Xiaolin; Zhang, Xiangjun; Wang, Xiaohan

2009-03-01

Recently, many researchers started to challenge a long-standing practice of digital photography: oversampling followed by compression and pursuing more intelligent sparse sampling techniques. In this paper, we propose a practical approach of uniform down sampling in image space and yet making the sampling adaptive by spatially varying, directional low-pass prefiltering. The resulting down-sampled prefiltered image remains a conventional square sample grid, and, thus, it can be compressed and transmitted without any change to current image coding standards and systems. The decoder first decompresses the low-resolution image and then upconverts it to the original resolution in a constrained least squares restoration process, using a 2-D piecewise autoregressive model and the knowledge of directional low-pass prefiltering. The proposed compression approach of collaborative adaptive down-sampling and upconversion (CADU) outperforms JPEG 2000 in PSNR measure at low to medium bit rates and achieves superior visual quality, as well. The superior low bit-rate performance of the CADU approach seems to suggest that oversampling not only wastes hardware resources and energy, and it could be counterproductive to image quality given a tight bit budget.

Temporary morphological changes in plus disease induced during contact digital imaging

PubMed Central

Zepeda-Romero, L C; Martinez-Perez, M E; Ruiz-Velasco, S; Ramirez-Ortiz, M A; Gutierrez-Padilla, J A

2011-01-01

Objective To compare and quantify the retinal vascular changes induced by non-intentional pressure contact by digital handheld camera during retinopathy of prematurity (ROP) imaging by means of a computer-based image analysis system, Retinal Image multiScale Analysis. Methods A set of 10 wide-angle retinal pairs of photographs per patient, who underwent routine ROP examinations, was measured. Vascular trees were matched between ‘compression artifact' (absence of the vascular column at the optic nerve) and ‘not compression artifact' conditions. Parameters were analyzed using a two-level linear model for each individual parameter for arterioles and venules separately: integrated curvature (IC), diameter (d), and tortuosity index (TI). Results Images affected with compression artifact showed significant vascular d (P<0.01) changes in both arteries and veins, as well as in artery IC (P<0.05). Vascular TI remained unchanged in both groups. Conclusions Non-adverted corneal pressure with the RetCam lens could compress and decrease intra-arterial diameter or even collapse retinal vessels. Careful attention to technique is essential to avoid absence of the arterial blood column at the optic nerve head that is indicative of increased pressure during imaging. PMID:21760627

Convolutional neural network-based classification system design with compressed wireless sensor network images.

PubMed

Ahn, Jungmo; Park, JaeYeon; Park, Donghwan; Paek, Jeongyeup; Ko, JeongGil

2018-01-01

With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.

Compressed domain indexing of losslessly compressed images

NASA Astrophysics Data System (ADS)

Schaefer, Gerald

2001-12-01

Image retrieval and image compression have been pursued separately in the past. Only little research has been done on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to uncompress them first. In this paper methods for image retrieval in the compressed domain of losslessly compressed images are introduced. While most image compression techniques are lossy, i.e. discard visually less significant information, lossless techniques are still required in fields like medical imaging or in situations where images must not be changed due to legal reasons. The algorithms in this paper are based on predictive coding methods where a pixel is encoded based on the pixel values of its (already encoded) neighborhood. The first method is based on an understanding that predictively coded data is itself indexable and represents a textural description of the image. The second method operates directly on the entropy encoded data by comparing codebooks of images. Experiments show good image retrieval results for both approaches.

Design of a receiver operating characteristic (ROC) study of 10:1 lossy image compression

NASA Astrophysics Data System (ADS)

Collins, Cary A.; Lane, David; Frank, Mark S.; Hardy, Michael E.; Haynor, David R.; Smith, Donald V.; Parker, James E.; Bender, Gregory N.; Kim, Yongmin

1994-04-01

The digital archiving system at Madigan Army Medical Center (MAMC) uses a 10:1 lossy data compression algorithm for most forms of computed radiography. A systematic study on the potential effect of lossy image compression on patient care has been initiated with a series of studies focused on specific diagnostic tasks. The studies are based upon the receiver operating characteristic (ROC) method of analysis for diagnostic systems. The null hypothesis is that observer performance with approximately 10:1 compressed and decompressed images is not different from using original, uncompressed images for detecting subtle pathologic findings seen on computed radiographs of bone, chest, or abdomen, when viewed on a high-resolution monitor. Our design involves collecting cases from eight pathologic categories. Truth is determined by committee using confirmatory studies performed during routine clinical practice whenever possible. Software has been developed to aid in case collection and to allow reading of the cases for the study using stand-alone Siemens Litebox workstations. Data analysis uses two methods, ROC analysis and free-response ROC (FROC) methods. This study will be one of the largest ROC/FROC studies of its kind and could benefit clinical radiology practice using PACS technology. The study design and results from a pilot FROC study are presented.

Dissemination of compressed satellite imagery within the Navy SPAWAR Central Site Product Display environment

NASA Technical Reports Server (NTRS)

Kiselyov, Oleg; Fisher, Paul

1995-01-01

This paper presents a case study of integration of compression techniques within a satellite image communication component of an actual tactical weather information dissemination system. The paper describes history and requirements of the project, and discusses the information flow, request/reply protocols, error handling, and, especially, system integration issues: specification of compression parameters and the place and time for compressor/decompressor plug-ins. A case for a non-uniform compression of satellite imagery is presented, and its implementation in the current system id demonstrated. The paper gives special attention to challenges of moving the system towards the use of standard, non-proprietary protocols (smtp and http) and new technologies (OpenDoc), and reports the ongoing work in this direction.

Image acquisition system using on sensor compressed sampling technique

NASA Astrophysics Data System (ADS)

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%.

Fast and accurate face recognition based on image compression

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2017-05-01

Image compression is desired for many image-related applications especially for network-based applications with bandwidth and storage constraints. The face recognition community typical reports concentrate on the maximal compression rate that would not decrease the recognition accuracy. In general, the wavelet-based face recognition methods such as EBGM (elastic bunch graph matching) and FPB (face pattern byte) are of high performance but run slowly due to their high computation demands. The PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) algorithms run fast but perform poorly in face recognition. In this paper, we propose a novel face recognition method based on standard image compression algorithm, which is termed as compression-based (CPB) face recognition. First, all gallery images are compressed by the selected compression algorithm. Second, a mixed image is formed with the probe and gallery images and then compressed. Third, a composite compression ratio (CCR) is computed with three compression ratios calculated from: probe, gallery and mixed images. Finally, the CCR values are compared and the largest CCR corresponds to the matched face. The time cost of each face matching is about the time of compressing the mixed face image. We tested the proposed CPB method on the "ASUMSS face database" (visible and thermal images) from 105 subjects. The face recognition accuracy with visible images is 94.76% when using JPEG compression. On the same face dataset, the accuracy of FPB algorithm was reported as 91.43%. The JPEG-compressionbased (JPEG-CPB) face recognition is standard and fast, which may be integrated into a real-time imaging device.

A database for assessment of effect of lossy compression on digital mammograms

NASA Astrophysics Data System (ADS)

Wang, Jiheng; Sahiner, Berkman; Petrick, Nicholas; Pezeshk, Aria

2018-03-01

With widespread use of screening digital mammography, efficient storage of the vast amounts of data has become a challenge. While lossless image compression causes no risk to the interpretation of the data, it does not allow for high compression rates. Lossy compression and the associated higher compression ratios are therefore more desirable. The U.S. Food and Drug Administration (FDA) currently interprets the Mammography Quality Standards Act as prohibiting lossy compression of digital mammograms for primary image interpretation, image retention, or transfer to the patient or her designated recipient. Previous work has used reader studies to determine proper usage criteria for evaluating lossy image compression in mammography, and utilized different measures and metrics to characterize medical image quality. The drawback of such studies is that they rely on a threshold on compression ratio as the fundamental criterion for preserving the quality of images. However, compression ratio is not a useful indicator of image quality. On the other hand, many objective image quality metrics (IQMs) have shown excellent performance for natural image content for consumer electronic applications. In this paper, we create a new synthetic mammogram database with several unique features. We compare and characterize the impact of image compression on several clinically relevant image attributes such as perceived contrast and mass appearance for different kinds of masses. We plan to use this database to develop a new objective IQM for measuring the quality of compressed mammographic images to help determine the allowed maximum compression for different kinds of breasts and masses in terms of visual and diagnostic quality.

Digital map databases in support of avionic display systems

NASA Astrophysics Data System (ADS)

Trenchard, Michael E.; Lohrenz, Maura C.; Rosche, Henry, III; Wischow, Perry B.

1991-08-01

The emergence of computerized mission planning systems (MPS) and airborne digital moving map systems (DMS) has necessitated the development of a global database of raster aeronautical chart data specifically designed for input to these systems. The Naval Oceanographic and Atmospheric Research Laboratory''s (NOARL) Map Data Formatting Facility (MDFF) is presently dedicated to supporting these avionic display systems with the development of the Compressed Aeronautical Chart (CAC) database on Compact Disk Read Only Memory (CDROM) optical discs. The MDFF is also developing a series of aircraft-specific Write-Once Read Many (WORM) optical discs. NOARL has initiated a comprehensive research program aimed at improving the pilots'' moving map displays current research efforts include the development of an alternate image compression technique and generation of a standard set of color palettes. The CAC database will provide digital aeronautical chart data in six different scales. CAC is derived from the Defense Mapping Agency''s (DMA) Equal Arc-second (ARC) Digitized Raster Graphics (ADRG) a series of scanned aeronautical charts. NOARL processes ADRG to tailor the chart image resolution to that of the DMS display while reducing storage requirements through image compression techniques. CAC is being distributed by DMA as a library of CDROMs.

Progressive compressive imager

NASA Astrophysics Data System (ADS)

Evladov, Sergei; Levi, Ofer; Stern, Adrian

2012-06-01

We have designed and built a working automatic progressive sampling imaging system based on the vector sensor concept, which utilizes a unique sampling scheme of Radon projections. This sampling scheme makes it possible to progressively add information resulting in tradeoff between compression and the quality of reconstruction. The uniqueness of our sampling is that in any moment of the acquisition process the reconstruction can produce a reasonable version of the image. The advantage of the gradual addition of the samples is seen when the sparsity rate of the object is unknown, and thus the number of needed measurements. We have developed the iterative algorithm OSO (Ordered Sets Optimization) which employs our sampling scheme for creation of nearly uniform distributed sets of samples, which allows the reconstruction of Mega-Pixel images. We present the good quality reconstruction from compressed data ratios of 1:20.

Networking of three dimensional sonography volume data.

PubMed

Kratochwil, A; Lee, A; Schoisswohl, A

2000-09-01

Three-dimensioned (3D) sonography enables the examiner to store, instead of copies from single B-scan planes, a volume consisting of 300 scan planes. The volume is displayed on a monitor in form of three orthogonal planes--longitudinal, axial and coronal. Translation and rotation facilitates anatomical orientation and provides any arbitrary plane within the volume to generate organ optimized scan planes. Different algorithms allow the extraction of different information such as surface, or bone structures by maximum mode, or fluid filled structures, such as vessels by the minimum mode. The volume may contain as well color information of vessels. The digitized information is stored on a magnetic optical disc. This allows virtual scanning in absence of the patient under the same conditions as the volume was primarily stored. The volume size is dependent on different, examiner-controlled settings. A volume may need a storage capacity between 2 and 16 MB of 8-bit gray level information. As such huge data sets are unsuitable for network transfer, data compression is of paramount interest. 100 stored volumes were submitted to JPEG, MPEG, and biorthogonal wavelet compression. The original and compressed volumes were randomly shown on two monitors. In case of noticeable image degradation, information on the location of the original and compressed volume and the ratio of compression was read. Numerical values for proving compression fidelity as pixel error calculation and computation of square root error have been unsuitable for evaluating image degradation. The best results in recognizing image degradation were achieved by image experts. The experts disagreed on the ratio where image degradation became visible in only 4% of the volumes. Wavelet compression ratios of 20:1 or 30:1 could be performed without discernible information reduction. The effect of volume compression is reflected both in the reduction of transfer time and in storage capacity. Transmission time for a volume of 6 MB using a normal telephone with a data flow of 56 kB/s was reduced from 14 min to 28 s at a compression rate of 30:1. Compression reduced storage requirements from 6 MB uncompressed to 200 kB at a compression rate of 30:1. This successful compression opens new possibilities of intra- and extra-hospital and global information for 3D sonography. The key to this communication is not only volume compression, but also the fact that the 3D examination can be simulated on any PC by the developed 3D software. PACS teleradiology using digitized radiographs transmitted over standard telephone lines. Systems in combination with the management systems of HIS and RIS are available for archiving, retrieval of images and reports and for local and global communication. This form of tele-medicine will have an impact on cost reduction in hospitals, reduction of transport costs. On this fundament worldwide education and multi-center studies becomes possible.

Optimal Compression of Floating-Point Astronomical Images Without Significant Loss of Information

NASA Technical Reports Server (NTRS)

Pence, William D.; White, R. L.; Seaman, R.

2010-01-01

We describe a compression method for floating-point astronomical images that gives compression ratios of 6 - 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process greatly improves the precision of measurements in the more coarsely quantized images. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.

Compression for radiological images

NASA Astrophysics Data System (ADS)

Wilson, Dennis L.

1992-07-01

The viewing of radiological images has peculiarities that must be taken into account in the design of a compression technique. The images may be manipulated on a workstation to change the contrast, to change the center of the brightness levels that are viewed, and even to invert the images. Because of the possible consequences of losing information in a medical application, bit preserving compression is used for the images used for diagnosis. However, for archiving the images may be compressed to 10 of their original size. A compression technique based on the Discrete Cosine Transform (DCT) takes the viewing factors into account by compressing the changes in the local brightness levels. The compression technique is a variation of the CCITT JPEG compression that suppresses the blocking of the DCT except in areas of very high contrast.

Reversible Watermarking Surviving JPEG Compression.

PubMed

Zain, J; Clarke, M

2005-01-01

This paper will discuss the properties of watermarking medical images. We will also discuss the possibility of such images being compressed by JPEG and give an overview of JPEG compression. We will then propose a watermarking scheme that is reversible and robust to JPEG compression. The purpose is to verify the integrity and authenticity of medical images. We used 800x600x8 bits ultrasound (US) images in our experiment. SHA-256 of the image is then embedded in the Least significant bits (LSB) of an 8x8 block in the Region of Non Interest (RONI). The image is then compressed using JPEG and decompressed using Photoshop 6.0. If the image has not been altered, the watermark extracted will match the hash (SHA256) of the original image. The result shown that the embedded watermark is robust to JPEG compression up to image quality 60 (~91% compressed).

Magnetic resonance image compression using scalar-vector quantization

NASA Astrophysics Data System (ADS)

Mohsenian, Nader; Shahri, Homayoun

1995-12-01

A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

Mixed raster content (MRC) model for compound image compression

NASA Astrophysics Data System (ADS)

de Queiroz, Ricardo L.; Buckley, Robert R.; Xu, Ming

1998-12-01

This paper will describe the Mixed Raster Content (MRC) method for compressing compound images, containing both binary test and continuous-tone images. A single compression algorithm that simultaneously meets the requirements for both text and image compression has been elusive. MRC takes a different approach. Rather than using a single algorithm, MRC uses a multi-layered imaging model for representing the results of multiple compression algorithms, including ones developed specifically for text and for images. As a result, MRC can combine the best of existing or new compression algorithms and offer different quality-compression ratio tradeoffs. The algorithms used by MRC set the lower bound on its compression performance. Compared to existing algorithms, MRC has some image-processing overhead to manage multiple algorithms and the imaging model. This paper will develop the rationale for the MRC approach by describing the multi-layered imaging model in light of a rate-distortion trade-off. Results will be presented comparing images compressed using MRC, JPEG and state-of-the-art wavelet algorithms such as SPIHT. MRC has been approved or proposed as an architectural model for several standards, including ITU Color Fax, IETF Internet Fax, and JPEG 2000.

Comparative data compression techniques and multi-compression results

NASA Astrophysics Data System (ADS)

Hasan, M. R.; Ibrahimy, M. I.; Motakabber, S. M. A.; Ferdaus, M. M.; Khan, M. N. H.

2013-12-01

Data compression is very necessary in business data processing, because of the cost savings that it offers and the large volume of data manipulated in many business applications. It is a method or system for transmitting a digital image (i.e., an array of pixels) from a digital data source to a digital data receiver. More the size of the data be smaller, it provides better transmission speed and saves time. In this communication, we always want to transmit data efficiently and noise freely. This paper will provide some compression techniques for lossless text type data compression and comparative result of multiple and single compression, that will help to find out better compression output and to develop compression algorithms.

Technical Note: Validation of two methods to determine contact area between breast and compression paddle in mammography.

PubMed

Branderhorst, Woutjan; de Groot, Jerry E; van Lier, Monique G J T B; Highnam, Ralph P; den Heeten, Gerard J; Grimbergen, Cornelis A

2017-08-01

To assess the accuracy of two methods of determining the contact area between the compression paddle and the breast in mammography. An accurate method to determine the contact area is essential to accurately calculate the average compression pressure applied by the paddle. For a set of 300 breast compressions, we measured the contact areas between breast and paddle, both capacitively using a transparent foil with indium-tin-oxide (ITO) coating attached to the paddle, and retrospectively from the obtained mammograms using image processing software (Volpara Enterprise, algorithm version 1.5.2). A gold standard was obtained from video images of the compressed breast. During each compression, the breast was illuminated from the sides in order to create a dark shadow on the video image where the breast was in contact with the compression paddle. We manually segmented the shadows captured at the time of x-ray exposure and measured their areas. We found a strong correlation between the manual segmentations and the capacitive measurements [r = 0.989, 95% CI (0.987, 0.992)] and between the manual segmentations and the image processing software [r = 0.978, 95% CI (0.972, 0.982)]. Bland-Altman analysis showed a bias of -0.0038 dm 2 for the capacitive measurement (SD 0.0658, 95% limits of agreement [-0.1329, 0.1252]) and -0.0035 dm 2 for the image processing software [SD 0.0962, 95% limits of agreement (-0.1921, 0.1850)]. The size of the contact area between the paddle and the breast can be determined accurately and precisely, both in real-time using the capacitive method, and retrospectively using image processing software. This result is beneficial for scientific research, data analysis and quality control systems that depend on one of these two methods for determining the average pressure on the breast during mammographic compression. © 2017 Sigmascreening B.V. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

The Pixon Method for Data Compression Image Classification, and Image Reconstruction

NASA Technical Reports Server (NTRS)

Puetter, Richard; Yahil, Amos

2002-01-01

As initially proposed, this program had three goals: (1) continue to develop the highly successful Pixon method for image reconstruction and support other scientist in implementing this technique for their applications; (2) develop image compression techniques based on the Pixon method; and (3) develop artificial intelligence algorithms for image classification based on the Pixon approach for simplifying neural networks. Subsequent to proposal review the scope of the program was greatly reduced and it was decided to investigate the ability of the Pixon method to provide superior restorations of images compressed with standard image compression schemes, specifically JPEG-compressed images.

A new hyperspectral image compression paradigm based on fusion

NASA Astrophysics Data System (ADS)

Guerra, Raúl; Melián, José; López, Sebastián.; Sarmiento, Roberto

2016-10-01

The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.

Hardware Implementation of Lossless Adaptive Compression of Data From a Hyperspectral Imager

NASA Technical Reports Server (NTRS)

Keymeulen, Didlier; Aranki, Nazeeh I.; Klimesh, Matthew A.; Bakhshi, Alireza

2012-01-01

Efficient onboard data compression can reduce the data volume from hyperspectral imagers on NASA and DoD spacecraft in order to return as much imagery as possible through constrained downlink channels. Lossless compression is important for signature extraction, object recognition, and feature classification capabilities. To provide onboard data compression, a hardware implementation of a lossless hyperspectral compression algorithm was developed using a field programmable gate array (FPGA). The underlying algorithm is the Fast Lossless (FL) compression algorithm reported in Fast Lossless Compression of Multispectral- Image Data (NPO-42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), p. 26 with the modification reported in Lossless, Multi-Spectral Data Comressor for Improved Compression for Pushbroom-Type Instruments (NPO-45473), NASA Tech Briefs, Vol. 32, No. 7 (July 2008) p. 63, which provides improved compression performance for data from pushbroom-type imagers. An FPGA implementation of the unmodified FL algorithm was previously developed and reported in Fast and Adaptive Lossless Onboard Hyperspectral Data Compression System (NPO-46867), NASA Tech Briefs, Vol. 36, No. 5 (May 2012) p. 42. The essence of the FL algorithm is adaptive linear predictive compression using the sign algorithm for filter adaption. The FL compressor achieves a combination of low complexity and compression effectiveness that exceeds that of stateof- the-art techniques currently in use. The modification changes the predictor structure to tolerate differences in sensitivity of different detector elements, as occurs in pushbroom-type imagers, which are suitable for spacecraft use. The FPGA implementation offers a low-cost, flexible solution compared to traditional ASIC (application specific integrated circuit) and can be integrated as an intellectual property (IP) for part of, e.g., a design that manages the instrument interface. The FPGA implementation was benchmarked on the Xilinx Virtex IV LX25 device, and ported to a Xilinx prototype board. The current implementation has a critical path of 29.5 ns, which dictated a clock speed of 33 MHz. The critical path delay is end-to-end measurement between the uncompressed input data and the output compression data stream. The implementation compresses one sample every clock cycle, which results in a speed of 33 Msample/s. The implementation has a rather low device use of the Xilinx Virtex IV LX25, making the total power consumption of the implementation about 1.27 W.

Data Compression Techniques for Maps

DTIC Science & Technology

1989-01-01

Lempel - Ziv compression is applied to the classified and unclassified images as also to the output of the compression algorithms . The algorithms ...resulted in a compression of 7:1. The output of the quadtree coding algorithm was then compressed using Lempel - Ziv coding. The compression ratio achieved...using Lempel - Ziv coding. The unclassified image gave a compression ratio of only 1.4:1. The K means classified image

Fast Lossless Compression of Multispectral-Image Data

NASA Technical Reports Server (NTRS)

Klimesh, Matthew

2006-01-01

An algorithm that effects fast lossless compression of multispectral-image data is based on low-complexity, proven adaptive-filtering algorithms. This algorithm is intended for use in compressing multispectral-image data aboard spacecraft for transmission to Earth stations. Variants of this algorithm could be useful for lossless compression of three-dimensional medical imagery and, perhaps, for compressing image data in general.

Optimal Compression Methods for Floating-point Format Images

NASA Technical Reports Server (NTRS)

Pence, W. D.; White, R. L.; Seaman, R.

2009-01-01

We report on the results of a comparison study of different techniques for compressing FITS images that have floating-point (real*4) pixel values. Standard file compression methods like GZIP are generally ineffective in this case (with compression ratios only in the range 1.2 - 1.6), so instead we use a technique of converting the floating-point values into quantized scaled integers which are compressed using the Rice algorithm. The compressed data stream is stored in FITS format using the tiled-image compression convention. This is technically a lossy compression method, since the pixel values are not exactly reproduced, however all the significant photometric and astrometric information content of the image can be preserved while still achieving file compression ratios in the range of 4 to 8. We also show that introducing dithering, or randomization, when assigning the quantized pixel-values can significantly improve the photometric and astrometric precision in the stellar images in the compressed file without adding additional noise. We quantify our results by comparing the stellar magnitudes and positions as measured in the original uncompressed image to those derived from the same image after applying successively greater amounts of compression.

Lossless Compression of Stromatolite Images: A Biogenicity Index?

NASA Astrophysics Data System (ADS)

Corsetti, Frank A.; Storrie-Lombardi, Michael C.

2003-12-01

It has been underappreciated that inorganic processes can produce stromatolites (laminated macroscopic constructions commonly attributed to microbiological activity), thus calling into question the long-standing use of stromatolites as de facto evidence for ancient life. Using lossless compression on unmagnified reflectance red-green-blue (RGB) images of matched stromatolite-sediment matrix pairs as a complexity metric, the compressibility index (δc, the log of the ratio of the compressibility of the matrix versus the target) of a putative abiotic test stromatolite is significantly less than the δc of a putative biotic test stromatolite. There is a clear separation in δc between the different stromatolites discernible at the outcrop scale. In terms of absolute compressibility, the sediment matrix between the stromatolite columns was low in both cases, the putative abiotic stromatolite was similar to the intracolumnar sediment, and the putative biotic stromatolite was much greater (again discernible at the outcrop scale). We propose that this metric would be useful for evaluating the biogenicity of images obtained by the camera systems available on every Mars surface probe launched to date including Viking, Pathfinder, Beagle, and the two Mars Exploration Rovers.

Lossless compression of stromatolite images: a biogenicity index?

PubMed

Corsetti, Frank A; Storrie-Lombardi, Michael C

2003-01-01

It has been underappreciated that inorganic processes can produce stromatolites (laminated macroscopic constructions commonly attreibuted to microbiological activity), thus calling into question the long-standing use of stromatolites as de facto evidence for ancient life. Using lossless compression on unmagnified reflectance red-green-blue (RGB) images of matched stromatolite-sediment matrix pairs as a complexity metric, the compressibility index (delta(c), the log ratio of the ratio of the compressibility of the matrix versus the target) of a putative abiotic test stromatolite is significantly less than the delta(c) of a putative biotic test stromatolite. There is a clear separation in delta(c) between the different stromatolites discernible at the outcrop scale. In terms of absolute compressibility, the sediment matrix between the stromatolite columns was low in both cases, the putative abiotic stromatolite was similar to the intracolumnar sediment, and the putative biotic stromatolite was much greater (again discernible at the outcrop scale). We propose tht this metric would be useful for evaluating the biogenicity of images obtained by the camera systems available on every Mars surface probe launched to date including Viking, Pathfinder, Beagle, and the two Mars Exploration Rovers.

Fingerprint recognition of wavelet-based compressed images by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Liu, Ti C.; Mitra, Sunanda

1996-06-01

Image compression plays a crucial role in many important and diverse applications requiring efficient storage and transmission. This work mainly focuses on a wavelet transform (WT) based compression of fingerprint images and the subsequent classification of the reconstructed images. The algorithm developed involves multiresolution wavelet decomposition, uniform scalar quantization, entropy and run- length encoder/decoder and K-means clustering of the invariant moments as fingerprint features. The performance of the WT-based compression algorithm has been compared with JPEG current image compression standard. Simulation results show that WT outperforms JPEG in high compression ratio region and the reconstructed fingerprint image yields proper classification.

Artifacts in slab average-intensity-projection images reformatted from JPEG 2000 compressed thin-section abdominal CT data sets.

PubMed

Kim, Bohyoung; Lee, Kyoung Ho; Kim, Kil Joong; Mantiuk, Rafal; Kim, Hye-ri; Kim, Young Hoon

2008-06-01

The objective of our study was to assess the effects of compressing source thin-section abdominal CT images on final transverse average-intensity-projection (AIP) images. At reversible, 4:1, 6:1, 8:1, 10:1, and 15:1 Joint Photographic Experts Group (JPEG) 2000 compressions, we compared the artifacts in 20 matching compressed thin sections (0.67 mm), compressed thick sections (5 mm), and AIP images (5 mm) reformatted from the compressed thin sections. The artifacts were quantitatively measured with peak signal-to-noise ratio (PSNR) and a perceptual quality metric (High Dynamic Range Visual Difference Predictor [HDR-VDP]). By comparing the compressed and original images, three radiologists independently graded the artifacts as 0 (none, indistinguishable), 1 (barely perceptible), 2 (subtle), or 3 (significant). Friedman tests and exact tests for paired proportions were used. At irreversible compressions, the artifacts tended to increase in the order of AIP, thick-section, and thin-section images in terms of PSNR (p < 0.0001), HDR-VDP (p < 0.0001), and the readers' grading (p < 0.01 at 6:1 or higher compressions). At 6:1 and 8:1, distinguishable pairs (grades 1-3) tended to increase in the order of AIP, thick-section, and thin-section images. Visually lossless threshold for the compression varied between images but decreased in the order of AIP, thick-section, and thin-section images (p < 0.0001). Compression artifacts in thin sections are significantly attenuated in AIP images. On the premise that thin sections are typically reviewed using an AIP technique, it is justifiable to compress them to a compression level currently accepted for thick sections.

About a method for compressing x-ray computed microtomography data

NASA Astrophysics Data System (ADS)

Mancini, Lucia; Kourousias, George; Billè, Fulvio; De Carlo, Francesco; Fidler, Aleš

2018-04-01

The management of scientific data is of high importance especially for experimental techniques that produce big data volumes. Such a technique is x-ray computed tomography (CT) and its community has introduced advanced data formats which allow for better management of experimental data. Rather than the organization of the data and the associated meta-data, the main topic on this work is data compression and its applicability to experimental data collected from a synchrotron-based CT beamline at the Elettra-Sincrotrone Trieste facility (Italy) and studies images acquired from various types of samples. This study covers parallel beam geometry, but it could be easily extended to a cone-beam one. The reconstruction workflow used is the one currently in operation at the beamline. Contrary to standard image compression studies, this manuscript proposes a systematic framework and workflow for the critical examination of different compression techniques and does so by applying it to experimental data. Beyond the methodology framework, this study presents and examines the use of JPEG-XR in combination with HDF5 and TIFF formats providing insights and strategies on data compression and image quality issues that can be used and implemented at other synchrotron facilities and laboratory systems. In conclusion, projection data compression using JPEG-XR appears as a promising, efficient method to reduce data file size and thus to facilitate data handling and image reconstruction.

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

PubMed Central

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

2014-01-01

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. PMID:25171121

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

PubMed

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.

Channel coding and data compression system considerations for efficient communication of planetary imaging data

NASA Technical Reports Server (NTRS)

Rice, R. F.

1974-01-01

End-to-end system considerations involving channel coding and data compression are reported which could drastically improve the efficiency in communicating pictorial information from future planetary spacecraft. In addition to presenting new and potentially significant system considerations, this report attempts to fill a need for a comprehensive tutorial which makes much of this very subject accessible to readers whose disciplines lie outside of communication theory.

JPEG2000 still image coding quality.

PubMed

Chen, Tzong-Jer; Lin, Sheng-Chieh; Lin, You-Chen; Cheng, Ren-Gui; Lin, Li-Hui; Wu, Wei

2013-10-01

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics (r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression.

The compression and storage method of the same kind of medical images: DPCM

NASA Astrophysics Data System (ADS)

Zhao, Xiuying; Wei, Jingyuan; Zhai, Linpei; Liu, Hong

2006-09-01

Medical imaging has started to take advantage of digital technology, opening the way for advanced medical imaging and teleradiology. Medical images, however, require large amounts of memory. At over 1 million bytes per image, a typical hospital needs a staggering amount of memory storage (over one trillion bytes per year), and transmitting an image over a network (even the promised superhighway) could take minutes--too slow for interactive teleradiology. This calls for image compression to reduce significantly the amount of data needed to represent an image. Several compression techniques with different compression ratio have been developed. However, the lossless techniques, which allow for perfect reconstruction of the original images, yield modest compression ratio, while the techniques that yield higher compression ratio are lossy, that is, the original image is reconstructed only approximately. Medical imaging poses the great challenge of having compression algorithms that are lossless (for diagnostic and legal reasons) and yet have high compression ratio for reduced storage and transmission time. To meet this challenge, we are developing and studying some compression schemes, which are either strictly lossless or diagnostically lossless, taking advantage of the peculiarities of medical images and of the medical practice. In order to increase the Signal to Noise Ratio (SNR) by exploitation of correlations within the source signal, a method of combining differential pulse code modulation (DPCM) is presented.

Image-adapted visually weighted quantization matrices for digital image compression

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1994-01-01

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-05-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI`s Integrated Automated Fingerprint Identification System.

The FBI wavelet/scalar quantization standard for gray-scale fingerprint image compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.; Hopper, T.

1993-01-01

The FBI has recently adopted a standard for the compression of digitized 8-bit gray-scale fingerprint images. The standard is based on scalar quantization of a 64-subband discrete wavelet transform decomposition of the images, followed by Huffman coding. Novel features of the algorithm include the use of symmetric boundary conditions for transforming finite-length signals and a subband decomposition tailored for fingerprint images scanned at 500 dpi. The standard is intended for use in conjunction with ANSI/NBS-CLS 1-1993, American National Standard Data Format for the Interchange of Fingerprint Information, and the FBI's Integrated Automated Fingerprint Identification System.

Lossless compression of VLSI layout image data.

PubMed

Dai, Vito; Zakhor, Avideh

2006-09-01

We present a novel lossless compression algorithm called Context Copy Combinatorial Code (C4), which integrates the advantages of two very disparate compression techniques: context-based modeling and Lempel-Ziv (LZ) style copying. While the algorithm can be applied to many lossless compression applications, such as document image compression, our primary target application has been lossless compression of integrated circuit layout image data. These images contain a heterogeneous mix of data: dense repetitive data better suited to LZ-style coding, and less dense structured data, better suited to context-based encoding. As part of C4, we have developed a novel binary entropy coding technique called combinatorial coding which is simultaneously as efficient as arithmetic coding, and as fast as Huffman coding. Compression results show C4 outperforms JBIG, ZIP, BZIP2, and two-dimensional LZ, and achieves lossless compression ratios greater than 22 for binary layout image data, and greater than 14 for gray-pixel image data.

Unequal power allocation for JPEG transmission over MIMO systems.

PubMed

Sabir, Muhammad Farooq; Bovik, Alan Conrad; Heath, Robert W

2010-02-01

With the introduction of multiple transmit and receive antennas in next generation wireless systems, real-time image and video communication are expected to become quite common, since very high data rates will become available along with improved data reliability. New joint transmission and coding schemes that explore advantages of multiple antenna systems matched with source statistics are expected to be developed. Based on this idea, we present an unequal power allocation scheme for transmission of JPEG compressed images over multiple-input multiple-output systems employing spatial multiplexing. The JPEG-compressed image is divided into different quality layers, and different layers are transmitted simultaneously from different transmit antennas using unequal transmit power, with a constraint on the total transmit power during any symbol period. Results show that our unequal power allocation scheme provides significant image quality improvement as compared to different equal power allocations schemes, with the peak-signal-to-noise-ratio gain as high as 14 dB at low signal-to-noise-ratios.

Cloud solution for histopathological image analysis using region of interest based compression.

PubMed

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

Compression of regions in the global advanced very high resolution radiometer 1-km data set

NASA Technical Reports Server (NTRS)

Kess, Barbara L.; Steinwand, Daniel R.; Reichenbach, Stephen E.

1994-01-01

The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

A Novel Range Compression Algorithm for Resolution Enhancement in GNSS-SARs.

PubMed

Zheng, Yu; Yang, Yang; Chen, Wu

2017-06-25

In this paper, a novel range compression algorithm for enhancing range resolutions of a passive Global Navigation Satellite System-based Synthetic Aperture Radar (GNSS-SAR) is proposed. In the proposed algorithm, within each azimuth bin, firstly range compression is carried out by correlating a reflected GNSS intermediate frequency (IF) signal with a synchronized direct GNSS base-band signal in the range domain. Thereafter, spectrum equalization is applied to the compressed results for suppressing side lobes to obtain a final range-compressed signal. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR images can be achieved by the proposed range compression algorithm, compared to the conventional range compression algorithm.

Study of on-board compression of earth resources data

NASA Technical Reports Server (NTRS)

Habibi, A.

1975-01-01

The current literature on image bandwidth compression was surveyed and those methods relevant to compression of multispectral imagery were selected. Typical satellite multispectral data was then analyzed statistically and the results used to select a smaller set of candidate bandwidth compression techniques particularly relevant to earth resources data. These were compared using both theoretical analysis and simulation, under various criteria of optimality such as mean square error (MSE), signal-to-noise ratio, classification accuracy, and computational complexity. By concatenating some of the most promising techniques, three multispectral data compression systems were synthesized which appear well suited to current and future NASA earth resources applications. The performance of these three recommended systems was then examined in detail by all of the above criteria. Finally, merits and deficiencies were summarized and a number of recommendations for future NASA activities in data compression proposed.

A new efficient method for color image compression based on visual attention mechanism

NASA Astrophysics Data System (ADS)

Shao, Xiaoguang; Gao, Kun; Lv, Lily; Ni, Guoqiang

2010-11-01

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

Space and Earth Science Data Compression Workshop

NASA Technical Reports Server (NTRS)

Tilton, James C. (Editor)

1991-01-01

The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The focus was on scientists' data requirements, as well as constraints imposed by the data collection, transmission, distribution, and archival systems. The workshop consisted of several invited papers; two described information systems for space and Earth science data, four depicted analysis scenarios for extracting information of scientific interest from data collected by Earth orbiting and deep space platforms, and a final one was a general tutorial on image data compression.

Data compression experiments with LANDSAT thematic mapper and Nimbus-7 coastal zone color scanner data

NASA Technical Reports Server (NTRS)

Tilton, James C.; Ramapriyan, H. K.

1989-01-01

A case study is presented where an image segmentation based compression technique is applied to LANDSAT Thematic Mapper (TM) and Nimbus-7 Coastal Zone Color Scanner (CZCS) data. The compression technique, called Spatially Constrained Clustering (SCC), can be regarded as an adaptive vector quantization approach. The SCC can be applied to either single or multiple spectral bands of image data. The segmented image resulting from SCC is encoded in small rectangular blocks, with the codebook varying from block to block. Lossless compression potential (LDP) of sample TM and CZCS images are evaluated. For the TM test image, the LCP is 2.79. For the CZCS test image the LCP is 1.89, even though when only a cloud-free section of the image is considered the LCP increases to 3.48. Examples of compressed images are shown at several compression ratios ranging from 4 to 15. In the case of TM data, the compressed data are classified using the Bayes' classifier. The results show an improvement in the similarity between the classification results and ground truth when compressed data are used, thus showing that compression is, in fact, a useful first step in the analysis.

Comparison of two SVD-based color image compression schemes.

PubMed

Li, Ying; Wei, Musheng; Zhang, Fengxia; Zhao, Jianli

2017-01-01

Color image compression is a commonly used process to represent image data as few bits as possible, which removes redundancy in the data while maintaining an appropriate level of quality for the user. Color image compression algorithms based on quaternion are very common in recent years. In this paper, we propose a color image compression scheme, based on the real SVD, named real compression scheme. First, we form a new real rectangular matrix C according to the red, green and blue components of the original color image and perform the real SVD for C. Then we select several largest singular values and the corresponding vectors in the left and right unitary matrices to compress the color image. We compare the real compression scheme with quaternion compression scheme by performing quaternion SVD using the real structure-preserving algorithm. We compare the two schemes in terms of operation amount, assignment number, operation speed, PSNR and CR. The experimental results show that with the same numbers of selected singular values, the real compression scheme offers higher CR, much less operation time, but a little bit smaller PSNR than the quaternion compression scheme. When these two schemes have the same CR, the real compression scheme shows more prominent advantages both on the operation time and PSNR.

Comparison of two SVD-based color image compression schemes

PubMed Central

Li, Ying; Wei, Musheng; Zhang, Fengxia; Zhao, Jianli

2017-01-01

Color image compression is a commonly used process to represent image data as few bits as possible, which removes redundancy in the data while maintaining an appropriate level of quality for the user. Color image compression algorithms based on quaternion are very common in recent years. In this paper, we propose a color image compression scheme, based on the real SVD, named real compression scheme. First, we form a new real rectangular matrix C according to the red, green and blue components of the original color image and perform the real SVD for C. Then we select several largest singular values and the corresponding vectors in the left and right unitary matrices to compress the color image. We compare the real compression scheme with quaternion compression scheme by performing quaternion SVD using the real structure-preserving algorithm. We compare the two schemes in terms of operation amount, assignment number, operation speed, PSNR and CR. The experimental results show that with the same numbers of selected singular values, the real compression scheme offers higher CR, much less operation time, but a little bit smaller PSNR than the quaternion compression scheme. When these two schemes have the same CR, the real compression scheme shows more prominent advantages both on the operation time and PSNR. PMID:28257451

Compression of the Global Land 1-km AVHRR dataset

USGS Publications Warehouse

Kess, B. L.; Steinwand, D.R.; Reichenbach, S.E.

1996-01-01

Large datasets, such as the Global Land 1-km Advanced Very High Resolution Radiometer (AVHRR) Data Set (Eidenshink and Faundeen 1994), require compression methods that provide efficient storage and quick access to portions of the data. A method of lossless compression is described that provides multiresolution decompression within geographic subwindows of multi-spectral, global, 1-km, AVHRR images. The compression algorithm segments each image into blocks and compresses each block in a hierarchical format. Users can access the data by specifying either a geographic subwindow or the whole image and a resolution (1,2,4, 8, or 16 km). The Global Land 1-km AVHRR data are presented in the Interrupted Goode's Homolosine map projection. These images contain masked regions for non-land areas which comprise 80 per cent of the image. A quadtree algorithm is used to compress the masked regions. The compressed region data are stored separately from the compressed land data. Results show that the masked regions compress to 0·143 per cent of the bytes they occupy in the test image and the land areas are compressed to 33·2 per cent of their original size. The entire image is compressed hierarchically to 6·72 per cent of the original image size, reducing the data from 9·05 gigabytes to 623 megabytes. These results are compared to the first order entropy of the residual image produced with lossless Joint Photographic Experts Group predictors. Compression results are also given for Lempel-Ziv-Welch (LZW) and LZ77, the algorithms used by UNIX compress and GZIP respectively. In addition to providing multiresolution decompression of geographic subwindows of the data, the hierarchical approach and the use of quadtrees for storing the masked regions gives a marked improvement over these popular methods.

Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors.

PubMed

Yorke, Ellen; Xiong, Ying; Han, Qian; Zhang, Pengpeng; Mageras, Gikas; Lovelock, Michael; Pham, Hai; Xiong, Jian-Ping; Goodman, Karyn A

2016-07-01

To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiation therapy (SBRT). A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during SBRT for abdominal tumors. Kilovoltage images were acquired at 5- to 6-second intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for 3 sessions for each patient. Intrafraction displacement patterns varied between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm, and 1.2% exceeded 0.75 cm. The calculated single-session dose to 95% of gross tumor volume differed from planned by an average of -1.2% (range, -11.1% to 4.8%) but only for 4 patients was the total 3-session calculated dose to 95% of gross tumor volume more than 3% different from planned. Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable. Copyright © 2015 Elsevier Inc. All rights reserved.

Kilovoltage imaging of implanted fiducials to monitor intrafraction motion with abdominal compression during stereotactic body radiotherapy for GI tumors

PubMed Central

Yorke, Ellen; Xiong, Ying; Han, Qian; Zhang, Pengpeng; Mageras, Gikas; Lovelock, Michael; Pham, Hai; Xiong, Jian-Ping; Goodman, Karyn A.

2017-01-01

Purpose/Objective To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiotherapy (sbrt). Methods and Materials A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during sbrt for abdominal tumors. Kilovoltage images were acquired at 5–6 sec intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for three sessions for each patient. Results Intrafraction displacement patterns varied between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm and 1.2% exceeded 0.75 cm. The calculated single session dose to 95% of gross tumor volume (GTVD95) differed from planned by an average of −1.2% (−11.1%−4.8%) but only for 4 patients was total 3-session calculated GTVD95 over 3% different from planned Conclusions Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable. PMID:26797539

Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-03-01

A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

Image data compression having minimum perceptual error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1995-01-01

A method for performing image compression that eliminates redundant and invisible image components is described. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

High efficient optical remote sensing images acquisition for nano-satellite-framework

NASA Astrophysics Data System (ADS)

Li, Feng; Xin, Lei; Liu, Yang; Fu, Jie; Liu, Yuhong; Guo, Yi

2017-09-01

It is more difficult and challenging to implement Nano-satellite (NanoSat) based optical Earth observation missions than conventional satellites because of the limitation of volume, weight and power consumption. In general, an image compression unit is a necessary onboard module to save data transmission bandwidth and disk space. The image compression unit can get rid of redundant information of those captured images. In this paper, a new image acquisition framework is proposed for NanoSat based optical Earth observation applications. The entire process of image acquisition and compression unit can be integrated in the photo detector array chip, that is, the output data of the chip is already compressed. That is to say, extra image compression unit is no longer needed; therefore, the power, volume, and weight of the common onboard image compression units consumed can be largely saved. The advantages of the proposed framework are: the image acquisition and image compression are combined into a single step; it can be easily built in CMOS architecture; quick view can be provided without reconstruction in the framework; Given a certain compression ratio, the reconstructed image quality is much better than those CS based methods. The framework holds promise to be widely used in the future.

Estimating JPEG2000 compression for image forensics using Benford's Law

NASA Astrophysics Data System (ADS)

Qadir, Ghulam; Zhao, Xi; Ho, Anthony T. S.

2010-05-01

With the tremendous growth and usage of digital images nowadays, the integrity and authenticity of digital content is becoming increasingly important, and a growing concern to many government and commercial sectors. Image Forensics, based on a passive statistical analysis of the image data only, is an alternative approach to the active embedding of data associated with Digital Watermarking. Benford's Law was first introduced to analyse the probability distribution of the 1st digit (1-9) numbers of natural data, and has since been applied to Accounting Forensics for detecting fraudulent income tax returns [9]. More recently, Benford's Law has been further applied to image processing and image forensics. For example, Fu et al. [5] proposed a Generalised Benford's Law technique for estimating the Quality Factor (QF) of JPEG compressed images. In our previous work, we proposed a framework incorporating the Generalised Benford's Law to accurately detect unknown JPEG compression rates of watermarked images in semi-fragile watermarking schemes. JPEG2000 (a relatively new image compression standard) offers higher compression rates and better image quality as compared to JPEG compression. In this paper, we propose the novel use of Benford's Law for estimating JPEG2000 compression for image forensics applications. By analysing the DWT coefficients and JPEG2000 compression on 1338 test images, the initial results indicate that the 1st digit probability of DWT coefficients follow the Benford's Law. The unknown JPEG2000 compression rates of the image can also be derived, and proved with the help of a divergence factor, which shows the deviation between the probabilities and Benford's Law. Based on 1338 test images, the mean divergence for DWT coefficients is approximately 0.0016, which is lower than DCT coefficients at 0.0034. However, the mean divergence for JPEG2000 images compression rate at 0.1 is 0.0108, which is much higher than uncompressed DWT coefficients. This result clearly indicates a presence of compression in the image. Moreover, we compare the results of 1st digit probability and divergence among JPEG2000 compression rates at 0.1, 0.3, 0.5 and 0.9. The initial results show that the expected difference among them could be used for further analysis to estimate the unknown JPEG2000 compression rates.

Low-latency situational awareness for UxV platforms

NASA Astrophysics Data System (ADS)

Berends, David C.

2012-06-01

Providing high quality, low latency video from unmanned vehicles through bandwidth-limited communications channels remains a formidable challenge for modern vision system designers. SRI has developed a number of enabling technologies to address this, including the use of SWaP-optimized Systems-on-a-Chip which provide Multispectral Fusion and Contrast Enhancement as well as H.264 video compression. Further, the use of salience-based image prefiltering prior to image compression greatly reduces output video bandwidth by selectively blurring non-important scene regions. Combined with our customization of the VLC open source video viewer for low latency video decoding, SRI developed a prototype high performance, high quality vision system for UxV application in support of very demanding system latency requirements and user CONOPS.

An interactive toolbox for atlas-based segmentation and coding of volumetric images

NASA Astrophysics Data System (ADS)

Menegaz, G.; Luti, S.; Duay, V.; Thiran, J.-Ph.

2007-03-01

Medical imaging poses the great challenge of having compression algorithms that are lossless for diagnostic and legal reasons and yet provide high compression rates for reduced storage and transmission time. The images usually consist of a region of interest representing the part of the body under investigation surrounded by a "background", which is often noisy and not of diagnostic interest. In this paper, we propose a ROI-based 3D coding system integrating both the segmentation and the compression tools. The ROI is extracted by an atlas based 3D segmentation method combining active contours with information theoretic principles, and the resulting segmentation map is exploited for ROI based coding. The system is equipped with a GUI allowing the medical doctors to supervise the segmentation process and eventually reshape the detected contours at any point. The process is initiated by the user through the selection of either one pre-de.ned reference image or one image of the volume to be used as the 2D "atlas". The object contour is successively propagated from one frame to the next where it is used as the initial border estimation. In this way, the entire volume is segmented based on a unique 2D atlas. The resulting 3D segmentation map is exploited for adaptive coding of the different image regions. Two coding systems were considered: the JPEG3D standard and the 3D-SPITH. The evaluation of the performance with respect to both segmentation and coding proved the high potential of the proposed system in providing an integrated, low-cost and computationally effective solution for CAD and PAC systems.

[Development of a video image system for wireless capsule endoscopes based on DSP].

PubMed

Yang, Li; Peng, Chenglin; Wu, Huafeng; Zhao, Dechun; Zhang, Jinhua

2008-02-01

A video image recorder to record video picture for wireless capsule endoscopes was designed. TMS320C6211 DSP of Texas Instruments Inc. is the core processor of this system. Images are periodically acquired from Composite Video Broadcast Signal (CVBS) source and scaled by video decoder (SAA7114H). Video data is transported from high speed buffer First-in First-out (FIFO) to Digital Signal Processor (DSP) under the control of Complex Programmable Logic Device (CPLD). This paper adopts JPEG algorithm for image coding, and the compressed data in DSP was stored to Compact Flash (CF) card. TMS320C6211 DSP is mainly used for image compression and data transporting. Fast Discrete Cosine Transform (DCT) algorithm and fast coefficient quantization algorithm are used to accelerate operation speed of DSP and decrease the executing code. At the same time, proper address is assigned for each memory, which has different speed;the memory structure is also optimized. In addition, this system uses plenty of Extended Direct Memory Access (EDMA) to transport and process image data, which results in stable and high performance.

A Standard Mammography Unit - Standard 3D Ultrasound Probe Fusion Prototype: First Results.

PubMed

Schulz-Wendtland, Rüdiger; Jud, Sebastian M; Fasching, Peter A; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W; Emons, Julius

2017-06-01

The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound - the second important imaging modality in complementary breast diagnostics - without increasing examination time or requiring additional staff.

PubMed Central

Schulz-Wendtland, Rüdiger; Jud, Sebastian M.; Fasching, Peter A.; Hartmann, Arndt; Radicke, Marcus; Rauh, Claudia; Uder, Michael; Wunderle, Marius; Gass, Paul; Langemann, Hanna; Beckmann, Matthias W.; Emons, Julius

2017-01-01

Aim The combination of different imaging modalities through the use of fusion devices promises significant diagnostic improvement for breast pathology. The aim of this study was to evaluate image quality and clinical feasibility of a prototype fusion device (fusion prototype) constructed from a standard tomosynthesis mammography unit and a standard 3D ultrasound probe using a new method of breast compression. Materials and Methods Imaging was performed on 5 mastectomy specimens from patients with confirmed DCIS or invasive carcinoma (BI-RADS ™ 6). For the preclinical fusion prototype an ABVS system ultrasound probe from an Acuson S2000 was integrated into a MAMMOMAT Inspiration (both Siemens Healthcare Ltd) and, with the aid of a newly developed compression plate, digital mammogram and automated 3D ultrasound images were obtained. Results The quality of digital mammogram images produced by the fusion prototype was comparable to those produced using conventional compression. The newly developed compression plate did not influence the applied x-ray dose. The method was not more labour intensive or time-consuming than conventional mammography. From the technical perspective, fusion of the two modalities was achievable. Conclusion In this study, using only a few mastectomy specimens, the fusion of an automated 3D ultrasound machine with a standard mammography unit delivered images of comparable quality to conventional mammography. The device allows simultaneous ultrasound – the second important imaging modality in complementary breast diagnostics – without increasing examination time or requiring additional staff. PMID:28713173

Measurement of compressed breast thickness by optical stereoscopic photogrammetry.

PubMed

Tyson, Albert H; Mawdsley, Gordon E; Yaffe, Martin J

2009-02-01

The determination of volumetric breast density (VBD) from mammograms requires accurate knowledge of the thickness of the compressed breast. In attempting to accurately determine VBD from images obtained on conventional mammography systems, the authors found that the thickness reported by a number of mammography systems in the field varied by as much as 15 mm when compressing the same breast or phantom. In order to evaluate the behavior of mammographic compression systems and to be able to predict the thickness at different locations in the breast on patients, they have developed a method for measuring the local thickness of the breast at all points of contact with the compression paddle using optical stereoscopic photogrammetry. On both flat (solid) and compressible phantoms, the measurements were accurate to better than 1 mm with a precision of 0.2 mm. In a pilot study, this method was used to measure thickness on 108 volunteers who were undergoing mammography examination. This measurement tool will allow us to characterize paddle surface deformations, deflections and calibration offsets for mammographic units.

Implementation of a thesaurus in an electronic photograph imaging system

NASA Astrophysics Data System (ADS)

Partlow, Denise

1995-11-01

A photograph imaging system presents a unique set of requirements for indexing and retrieving images, unlike a standard imaging system for written documents. This paper presents the requirements, technical design, and development results for a hierarchical ANSI standard thesaurus embedded into a photograph archival system. The thesaurus design incorporates storage reduction techniques, permits fast searches, and contains flexible indexing methods. It can be extended to many applications other than the retrieval of photographs. When photographic images are indexed into an electronic system, they are subject to a variety of indexing problems based on what the indexer `sees.' For instance, the indexer may categorize an image as a boat when others might refer to it as a ship, sailboat, or raft. The thesaurus will allow a user to locate images containing any synonym for boat, regardless of how the image was actually indexed. In addition to indexing problems, photos may need to be retrieved based on a broad category, for instance, flowers. The thesaurus allows a search for `flowers' to locate all images containing a rose, hibiscus, or daisy, yet still allow a specific search for an image containing only a rose. The technical design and method of implementation for such a thesaurus is presented. The thesaurus is implemented using an SQL relational data base management system that supports blobs, binary large objects. The design incorporates unique compression methods for storing the thesaurus words. Words are indexed to photographs using the compressed word and allow for very rapid searches, eliminating lengthy string matches.

Learning random networks for compression of still and moving images

NASA Technical Reports Server (NTRS)

Gelenbe, Erol; Sungur, Mert; Cramer, Christopher

1994-01-01

Image compression for both still and moving images is an extremely important area of investigation, with numerous applications to videoconferencing, interactive education, home entertainment, and potential applications to earth observations, medical imaging, digital libraries, and many other areas. We describe work on a neural network methodology to compress/decompress still and moving images. We use the 'point-process' type neural network model which is closer to biophysical reality than standard models, and yet is mathematically much more tractable. We currently achieve compression ratios of the order of 120:1 for moving grey-level images, based on a combination of motion detection and compression. The observed signal-to-noise ratio varies from values above 25 to more than 35. The method is computationally fast so that compression and decompression can be carried out in real-time. It uses the adaptive capabilities of a set of neural networks so as to select varying compression ratios in real-time as a function of quality achieved. It also uses a motion detector which will avoid retransmitting portions of the image which have varied little from the previous frame. Further improvements can be achieved by using on-line learning during compression, and by appropriate compensation of nonlinearities in the compression/decompression scheme. We expect to go well beyond the 250:1 compression level for color images with good quality levels.

Web-based document and content management with off-the-shelf software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuster, J

1999-03-18

This, then, is the current status of the project: Since we made the switch to Intradoc, we are now treating the project as a document and image management system. In reality, it could be considered a document and content management system since we can manage almost any file input to the system such as video or audio. At present, however, we are concentrating on images. As mentioned above, my CRADA funding was only targeted at including thumbnails of images in Intradoc. We still had to modify Intradoc so that it would compress images submitted to the system. All processing ofmore » files submitted to Intradoc is handled in what is called the Document Refinery. Even though MrSID created thumbnails in the process of compressing an image, work needed to be done to somehow build this capability into the Document Refinery. Therefore we made the decision to contract the Intradoc Engineering Team to perform this custom development work. To make Intradoc even more capable of handling images, we have also contracted for customization of the Document Refinery to accept Adobe PhotoShop and Illustrator file in their native format.« less

An image assessment study of image acceptability of the Galileo low gain antenna mission

NASA Technical Reports Server (NTRS)

Chuang, S. L.; Haines, R. F.; Grant, T.; Gold, Yaron; Cheung, Kar-Ming

1994-01-01

This paper describes a study conducted by NASA Ames Research Center (ARC) in collaboration with the Jet Propulsion Laboratory (JPL), Pasadena, California on the image acceptability of the Galileo Low Gain Antenna mission. The primary objective of the study is to determine the impact of the Integer Cosine Transform (ICT) compression algorithm on Galilean images of atmospheric bodies, moons, asteroids and Jupiter's rings. The approach involved fifteen volunteer subjects representing twelve institutions involved with the Galileo Solid State Imaging (SSI) experiment. Four different experiment specific quantization tables (q-table) and various compression stepsizes (q-factor) to achieve different compression ratios were used. It then determined the acceptability of the compressed monochromatic astronomical images as evaluated by Galileo SSI mission scientists. Fourteen different images were evaluated. Each observer viewed two versions of the same image side by side on a high resolution monitor, each was compressed using a different quantization stepsize. They were requested to select which image had the highest overall quality to support them in carrying out their visual evaluations of image content. Then they rated both images using a scale from one to five on its judged degree of usefulness. Up to four pre-selected types of images were presented with and without noise to each subject based upon results of a previously administered survey of their image preferences. Fourteen different images in seven image groups were studied. The results showed that: (1) acceptable compression ratios vary widely with the type of images; (2) noisy images detract greatly from image acceptability and acceptable compression ratios; and (3) atmospheric images of Jupiter seem to have higher compression ratios of 4 to 5 times that of some clear surface satellite images.

Compressed/reconstructed test images for CRAF/Cassini

NASA Technical Reports Server (NTRS)

Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.

1991-01-01

A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.

High-performance compression of astronomical images

NASA Technical Reports Server (NTRS)

White, Richard L.

1993-01-01

Astronomical images have some rather unusual characteristics that make many existing image compression techniques either ineffective or inapplicable. A typical image consists of a nearly flat background sprinkled with point sources and occasional extended sources. The images are often noisy, so that lossless compression does not work very well; furthermore, the images are usually subjected to stringent quantitative analysis, so any lossy compression method must be proven not to discard useful information, but must instead discard only the noise. Finally, the images can be extremely large. For example, the Space Telescope Science Institute has digitized photographic plates covering the entire sky, generating 1500 images each having 14000 x 14000 16-bit pixels. Several astronomical groups are now constructing cameras with mosaics of large CCD's (each 2048 x 2048 or larger); these instruments will be used in projects that generate data at a rate exceeding 100 MBytes every 5 minutes for many years. An effective technique for image compression may be based on the H-transform (Fritze et al. 1977). The method that we have developed can be used for either lossless or lossy compression. The digitized sky survey images can be compressed by at least a factor of 10 with no noticeable losses in the astrometric and photometric properties of the compressed images. The method has been designed to be computationally efficient: compression or decompression of a 512 x 512 image requires only 4 seconds on a Sun SPARCstation 1. The algorithm uses only integer arithmetic, so it is completely reversible in its lossless mode, and it could easily be implemented in hardware for space applications.

Halftoning processing on a JPEG-compressed image

NASA Astrophysics Data System (ADS)

Sibade, Cedric; Barizien, Stephane; Akil, Mohamed; Perroton, Laurent

2003-12-01

Digital image processing algorithms are usually designed for the raw format, that is on an uncompressed representation of the image. Therefore prior to transforming or processing a compressed format, decompression is applied; then, the result of the processing application is finally re-compressed for further transfer or storage. The change of data representation is resource-consuming in terms of computation, time and memory usage. In the wide format printing industry, this problem becomes an important issue: e.g. a 1 m2 input color image, scanned at 600 dpi exceeds 1.6 GB in its raw representation. However, some image processing algorithms can be performed in the compressed-domain, by applying an equivalent operation on the compressed format. This paper is presenting an innovative application of the halftoning processing operation by screening, to be applied on JPEG-compressed image. This compressed-domain transform is performed by computing the threshold operation of the screening algorithm in the DCT domain. This algorithm is illustrated by examples for different halftone masks. A pre-sharpening operation, applied on a JPEG-compressed low quality image is also described; it allows to de-noise and to enhance the contours of this image.

A Novel Range Compression Algorithm for Resolution Enhancement in GNSS-SARs

PubMed Central

Zheng, Yu; Yang, Yang; Chen, Wu

2017-01-01

In this paper, a novel range compression algorithm for enhancing range resolutions of a passive Global Navigation Satellite System-based Synthetic Aperture Radar (GNSS-SAR) is proposed. In the proposed algorithm, within each azimuth bin, firstly range compression is carried out by correlating a reflected GNSS intermediate frequency (IF) signal with a synchronized direct GNSS base-band signal in the range domain. Thereafter, spectrum equalization is applied to the compressed results for suppressing side lobes to obtain a final range-compressed signal. Both theoretical analysis and simulation results have demonstrated that significant range resolution improvement in GNSS-SAR images can be achieved by the proposed range compression algorithm, compared to the conventional range compression algorithm. PMID:28672830

The effect of lossy image compression on image classification

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.

Reevaluation of JPEG image compression to digitalized gastrointestinal endoscopic color images: a pilot study

NASA Astrophysics Data System (ADS)

Kim, Christopher Y.

1999-05-01

Endoscopic images p lay an important role in describing many gastrointestinal (GI) disorders. The field of radiology has been on the leading edge of creating, archiving and transmitting digital images. With the advent of digital videoendoscopy, endoscopists now have the ability to generate images for storage and transmission. X-rays can be compressed 30-40X without appreciable decline in quality. We reported results of a pilot study using JPEG compression of 24-bit color endoscopic images. For that study, the result indicated that adequate compression ratios vary according to the lesion and that images could be compressed to between 31- and 99-fold smaller than the original size without an appreciable decline in quality. The purpose of this study was to expand upon the methodology of the previous sty with an eye towards application for the WWW, a medium which would expand both clinical and educational purposes of color medical imags. The results indicate that endoscopists are able to tolerate very significant compression of endoscopic images without loss of clinical image quality. This finding suggests that even 1 MB color images can be compressed to well under 30KB, which is considered a maximal tolerable image size for downloading on the WWW.

42 CFR 37.44 - Approval of radiographic facilities that use digital radiography systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... image acquisition, digitization, processing, compression, transmission, display, archiving, and... quality digital chest radiographs by submitting to NIOSH digital radiographic image files of a test object... digital radiographic image files from six or more sample chest radiographs that are of acceptable quality...

42 CFR 37.44 - Approval of radiographic facilities that use digital radiography systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... image acquisition, digitization, processing, compression, transmission, display, archiving, and... quality digital chest radiographs by submitting to NIOSH digital radiographic image files of a test object... digital radiographic image files from six or more sample chest radiographs that are of acceptable quality...

Image Segmentation, Registration, Compression, and Matching

NASA Technical Reports Server (NTRS)

Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

2011-01-01

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Cyclops: single-pixel imaging lidar system based on compressive sensing

NASA Astrophysics Data System (ADS)

Magalhães, F.; Correia, M. V.; Farahi, F.; Pereira do Carmo, J.; Araújo, F. M.

2017-11-01

Mars and the Moon are envisaged as major destinations of future space exploration missions in the upcoming decades. Imaging LIDARs are seen as a key enabling technology in the support of autonomous guidance, navigation and control operations, as they can provide very accurate, wide range, high-resolution distance measurements as required for the exploration missions. Imaging LIDARs can be used at critical stages of these exploration missions, such as descent and selection of safe landing sites, rendezvous and docking manoeuvres, or robotic surface navigation and exploration. Despite these devices have been commercially available and used for long in diverse metrology and ranging applications, their size, mass and power consumption are still far from being suitable and attractive for space exploratory missions. Here, we describe a compact Single-Pixel Imaging LIDAR System that is based on a compressive sensing technique. The application of the compressive codes to a DMD array enables compression of the spatial information, while the collection of timing histograms correlated to the pulsed laser source ensures image reconstruction at the ranged distances. Single-pixel cameras have been compared with raster scanning and array based counterparts in terms of noise performance, and proved to be superior. Since a single photodetector is used, a better SNR and higher reliability is expected in contrast with systems using large format photodetector arrays. Furthermore, the event of failure of one or more micromirror elements in the DMD does not prevent full reconstruction of the images. This brings additional robustness to the proposed 3D imaging LIDAR. The prototype that was implemented has three modes of operation. Range Finder: outputs the average distance between the system and the area of the target under illumination; Attitude Meter: provides the slope of the target surface based on distance measurements in three areas of the target; 3D Imager: produces 3D ranged images of the target surface. The implemented prototype demonstrated a frame rate of 30 mHz for 16x16 pixels images, a transversal (xy) resolution of 2 cm at 10 m for images with 64x64 pixels and the range (z) resolution proved to be better than 1 cm. The experimental results obtained for the "3D imaging" mode of operation demonstrated that it was possible to reconstruct spherical smooth surfaces. The proposed solution demonstrates a great potential for: miniaturization; increase spatial resolution without using large format detector arrays; eliminate the need for scanning mechanisms; implementing simple and robust configurations.

EBLAST: an efficient high-compression image transformation 3. application to Internet image and video transmission

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.; Caimi, Frank M.

2001-12-01

A wide variety of digital image compression transforms developed for still imaging and broadcast video transmission are unsuitable for Internet video applications due to insufficient compression ratio, poor reconstruction fidelity, or excessive computational requirements. Examples include hierarchical transforms that require all, or large portion of, a source image to reside in memory at one time, transforms that induce significant locking effect at operationally salient compression ratios, and algorithms that require large amounts of floating-point computation. The latter constraint holds especially for video compression by small mobile imaging devices for transmission to, and compression on, platforms such as palmtop computers or personal digital assistants (PDAs). As Internet video requirements for frame rate and resolution increase to produce more detailed, less discontinuous motion sequences, a new class of compression transforms will be needed, especially for small memory models and displays such as those found on PDAs. In this, the third series of papers, we discuss the EBLAST compression transform and its application to Internet communication. Leading transforms for compression of Internet video and still imagery are reviewed and analyzed, including GIF, JPEG, AWIC (wavelet-based), wavelet packets, and SPIHT, whose performance is compared with EBLAST. Performance analysis criteria include time and space complexity and quality of the decompressed image. The latter is determined by rate-distortion data obtained from a database of realistic test images. Discussion also includes issues such as robustness of the compressed format to channel noise. EBLAST has been shown to perform superiorly to JPEG and, unlike current wavelet compression transforms, supports fast implementation on embedded processors with small memory models.

Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2016-12-01

To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

SEMG signal compression based on two-dimensional techniques.

PubMed

de Melo, Wheidima Carneiro; de Lima Filho, Eddie Batista; da Silva Júnior, Waldir Sabino

2016-04-18

Recently, two-dimensional techniques have been successfully employed for compressing surface electromyographic (SEMG) records as images, through the use of image and video encoders. Such schemes usually provide specific compressors, which are tuned for SEMG data, or employ preprocessing techniques, before the two-dimensional encoding procedure, in order to provide a suitable data organization, whose correlations can be better exploited by off-the-shelf encoders. Besides preprocessing input matrices, one may also depart from those approaches and employ an adaptive framework, which is able to directly tackle SEMG signals reassembled as images. This paper proposes a new two-dimensional approach for SEMG signal compression, which is based on a recurrent pattern matching algorithm called multidimensional multiscale parser (MMP). The mentioned encoder was modified, in order to efficiently work with SEMG signals and exploit their inherent redundancies. Moreover, a new preprocessing technique, named as segmentation by similarity (SbS), which has the potential to enhance the exploitation of intra- and intersegment correlations, is introduced, the percentage difference sorting (PDS) algorithm is employed, with different image compressors, and results with the high efficiency video coding (HEVC), H.264/AVC, and JPEG2000 encoders are presented. Experiments were carried out with real isometric and dynamic records, acquired in laboratory. Dynamic signals compressed with H.264/AVC and HEVC, when combined with preprocessing techniques, resulted in good percent root-mean-square difference [Formula: see text] compression factor figures, for low and high compression factors, respectively. Besides, regarding isometric signals, the modified two-dimensional MMP algorithm outperformed state-of-the-art schemes, for low compression factors, the combination between SbS and HEVC proved to be competitive, for high compression factors, and JPEG2000, combined with PDS, provided good performance allied to low computational complexity, all in terms of percent root-mean-square difference [Formula: see text] compression factor. The proposed schemes are effective and, specifically, the modified MMP algorithm can be considered as an interesting alternative for isometric signals, regarding traditional SEMG encoders. Besides, the approach based on off-the-shelf image encoders has the potential of fast implementation and dissemination, given that many embedded systems may already have such encoders available, in the underlying hardware/software architecture.

Innovative Video Diagnostic Equipment for Material Science

NASA Technical Reports Server (NTRS)

Capuano, G.; Titomanlio, D.; Soellner, W.; Seidel, A.

2012-01-01

Materials science experiments under microgravity increasingly rely on advanced optical systems to determine the physical properties of the samples under investigation. This includes video systems with high spatial and temporal resolution. The acquisition, handling, storage and transmission to ground of the resulting video data are very challenging. Since the available downlink data rate is limited, the capability to compress the video data significantly without compromising the data quality is essential. We report on the development of a Digital Video System (DVS) for EML (Electro Magnetic Levitator) which provides real-time video acquisition, high compression using advanced Wavelet algorithms, storage and transmission of a continuous flow of video with different characteristics in terms of image dimensions and frame rates. The DVS is able to operate with the latest generation of high-performance cameras acquiring high resolution video images up to 4Mpixels@60 fps or high frame rate video images up to about 1000 fps@512x512pixels.

Oblivious image watermarking combined with JPEG compression

NASA Astrophysics Data System (ADS)

Chen, Qing; Maitre, Henri; Pesquet-Popescu, Beatrice

2003-06-01

For most data hiding applications, the main source of concern is the effect of lossy compression on hidden information. The objective of watermarking is fundamentally in conflict with lossy compression. The latter attempts to remove all irrelevant and redundant information from a signal, while the former uses the irrelevant information to mask the presence of hidden data. Compression on a watermarked image can significantly affect the retrieval of the watermark. Past investigations of this problem have heavily relied on simulation. It is desirable not only to measure the effect of compression on embedded watermark, but also to control the embedding process to survive lossy compression. In this paper, we focus on oblivious watermarking by assuming that the watermarked image inevitably undergoes JPEG compression prior to watermark extraction. We propose an image-adaptive watermarking scheme where the watermarking algorithm and the JPEG compression standard are jointly considered. Watermark embedding takes into consideration the JPEG compression quality factor and exploits an HVS model to adaptively attain a proper trade-off among transparency, hiding data rate, and robustness to JPEG compression. The scheme estimates the image-dependent payload under JPEG compression to achieve the watermarking bit allocation in a determinate way, while maintaining consistent watermark retrieval performance.

Clinical utility of wavelet compression for resolution-enhanced chest radiography

NASA Astrophysics Data System (ADS)

Andriole, Katherine P.; Hovanes, Michael E.; Rowberg, Alan H.

2000-05-01

This study evaluates the usefulness of wavelet compression for resolution-enhanced storage phosphor chest radiographs in the detection of subtle interstitial disease, pneumothorax and other abnormalities. A wavelet compression technique, MrSIDTM (LizardTech, Inc., Seattle, WA), is implemented which compresses the images from their original 2,000 by 2,000 (2K) matrix size, and then decompresses the image data for display at optimal resolution by matching the spatial frequency characteristics of image objects using a 4,000- square matrix. The 2K-matrix computed radiography (CR) chest images are magnified to a 4K-matrix using wavelet series expansion. The magnified images are compared with the original uncompressed 2K radiographs and with two-times magnification of the original images. Preliminary results show radiologist preference for MrSIDTM wavelet-based magnification over magnification of original data, and suggest that the compressed/decompressed images may provide an enhancement to the original. Data collection for clinical trials of 100 chest radiographs including subtle interstitial abnormalities and/or subtle pneumothoraces and normal cases, are in progress. Three experienced thoracic radiologists will view images side-by- side on calibrated softcopy workstations under controlled viewing conditions, and rank order preference tests will be performed. This technique combines image compression with image enhancement, and suggests that compressed/decompressed images can actually improve the originals.

Onboard Processor for Compressing HSI Data

NASA Technical Reports Server (NTRS)

Cook, Sid; Harsanyi, Joe; Day, John H. (Technical Monitor)

2002-01-01

With EO-1 Hyperion and MightySat in orbit NASA and the DoD are showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor greater than 100, while retaining the necessary spectral fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our initial spectral compression experiments leverage commercial-off-the-shelf (COTS) spectral exploitation algorithms for segmentation, material identification and spectral compression that ASIT has developed. ASIT will also support the modification and integration of this COTS software into the OBP. Other commercially available COTS software for spatial compression will also be employed as part of the overall compression processing sequence. Over the next year elements of a high-performance reconfigurable OBP will be developed to implement proven preprocessing steps that distill the HSI data stream in both spectral and spatial dimensions. The system will intelligently reduce the volume of data that must be stored, transmitted to the ground, and processed while minimizing the loss of information.

Pornographic image recognition and filtering using incremental learning in compressed domain

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Spectrally Adaptable Compressive Sensing Imaging System

DTIC Science & Technology

2014-05-01

signal recovering [?, ?]. The time-varying coded apertures can be implemented using micro-piezo motors [?] or through the use of Digital Micromirror ...feasibility of this testbed by developing a Digital- Micromirror -Device-based Snapshot Spectral Imaging (DMD-SSI) system, which implements CS measurement...Y. Wu, I. O. Mirza, G. R. Arce, and D. W. Prather, ”Development of a digital- micromirror - device- based multishot snapshot spectral imaging

Image processing using Gallium Arsenide (GaAs) technology

NASA Technical Reports Server (NTRS)

Miller, Warner H.

1989-01-01

The need to increase the information return from space-borne imaging systems has increased in the past decade. The use of multi-spectral data has resulted in the need for finer spatial resolution and greater spectral coverage. Onboard signal processing will be necessary in order to utilize the available Tracking and Data Relay Satellite System (TDRSS) communication channel at high efficiency. A generally recognized approach to the increased efficiency of channel usage is through data compression techniques. The compression technique implemented is a differential pulse code modulation (DPCM) scheme with a non-uniform quantizer. The need to advance the state-of-the-art of onboard processing was recognized and a GaAs integrated circuit technology was chosen. An Adaptive Programmable Processor (APP) chip set was developed which is based on an 8-bit slice general processor. The reason for choosing the compression technique for the Multi-spectral Linear Array (MLA) instrument is described. Also a description is given of the GaAs integrated circuit chip set which will demonstrate that data compression can be performed onboard in real time at data rate in the order of 500 Mb/s.

A Framework of Hyperspectral Image Compression using Neural Networks

DOE PAGES

Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; ...

2015-01-01

Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows usmore » to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.« less

MUSIC - Multifunctional stereo imaging camera system for wide angle and high resolution stereo and color observations on the Mars-94 mission

NASA Astrophysics Data System (ADS)

Oertel, D.; Jahn, H.; Sandau, R.; Walter, I.; Driescher, H.

1990-10-01

Objectives of the multifunctional stereo imaging camera (MUSIC) system to be deployed on the Soviet Mars-94 mission are outlined. A high-resolution stereo camera (HRSC) and wide-angle opto-electronic stereo scanner (WAOSS) are combined in terms of hardware, software, technology aspects, and solutions. Both HRSC and WAOSS are push-button instruments containing a single optical system and focal plates with several parallel CCD line sensors. Emphasis is placed on the MUSIC system's stereo capability, its design, mass memory, and data compression. A 1-Gbit memory is divided into two parts: 80 percent for HRSC and 20 percent for WAOSS, while the selected on-line compression strategy is based on macropixel coding and real-time transform coding.

Kilovoltage Imaging of Implanted Fiducials to Monitor Intrafraction Motion With Abdominal Compression During Stereotactic Body Radiation Therapy for Gastrointestinal Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yorke, Ellen, E-mail: yorke@mskcc.org; Xiong, Ying; Han, Qian

2016-07-01

Purpose: To assess intrafraction respiratory motion using a commercial kilovoltage imaging system for abdominal tumor patients with implanted fiducials and breathing constrained by pneumatic compression during stereotactic body radiation therapy (SBRT). Methods and Materials: A pneumatic compression belt limited respiratory motion in 19 patients with radiopaque fiducials in or near their tumor during SBRT for abdominal tumors. Kilovoltage images were acquired at 5- to 6-second intervals during treatment using a commercial system. Intrafractional fiducial displacements were measured using in-house software. The dosimetric effect of the observed displacements was calculated for 3 sessions for each patient. Results: Intrafraction displacement patterns variedmore » between patients and between individual treatment sessions. Averaged over 19 patients, 73 sessions, 7.6% of craniocaudal displacements exceeded 0.5 cm, and 1.2% exceeded 0.75 cm. The calculated single-session dose to 95% of gross tumor volume differed from planned by an average of −1.2% (range, −11.1% to 4.8%) but only for 4 patients was the total 3-session calculated dose to 95% of gross tumor volume more than 3% different from planned. Conclusions: Our pneumatic compression limited intrafractional abdominal target motion, maintained target position established at setup, and was moderately effective in preserving coverage. Commercially available intrafractional imaging is useful for surveillance but can be made more effective and reliable.« less

A block-based JPEG-LS compression technique with lossless region of interest

NASA Astrophysics Data System (ADS)

Deng, Lihua; Huang, Zhenghua; Yao, Shoukui

2018-03-01

JPEG-LS lossless compression algorithm is used in many specialized applications that emphasize on the attainment of high fidelity for its lower complexity and better compression ratios than the lossless JPEG standard. But it cannot prevent error diffusion because of the context dependence of the algorithm, and have low compression rate when compared to lossy compression. In this paper, we firstly divide the image into two parts: ROI regions and non-ROI regions. Then we adopt a block-based image compression technique to decrease the range of error diffusion. We provide JPEG-LS lossless compression for the image blocks which include the whole or part region of interest (ROI) and JPEG-LS near lossless compression for the image blocks which are included in the non-ROI (unimportant) regions. Finally, a set of experiments are designed to assess the effectiveness of the proposed compression method.

Feasibility of video codec algorithms for software-only playback

NASA Astrophysics Data System (ADS)

Rodriguez, Arturo A.; Morse, Ken

1994-05-01

Software-only video codecs can provide good playback performance in desktop computers with a 486 or 68040 CPU running at 33 MHz without special hardware assistance. Typically, playback of compressed video can be categorized into three tasks: the actual decoding of the video stream, color conversion, and the transfer of decoded video data from system RAM to video RAM. By current standards, good playback performance is the decoding and display of video streams of 320 by 240 (or larger) compressed frames at 15 (or greater) frames-per- second. Software-only video codecs have evolved by modifying and tailoring existing compression methodologies to suit video playback in desktop computers. In this paper we examine the characteristics used to evaluate software-only video codec algorithms, namely: image fidelity (i.e., image quality), bandwidth (i.e., compression) ease-of-decoding (i.e., playback performance), memory consumption, compression to decompression asymmetry, scalability, and delay. We discuss the tradeoffs among these variables and the compromises that can be made to achieve low numerical complexity for software-only playback. Frame- differencing approaches are described since software-only video codecs typically employ them to enhance playback performance. To complement other papers that appear in this session of the Proceedings, we review methods derived from binary pattern image coding since these methods are amenable for software-only playback. In particular, we introduce a novel approach called pixel distribution image coding.

Real-time video compressing under DSP/BIOS

NASA Astrophysics Data System (ADS)

Chen, Qiu-ping; Li, Gui-ju

2009-10-01

This paper presents real-time MPEG-4 Simple Profile video compressing based on the DSP processor. The programming framework of video compressing is constructed using TMS320C6416 Microprocessor, TDS510 simulator and PC. It uses embedded real-time operating system DSP/BIOS and the API functions to build periodic function, tasks and interruptions etcs. Realize real-time video compressing. To the questions of data transferring among the system. Based on the architecture of the C64x DSP, utilized double buffer switched and EDMA data transfer controller to transit data from external memory to internal, and realize data transition and processing at the same time; the architecture level optimizations are used to improve software pipeline. The system used DSP/BIOS to realize multi-thread scheduling. The whole system realizes high speed transition of a great deal of data. Experimental results show the encoder can realize real-time encoding of 768*576, 25 frame/s video images.

Multispectral Image Compression for Improvement of Colorimetric and Spectral Reproducibility by Nonlinear Spectral Transform

NASA Astrophysics Data System (ADS)

Yu, Shanshan; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2006-09-01

The article proposes a multispectral image compression scheme using nonlinear spectral transform for better colorimetric and spectral reproducibility. In the method, we show the reduction of colorimetric error under a defined viewing illuminant and also that spectral accuracy can be improved simultaneously using a nonlinear spectral transform called Labplus, which takes into account the nonlinearity of human color vision. Moreover, we show that the addition of diagonal matrices to Labplus can further preserve the spectral accuracy and has a generalized effect of improving the colorimetric accuracy under other viewing illuminants than the defined one. Finally, we discuss the usage of the first-order Markov model to form the analysis vectors for the higher order channels in Labplus to reduce the computational complexity. We implement a multispectral image compression system that integrates Labplus with JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for a 16-band multispectral image show the effectiveness of the proposed scheme.

Effects of image compression and degradation on an automatic diabetic retinopathy screening algorithm

NASA Astrophysics Data System (ADS)

Agurto, C.; Barriga, S.; Murray, V.; Pattichis, M.; Soliz, P.

2010-03-01

Diabetic retinopathy (DR) is one of the leading causes of blindness among adult Americans. Automatic methods for detection of the disease have been developed in recent years, most of them addressing the segmentation of bright and red lesions. In this paper we present an automatic DR screening system that does approach the problem through the segmentation of features. The algorithm determines non-diseased retinal images from those with pathology based on textural features obtained using multiscale Amplitude Modulation-Frequency Modulation (AM-FM) decompositions. The decomposition is represented as features that are the inputs to a classifier. The algorithm achieves 0.88 area under the ROC curve (AROC) for a set of 280 images from the MESSIDOR database. The algorithm is then used to analyze the effects of image compression and degradation, which will be present in most actual clinical or screening environments. Results show that the algorithm is insensitive to illumination variations, but high rates of compression and large blurring effects degrade its performance.

Compression and Transmission of RF Signals for Telediagnosis

NASA Astrophysics Data System (ADS)

Seko, Toshihiro; Doi, Motonori; Oshiro, Osamu; Chihara, Kunihiro

2000-05-01

Health care is a critical issue nowadays. Much emphasis is given to quality care for all people. Telediagnosis has attracted public attention. We propose a new method of ultrasound image transmission for telediagnosis. In conventional methods, video image signals are transmitted. In our method, the RF signals which are acquired by an ultrasound probe, are transmitted. The RF signals can be transformed to color Doppler images or high-resolution images by a receiver. Because a stored form is adopted, the proposed system can be realized with existent technology such as hyper text transfer protocol (HTTP) and file transfer protocol (FTP). In this paper, we describe two lossless compression methods which specialize in the transmission of RF signals. One of the methods uses the characteristics of the RF signal. In the other method, the amount of the data is reduced. Measurements were performed in water targeting an iron block and triangular Styrofoam. Additionally, abdominal fat measurement was performed. Our method achieved a compression rate of 13% with 8 bit data.

Performance assessment of a single-pixel compressive sensing imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2016-05-01

Conventional electro-optical and infrared (EO/IR) systems capture an image by measuring the light incident at each of the millions of pixels in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process known as sparse reconstruction to recover the image as if a fully populated array that satisfies the Nyquist criteria was used. Therefore, CS operates under the assumption that signal acquisition and data compression can be accomplished simultaneously. CS has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations (SWaP-C), reconstruction accuracy, and reconstruction speed to meet operational requirements. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of the two-handheld object target set at range was collected using a passive SWIR single-pixel CS camera for various ranges, mirror resolution, and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled with the Night Vision Integrated Performance Model (NV-IPM) by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques will be discussed.

CWICOM: A Highly Integrated & Innovative CCSDS Image Compression ASIC

NASA Astrophysics Data System (ADS)

Poupat, Jean-Luc; Vitulli, Raffaele

2013-08-01

The space market is more and more demanding in terms of on image compression performances. The earth observation satellites instrument resolution, the agility and the swath are continuously increasing. It multiplies by 10 the volume of picture acquired on one orbit. In parallel, the satellites size and mass are decreasing, requiring innovative electronic technologies reducing size, mass and power consumption. Astrium, leader on the market of the combined solutions for compression and memory for space application, has developed a new image compression ASIC which is presented in this paper. CWICOM is a high performance and innovative image compression ASIC developed by Astrium in the frame of the ESA contract n°22011/08/NLL/LvH. The objective of this ESA contract is to develop a radiation hardened ASIC that implements the CCSDS 122.0-B-1 Standard for Image Data Compression, that has a SpaceWire interface for configuring and controlling the device, and that is compatible with Sentinel-2 interface and with similar Earth Observation missions. CWICOM stands for CCSDS Wavelet Image COMpression ASIC. It is a large dynamic, large image and very high speed image compression ASIC potentially relevant for compression of any 2D image with bi-dimensional data correlation such as Earth observation, scientific data compression… The paper presents some of the main aspects of the CWICOM development, such as the algorithm and specification, the innovative memory organization, the validation approach and the status of the project.

Image Data Compression Having Minimum Perceptual Error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1997-01-01

A method is presented for performing color or grayscale image compression that eliminates redundant and invisible image components. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The quantization matrix comprises visual masking by luminance and contrast technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Proposed data compression schemes for the Galileo S-band contingency mission

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Tong, Kevin

1993-01-01

The Galileo spacecraft is currently on its way to Jupiter and its moons. In April 1991, the high gain antenna (HGA) failed to deploy as commanded. In case the current efforts to deploy the HGA fails, communications during the Jupiter encounters will be through one of two low gain antenna (LGA) on an S-band (2.3 GHz) carrier. A lot of effort has been and will be conducted to attempt to open the HGA. Also various options for improving Galileo's telemetry downlink performance are being evaluated in the event that the HGA will not open at Jupiter arrival. Among all viable options the most promising and powerful one is to perform image and non-image data compression in software onboard the spacecraft. This involves in-flight re-programming of the existing flight software of Galileo's Command and Data Subsystem processors and Attitude and Articulation Control System (AACS) processor, which have very limited computational and memory resources. In this article we describe the proposed data compression algorithms and give their respective compression performance. The planned image compression algorithm is a 4 x 4 or an 8 x 8 multiplication-free integer cosine transform (ICT) scheme, which can be viewed as an integer approximation of the popular discrete cosine transform (DCT) scheme. The implementation complexity of the ICT schemes is much lower than the DCT-based schemes, yet the performances of the two algorithms are indistinguishable. The proposed non-image compression algorith is a Lempel-Ziv-Welch (LZW) variant, which is a lossless universal compression algorithm based on a dynamic dictionary lookup table. We developed a simple and efficient hashing function to perform the string search.

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

An optical color image watermarking scheme by using compressive sensing with human visual characteristics in gyrator domain

NASA Astrophysics Data System (ADS)

Liansheng, Sui; Bei, Zhou; Zhanmin, Wang; Ailing, Tian

2017-05-01

A novel optical color image watermarking scheme considering human visual characteristics is presented in gyrator transform domain. Initially, an appropriate reference image is constructed of significant blocks chosen from the grayscale host image by evaluating visual characteristics such as visual entropy and edge entropy. Three components of the color watermark image are compressed based on compressive sensing, and the corresponding results are combined to form the grayscale watermark. Then, the frequency coefficients of the watermark image are fused into the frequency data of the gyrator-transformed reference image. The fused result is inversely transformed and partitioned, and eventually the watermarked image is obtained by mapping the resultant blocks into their original positions. The scheme can reconstruct the watermark with high perceptual quality and has the enhanced security due to high sensitivity of the secret keys. Importantly, the scheme can be implemented easily under the framework of double random phase encoding with the 4f optical system. To the best of our knowledge, it is the first report on embedding the color watermark into the grayscale host image which will be out of attacker's expectation. Simulation results are given to verify the feasibility and its superior performance in terms of noise and occlusion robustness.

Assessing Mesoscale Material Response via High-Resolution Line-Imaging VISAR

NASA Astrophysics Data System (ADS)

Furnish, M. D.; Trott, W. M.; Mason, J.; Podsednik, J.; Reinhart, W. D.; Hall, C.

2004-07-01

Of special promise for providing dynamic mesoscale response data is the line-imaging VISAR, an instrument for providing spatially resolved velocity histories in dynamic experiments. We have prepared a line-imaging VISAR system capable of spatial resolution in the 10 - 20 micron range. We are applying this instrument to selected experiments on a compressed gas gun, chosen to provide initial data for several problems of interest, including: (1) pore-collapse in single-crystal copper (70 micron diameter hole; 2 different versions); and (2) response of a welded joint in dissimilar materials (Ta, Nb) to ramp loading relative to that of a compression joint.

Optical asymmetric image encryption using gyrator wavelet transform

NASA Astrophysics Data System (ADS)

Mehra, Isha; Nishchal, Naveen K.

2015-11-01

In this paper, we propose a new optical information processing tool termed as gyrator wavelet transform to secure a fully phase image, based on amplitude- and phase-truncation approach. The gyrator wavelet transform constitutes four basic parameters; gyrator transform order, type and level of mother wavelet, and position of different frequency bands. These parameters are used as encryption keys in addition to the random phase codes to the optical cryptosystem. This tool has also been applied for simultaneous compression and encryption of an image. The system's performance and its sensitivity to the encryption parameters, such as, gyrator transform order, and robustness has also been analyzed. It is expected that this tool will not only update current optical security systems, but may also shed some light on future developments. The computer simulation results demonstrate the abilities of the gyrator wavelet transform as an effective tool, which can be used in various optical information processing applications, including image encryption, and image compression. Also this tool can be applied for securing the color image, multispectral, and three-dimensional images.

Web-based video monitoring of CT and MRI procedures

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Dahlbom, Magdalena; Kho, Hwa T.; Valentino, Daniel J.; McCoy, J. Michael

2000-05-01

A web-based video transmission of images from CT and MRI consoles was implemented in an Intranet environment for real- time monitoring of ongoing procedures. Images captured from the consoles are compressed to video resolution and broadcasted through a web server. When called upon, the attending radiologists can view these live images on any computer within the secured Intranet network. With adequate compression, these images can be displayed simultaneously in different locations at a rate of 2 to 5 images/sec through standard LAN. The quality of the images being insufficient for diagnostic purposes, our users survey showed that they were suitable for supervising a procedure, positioning the imaging slices and for routine quality checking before completion of a study. The system was implemented at UCLA to monitor 9 CTs and 6 MRIs distributed in 4 buildings. This system significantly improved the radiologists productivity by saving precious time spent in trips between reading rooms and examination rooms. It also improved patient throughput by reducing the waiting time for the radiologists to come to check a study before moving the patient from the scanner.

Low-rate image coding using vector quantization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makur, A.

1990-01-01

This thesis deals with the development and analysis of a computationally simple vector quantization image compression system for coding monochrome images at low bit rate. Vector quantization has been known to be an effective compression scheme when a low bit rate is desirable, but the intensive computation required in a vector quantization encoder has been a handicap in using it for low rate image coding. The present work shows that, without substantially increasing the coder complexity, it is indeed possible to achieve acceptable picture quality while attaining a high compression ratio. Several modifications to the conventional vector quantization coder aremore » proposed in the thesis. These modifications are shown to offer better subjective quality when compared to the basic coder. Distributed blocks are used instead of spatial blocks to construct the input vectors. A class of input-dependent weighted distortion functions is used to incorporate psychovisual characteristics in the distortion measure. Computationally simple filtering techniques are applied to further improve the decoded image quality. Finally, unique designs of the vector quantization coder using electronic neural networks are described, so that the coding delay is reduced considerably.« less

Reconfigurable Hardware for Compressing Hyperspectral Image Data

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh; Namkung, Jeffrey; Villapando, Carlos; Kiely, Aaron; Klimesh, Matthew; Xie, Hua

2010-01-01

High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

Optimal color coding for compression of true color images

NASA Astrophysics Data System (ADS)

Musatenko, Yurij S.; Kurashov, Vitalij N.

1998-11-01

In the paper we present the method that improves lossy compression of the true color or other multispectral images. The essence of the method is to project initial color planes into Karhunen-Loeve (KL) basis that gives completely decorrelated representation for the image and to compress basis functions instead of the planes. To do that the new fast algorithm of true KL basis construction with low memory consumption is suggested and our recently proposed scheme for finding optimal losses of Kl functions while compression is used. Compare to standard JPEG compression of the CMYK images the method provides the PSNR gain from 0.2 to 2 dB for the convenient compression ratios. Experimental results are obtained for high resolution CMYK images. It is demonstrated that presented scheme could work on common hardware.

Simultaneous compression and encryption of closely resembling images: application to video sequences and polarimetric images.

PubMed

Aldossari, M; Alfalou, A; Brosseau, C

2014-09-22

This study presents and validates an optimized method of simultaneous compression and encryption designed to process images with close spectra. This approach is well adapted to the compression and encryption of images of a time-varying scene but also to static polarimetric images. We use the recently developed spectral fusion method [Opt. Lett.35, 1914-1916 (2010)] to deal with the close resemblance of the images. The spectral plane (containing the information to send and/or to store) is decomposed in several independent areas which are assigned according a specific way. In addition, each spectrum is shifted in order to minimize their overlap. The dual purpose of these operations is to optimize the spectral plane allowing us to keep the low- and high-frequency information (compression) and to introduce an additional noise for reconstructing the images (encryption). Our results show that not only can the control of the spectral plane enhance the number of spectra to be merged, but also that a compromise between the compression rate and the quality of the reconstructed images can be tuned. We use a root-mean-square (RMS) optimization criterion to treat compression. Image encryption is realized at different security levels. Firstly, we add a specific encryption level which is related to the different areas of the spectral plane, and then, we make use of several random phase keys. An in-depth analysis at the spectral fusion methodology is done in order to find a good trade-off between the compression rate and the quality of the reconstructed images. Our new proposal spectral shift allows us to minimize the image overlap. We further analyze the influence of the spectral shift on the reconstructed image quality and compression rate. The performance of the multiple-image optical compression and encryption method is verified by analyzing several video sequences and polarimetric images.

A Lossless hybrid wavelet-fractal compression for welding radiographic images.

PubMed

Mekhalfa, Faiza; Avanaki, Mohammad R N; Berkani, Daoud

2016-01-01

In this work a lossless wavelet-fractal image coder is proposed. The process starts by compressing and decompressing the original image using wavelet transformation and fractal coding algorithm. The decompressed image is removed from the original one to obtain a residual image which is coded by using Huffman algorithm. Simulation results show that with the proposed scheme, we achieve an infinite peak signal to noise ratio (PSNR) with higher compression ratio compared to typical lossless method. Moreover, the use of wavelet transform speeds up the fractal compression algorithm by reducing the size of the domain pool. The compression results of several welding radiographic images using the proposed scheme are evaluated quantitatively and compared with the results of Huffman coding algorithm.

High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

NASA Astrophysics Data System (ADS)

Zhao, Shengmei; Wang, Le; Liang, Wenqiang; Cheng, Weiwen; Gong, Longyan

2015-10-01

In this paper, we propose a high performance optical encryption (OE) scheme based on computational ghost imaging (GI) with QR code and compressive sensing (CS) technique, named QR-CGI-OE scheme. N random phase screens, generated by Alice, is a secret key and be shared with its authorized user, Bob. The information is first encoded by Alice with QR code, and the QR-coded image is then encrypted with the aid of computational ghost imaging optical system. Here, measurement results from the GI optical system's bucket detector are the encrypted information and be transmitted to Bob. With the key, Bob decrypts the encrypted information to obtain the QR-coded image with GI and CS techniques, and further recovers the information by QR decoding. The experimental and numerical simulated results show that the authorized users can recover completely the original image, whereas the eavesdroppers can not acquire any information about the image even the eavesdropping ratio (ER) is up to 60% at the given measurement times. For the proposed scheme, the number of bits sent from Alice to Bob are reduced considerably and the robustness is enhanced significantly. Meantime, the measurement times in GI system is reduced and the quality of the reconstructed QR-coded image is improved.

Digital mammography, cancer screening: Factors important for image compression

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.; Blaine, G. James; Doi, Kunio; Yaffe, Martin J.; Shtern, Faina; Brown, G. Stephen; Winfield, Daniel L.; Kallergi, Maria

1993-01-01

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers.

Wavelet/scalar quantization compression standard for fingerprint images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brislawn, C.M.

1996-06-12

US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class ofmore » potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.« less

Image compression technique

DOEpatents

Fu, Chi-Yung; Petrich, Loren I.

1997-01-01

An image is compressed by identifying edge pixels of the image; creating a filled edge array of pixels each of the pixels in the filled edge array which corresponds to an edge pixel having a value equal to the value of a pixel of the image array selected in response to the edge pixel, and each of the pixels in the filled edge array which does not correspond to an edge pixel having a value which is a weighted average of the values of surrounding pixels in the filled edge array which do correspond to edge pixels; and subtracting the filled edge array from the image array to create a difference array. The edge file and the difference array are then separately compressed and transmitted or stored. The original image is later reconstructed by creating a preliminary array in response to the received edge file, and adding the preliminary array to the received difference array. Filling is accomplished by solving Laplace's equation using a multi-grid technique. Contour and difference file coding techniques also are described. The techniques can be used in a method for processing a plurality of images by selecting a respective compression approach for each image, compressing each of the images according to the compression approach selected, and transmitting each of the images as compressed, in correspondence with an indication of the approach selected for the image.

Image compression technique

DOEpatents

Fu, C.Y.; Petrich, L.I.

1997-03-25

An image is compressed by identifying edge pixels of the image; creating a filled edge array of pixels each of the pixels in the filled edge array which corresponds to an edge pixel having a value equal to the value of a pixel of the image array selected in response to the edge pixel, and each of the pixels in the filled edge array which does not correspond to an edge pixel having a value which is a weighted average of the values of surrounding pixels in the filled edge array which do correspond to edge pixels; and subtracting the filled edge array from the image array to create a difference array. The edge file and the difference array are then separately compressed and transmitted or stored. The original image is later reconstructed by creating a preliminary array in response to the received edge file, and adding the preliminary array to the received difference array. Filling is accomplished by solving Laplace`s equation using a multi-grid technique. Contour and difference file coding techniques also are described. The techniques can be used in a method for processing a plurality of images by selecting a respective compression approach for each image, compressing each of the images according to the compression approach selected, and transmitting each of the images as compressed, in correspondence with an indication of the approach selected for the image. 16 figs.

Hyperspectral data compression using a Wiener filter predictor

NASA Astrophysics Data System (ADS)

Villeneuve, Pierre V.; Beaven, Scott G.; Stocker, Alan D.

2013-09-01

The application of compression to hyperspectral image data is a significant technical challenge. A primary bottleneck in disseminating data products to the tactical user community is the limited communication bandwidth between the airborne sensor and the ground station receiver. This report summarizes the newly-developed "Z-Chrome" algorithm for lossless compression of hyperspectral image data. A Wiener filter prediction framework is used as a basis for modeling new image bands from already-encoded bands. The resulting residual errors are then compressed using available state-of-the-art lossless image compression functions. Compression performance is demonstrated using a large number of test data collected over a wide variety of scene content from six different airborne and spaceborne sensors .

Impact of lossy compression on diagnostic accuracy of radiographs for periapical lesions

NASA Technical Reports Server (NTRS)

Eraso, Francisco E.; Analoui, Mostafa; Watson, Andrew B.; Rebeschini, Regina

2002-01-01

OBJECTIVES: The purpose of this study was to evaluate the lossy Joint Photographic Experts Group compression for endodontic pretreatment digital radiographs. STUDY DESIGN: Fifty clinical charge-coupled device-based, digital radiographs depicting periapical areas were selected. Each image was compressed at 2, 4, 8, 16, 32, 48, and 64 compression ratios. One root per image was marked for examination. Images were randomized and viewed by four clinical observers under standardized viewing conditions. Each observer read the image set three times, with at least two weeks between each reading. Three pre-selected sites per image (mesial, distal, apical) were scored on a five-scale score confidence scale. A panel of three examiners scored the uncompressed images, with a consensus score for each site. The consensus score was used as the baseline for assessing the impact of lossy compression on the diagnostic values of images. The mean absolute error between consensus and observer scores was computed for each observer, site, and reading session. RESULTS: Balanced one-way analysis of variance for all observers indicated that for compression ratios 48 and 64, there was significant difference between mean absolute error of uncompressed and compressed images (P <.05). After converting the five-scale score to two-level diagnostic values, the diagnostic accuracy was strongly correlated (R (2) = 0.91) with the compression ratio. CONCLUSION: The results of this study suggest that high compression ratios can have a severe impact on the diagnostic quality of the digital radiographs for detection of periapical lesions.

Measurement of compressed breast thickness by optical stereoscopic photogrammetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tyson, Albert H.; Mawdsley, Gordon E.; Yaffe, Martin J.

2009-02-15

The determination of volumetric breast density (VBD) from mammograms requires accurate knowledge of the thickness of the compressed breast. In attempting to accurately determine VBD from images obtained on conventional mammography systems, the authors found that the thickness reported by a number of mammography systems in the field varied by as much as 15 mm when compressing the same breast or phantom. In order to evaluate the behavior of mammographic compression systems and to be able to predict the thickness at different locations in the breast on patients, they have developed a method for measuring the local thickness of themore » breast at all points of contact with the compression paddle using optical stereoscopic photogrammetry. On both flat (solid) and compressible phantoms, the measurements were accurate to better than 1 mm with a precision of 0.2 mm. In a pilot study, this method was used to measure thickness on 108 volunteers who were undergoing mammography examination. This measurement tool will allow us to characterize paddle surface deformations, deflections and calibration offsets for mammographic units.« less

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

100J Pulsed Laser Shock Driver for Dynamic Compression Research

NASA Astrophysics Data System (ADS)

Wang, X.; Sethian, J.; Bromage, J.; Fochs, S.; Broege, D.; Zuegel, J.; Roides, R.; Cuffney, R.; Brent, G.; Zweiback, J.; Currier, Z.; D'Amico, K.; Hawreliak, J.; Zhang, J.; Rigg, P. A.; Gupta, Y. M.

2017-06-01

Logos Technologies and the Laboratory for Laser Energetics (LLE, University of Rochester) - in partnership with Washington State University - have designed, built and deployed a one of a kind 100J pulsed UV (351 nm) laser system to perform real-time, x-ray diffraction and imaging experiments in laser-driven compression experiments at the Dynamic Compression Sector (DCS) at the Advanced Photon Source, Argonne National Laboratory. The laser complements the other dynamic compression drivers at DCS. The laser system features beam smoothing for 2-d spatially uniform loading of samples and four, highly reproducible, temporal profiles (total pulse duration: 5-15 ns) to accommodate a wide variety of scientific needs. Other pulse shapes can be achieved as the experimental needs evolve. Timing of the laser pulse is highly precise (<200 ps) to allow accurate synchronization of the x-rays with the dynamic compression event. Details of the laser system, its operating parameters, and representative results will be presented. Work supported by DOE/NNSA.

The effect of JPEG compression on automated detection of microaneurysms in retinal images

NASA Astrophysics Data System (ADS)

Cree, M. J.; Jelinek, H. F.

2008-02-01

As JPEG compression at source is ubiquitous in retinal imaging, and the block artefacts introduced are known to be of similar size to microaneurysms (an important indicator of diabetic retinopathy) it is prudent to evaluate the effect of JPEG compression on automated detection of retinal pathology. Retinal images were acquired at high quality and then compressed to various lower qualities. An automated microaneurysm detector was run on the retinal images of various qualities of JPEG compression and the ability to predict the presence of diabetic retinopathy based on the detected presence of microaneurysms was evaluated with receiver operating characteristic (ROC) methodology. The negative effect of JPEG compression on automated detection was observed even at levels of compression sometimes used in retinal eye-screening programmes and these may have important clinical implications for deciding on acceptable levels of compression for a fully automated eye-screening programme.

Novel image compression-encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing

NASA Astrophysics Data System (ADS)

Zhou, Nanrun; Zhang, Aidi; Zheng, Fen; Gong, Lihua

2014-10-01

The existing ways to encrypt images based on compressive sensing usually treat the whole measurement matrix as the key, which renders the key too large to distribute and memorize or store. To solve this problem, a new image compression-encryption hybrid algorithm is proposed to realize compression and encryption simultaneously, where the key is easily distributed, stored or memorized. The input image is divided into 4 blocks to compress and encrypt, then the pixels of the two adjacent blocks are exchanged randomly by random matrices. The measurement matrices in compressive sensing are constructed by utilizing the circulant matrices and controlling the original row vectors of the circulant matrices with logistic map. And the random matrices used in random pixel exchanging are bound with the measurement matrices. Simulation results verify the effectiveness, security of the proposed algorithm and the acceptable compression performance.

COxSwAIN: Compressive Sensing for Advanced Imaging and Navigation

NASA Technical Reports Server (NTRS)

Kurwitz, Richard; Pulley, Marina; LaFerney, Nathan; Munoz, Carlos

2015-01-01

The COxSwAIN project focuses on building an image and video compression scheme that can be implemented in a small or low-power satellite. To do this, we used Compressive Sensing, where the compression is performed by matrix multiplications on the satellite and reconstructed on the ground. Our paper explains our methodology and demonstrates the results of the scheme, being able to achieve high quality image compression that is robust to noise and corruption.

Efficient Imaging and Real-Time Display of Scanning Ion Conductance Microscopy Based on Block Compressive Sensing

NASA Astrophysics Data System (ADS)

Li, Gongxin; Li, Peng; Wang, Yuechao; Wang, Wenxue; Xi, Ning; Liu, Lianqing

2014-07-01

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it is widely used in imaging soft samples for many distinctive advantages. However, the scanning speed of SICM is much slower than other SPMs. Compressive sensing (CS) could improve scanning speed tremendously by breaking through the Shannon sampling theorem, but it still requires too much time in image reconstruction. Block compressive sensing can be applied to SICM imaging to further reduce the reconstruction time of sparse signals, and it has another unique application that it can achieve the function of image real-time display in SICM imaging. In this article, a new method of dividing blocks and a new matrix arithmetic operation were proposed to build the block compressive sensing model, and several experiments were carried out to verify the superiority of block compressive sensing in reducing imaging time and real-time display in SICM imaging.

Compressed Sensing for Body MRI

PubMed Central

Feng, Li; Benkert, Thomas; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo; Chandarana, Hersh

2016-01-01

The introduction of compressed sensing for increasing imaging speed in MRI has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than that are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This paper presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and non-linear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the paper discusses current challenges and future opportunities. PMID:27981664

Digital Image Compression Using Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Serra-Ricart, M.; Garrido, L.; Gaitan, V.; Aloy, A.

1993-01-01

The problem of storing, transmitting, and manipulating digital images is considered. Because of the file sizes involved, large amounts of digitized image information are becoming common in modern projects. Our goal is to described an image compression transform coder based on artificial neural networks techniques (NNCTC). A comparison of the compression results obtained from digital astronomical images by the NNCTC and the method used in the compression of the digitized sky survey from the Space Telescope Science Institute based on the H-transform is performed in order to assess the reliability of the NNCTC.

Measurement of Full Field Strains in Filament Wound Composite Tubes Under Axial Compressive Loading by the Digital Image Correlation (DIC) Technique

DTIC Science & Technology

2013-05-01

Measurement of Full Field Strains in Filament Wound Composite Tubes Under Axial Compressive Loading by the Digital Image Correlation (DIC...of Full Field Strains in Filament Wound Composite Tubes Under Axial Compressive Loading by the Digital Image Correlation (DIC) Technique Todd C...Wound Composite Tubes Under Axial Compressive Loading by the Digital Image Correlation (DIC) Technique 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

Experimental scheme and restoration algorithm of block compression sensing

NASA Astrophysics Data System (ADS)

Zhang, Linxia; Zhou, Qun; Ke, Jun

2018-01-01

Compressed Sensing (CS) can use the sparseness of a target to obtain its image with much less data than that defined by the Nyquist sampling theorem. In this paper, we study the hardware implementation of a block compression sensing system and its reconstruction algorithms. Different block sizes are used. Two algorithms, the orthogonal matching algorithm (OMP) and the full variation minimum algorithm (TV) are used to obtain good reconstructions. The influence of block size on reconstruction is also discussed.

The effects of video compression on acceptability of images for monitoring life sciences experiments

NASA Astrophysics Data System (ADS)

Haines, Richard F.; Chuang, Sherry L.

1992-07-01

Future manned space operations for Space Station Freedom will call for a variety of carefully planned multimedia digital communications, including full-frame-rate color video, to support remote operations of scientific experiments. This paper presents the results of an investigation to determine if video compression is a viable solution to transmission bandwidth constraints. It reports on the impact of different levels of compression and associated calculational parameters on image acceptability to investigators in life-sciences research at ARC. Three nonhuman life-sciences disciplines (plant, rodent, and primate biology) were selected for this study. A total of 33 subjects viewed experimental scenes in their own scientific disciplines. Ten plant scientists viewed still images of wheat stalks at various stages of growth. Each image was compressed to four different compression levels using the Joint Photographic Expert Group (JPEG) standard algorithm, and the images were presented in random order. Twelve and eleven staffmembers viewed 30-sec videotaped segments showing small rodents and a small primate, respectively. Each segment was repeated at four different compression levels in random order using an inverse cosine transform (ICT) algorithm. Each viewer made a series of subjective image-quality ratings. There was a significant difference in image ratings according to the type of scene viewed within disciplines; thus, ratings were scene dependent. Image (still and motion) acceptability does, in fact, vary according to compression level. The JPEG still-image-compression levels, even with the large range of 5:1 to 120:1 in this study, yielded equally high levels of acceptability. In contrast, the ICT algorithm for motion compression yielded a sharp decline in acceptability below 768 kb/sec. Therefore, if video compression is to be used as a solution for overcoming transmission bandwidth constraints, the effective management of the ratio and compression parameters according to scientific discipline and experiment type is critical to the success of remote experiments.

The effects of video compression on acceptability of images for monitoring life sciences experiments

NASA Technical Reports Server (NTRS)

Haines, Richard F.; Chuang, Sherry L.

1992-01-01

Future manned space operations for Space Station Freedom will call for a variety of carefully planned multimedia digital communications, including full-frame-rate color video, to support remote operations of scientific experiments. This paper presents the results of an investigation to determine if video compression is a viable solution to transmission bandwidth constraints. It reports on the impact of different levels of compression and associated calculational parameters on image acceptability to investigators in life-sciences research at ARC. Three nonhuman life-sciences disciplines (plant, rodent, and primate biology) were selected for this study. A total of 33 subjects viewed experimental scenes in their own scientific disciplines. Ten plant scientists viewed still images of wheat stalks at various stages of growth. Each image was compressed to four different compression levels using the Joint Photographic Expert Group (JPEG) standard algorithm, and the images were presented in random order. Twelve and eleven staffmembers viewed 30-sec videotaped segments showing small rodents and a small primate, respectively. Each segment was repeated at four different compression levels in random order using an inverse cosine transform (ICT) algorithm. Each viewer made a series of subjective image-quality ratings. There was a significant difference in image ratings according to the type of scene viewed within disciplines; thus, ratings were scene dependent. Image (still and motion) acceptability does, in fact, vary according to compression level. The JPEG still-image-compression levels, even with the large range of 5:1 to 120:1 in this study, yielded equally high levels of acceptability. In contrast, the ICT algorithm for motion compression yielded a sharp decline in acceptability below 768 kb/sec. Therefore, if video compression is to be used as a solution for overcoming transmission bandwidth constraints, the effective management of the ratio and compression parameters according to scientific discipline and experiment type is critical to the success of remote experiments.

Real-Time Aggressive Image Data Compression

DTIC Science & Technology

1990-03-31

implemented with higher degrees of modularity, concurrency, and higher levels of machine intelligence , thereby providing higher data -throughput rates...Project Summary Project Title: Real-Time Aggressive Image Data Compression Principal Investigators: Dr. Yih-Fang Huang and Dr. Ruey-wen Liu Institution...Summary The objective of the proposed research is to develop reliable algorithms !.hat can achieve aggressive image data compression (with a compression

Context Modeler for Wavelet Compression of Spectral Hyperspectral Images

NASA Technical Reports Server (NTRS)

Kiely, Aaron; Xie, Hua; Klimesh, matthew; Aranki, Nazeeh

2010-01-01

A context-modeling sub-algorithm has been developed as part of an algorithm that effects three-dimensional (3D) wavelet-based compression of hyperspectral image data. The context-modeling subalgorithm, hereafter denoted the context modeler, provides estimates of probability distributions of wavelet-transformed data being encoded. These estimates are utilized by an entropy coding subalgorithm that is another major component of the compression algorithm. The estimates make it possible to compress the image data more effectively than would otherwise be possible. The following background discussion is prerequisite to a meaningful summary of the context modeler. This discussion is presented relative to ICER-3D, which is the name attached to a particular compression algorithm and the software that implements it. The ICER-3D software is summarized briefly in the preceding article, ICER-3D Hyperspectral Image Compression Software (NPO-43238). Some aspects of this algorithm were previously described, in a slightly more general context than the ICER-3D software, in "Improving 3D Wavelet-Based Compression of Hyperspectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. In turn, ICER-3D is a product of generalization of ICER, another previously reported algorithm and computer program that can perform both lossless and lossy wavelet-based compression and decompression of gray-scale-image data. In ICER-3D, hyperspectral image data are decomposed using a 3D discrete wavelet transform (DWT). Following wavelet decomposition, mean values are subtracted from spatial planes of spatially low-pass subbands prior to encoding. The resulting data are converted to sign-magnitude form and compressed. In ICER-3D, compression is progressive, in that compressed information is ordered so that as more of the compressed data stream is received, successive reconstructions of the hyperspectral image data are of successively higher overall fidelity.

Development of a digital-micromirror-device-based multishot snapshot spectral imaging system.

PubMed

Wu, Yuehao; Mirza, Iftekhar O; Arce, Gonzalo R; Prather, Dennis W

2011-07-15

We report on the development of a digital-micromirror-device (DMD)-based multishot snapshot spectral imaging (DMD-SSI) system as an alternative to current piezostage-based multishot coded aperture snapshot spectral imager (CASSI) systems. In this system, a DMD is used to implement compressive sensing (CS) measurement patterns for reconstructing the spatial/spectral information of an imaging scene. Based on the CS measurement results, we demonstrated the concurrent reconstruction of 24 spectral images. The DMD-SSI system is versatile in nature as it can be used to implement independent CS measurement patterns in addition to spatially shifted patterns that piezostage-based systems can offer. © 2011 Optical Society of America

Image compression evaluation for digital cinema: the case of Star Wars: Episode II

NASA Astrophysics Data System (ADS)

Schnuelle, David L.

2003-05-01

A program of evaluation of compression algorithms proposed for use in a digital cinema application is described and the results presented in general form. The work was intended to aid in the selection of a compression system to be used for the digital cinema release of Star Wars: Episode II, in May 2002. An additional goal was to provide feedback to the algorithm proponents on what parameters and performance levels the feature film industry is looking for in digital cinema compression. The primary conclusion of the test program is that any of the current digital cinema compression proponents will work for digital cinema distribution to today's theaters.

Image-Data Compression Using Edge-Optimizing Algorithm for WFA Inference.

ERIC Educational Resources Information Center

Culik, Karel II; Kari, Jarkko

1994-01-01

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

Performance evaluation of the multiple-image optical compression and encryption method by increasing the number of target images

NASA Astrophysics Data System (ADS)

Aldossari, M.; Alfalou, A.; Brosseau, C.

2017-08-01

In an earlier study [Opt. Express 22, 22349-22368 (2014)], a compression and encryption method that simultaneous compress and encrypt closely resembling images was proposed and validated. This multiple-image optical compression and encryption (MIOCE) method is based on a special fusion of the different target images spectra in the spectral domain. Now for the purpose of assessing the capacity of the MIOCE method, we would like to evaluate and determine the influence of the number of target images. This analysis allows us to evaluate the performance limitation of this method. To achieve this goal, we use a criterion based on the root-mean-square (RMS) [Opt. Lett. 35, 1914-1916 (2010)] and compression ratio to determine the spectral plane area. Then, the different spectral areas are merged in a single spectrum plane. By choosing specific areas, we can compress together 38 images instead of 26 using the classical MIOCE method. The quality of the reconstructed image is evaluated by making use of the mean-square-error criterion (MSE).

Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zimmermann, Bernhard B.; Deng, Bin; Singh, Bhawana; Martino, Mark; Selb, Juliette; Fang, Qianqian; Sajjadi, Amir Y.; Cormier, Jayne; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.; Saksena, Mansi A.; Carp, Stefan A.

2017-04-01

Diffuse optical tomography (DOT) is emerging as a noninvasive functional imaging method for breast cancer diagnosis and neoadjuvant chemotherapy monitoring. In particular, the multimodal approach of combining DOT with x-ray digital breast tomosynthesis (DBT) is especially synergistic as DBT prior information can be used to enhance the DOT reconstruction. DOT, in turn, provides a functional information overlay onto the mammographic images, increasing sensitivity and specificity to cancer pathology. We describe a dynamic DOT apparatus designed for tight integration with commercial DBT scanners and providing a fast (up to 1 Hz) image acquisition rate to enable tracking hemodynamic changes induced by the mammographic breast compression. The system integrates 96 continuous-wave and 24 frequency-domain source locations as well as 32 continuous wave and 20 frequency-domain detection locations into low-profile plastic plates that can easily mate to the DBT compression paddle and x-ray detector cover, respectively. We demonstrate system performance using static and dynamic tissue-like phantoms as well as in vivo images acquired from the pool of patients recalled for breast biopsies at the Massachusetts General Hospital Breast Imaging Division.

Compression of multispectral fluorescence microscopic images based on a modified set partitioning in hierarchal trees

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Robinson, J. Paul; Rajwa, Bartek

2009-02-01

Modern automated microscopic imaging techniques such as high-content screening (HCS), high-throughput screening, 4D imaging, and multispectral imaging are capable of producing hundreds to thousands of images per experiment. For quick retrieval, fast transmission, and storage economy, these images should be saved in a compressed format. A considerable number of techniques based on interband and intraband redundancies of multispectral images have been proposed in the literature for the compression of multispectral and 3D temporal data. However, these works have been carried out mostly in the elds of remote sensing and video processing. Compression for multispectral optical microscopy imaging, with its own set of specialized requirements, has remained under-investigated. Digital photography{oriented 2D compression techniques like JPEG (ISO/IEC IS 10918-1) and JPEG2000 (ISO/IEC 15444-1) are generally adopted for multispectral images which optimize visual quality but do not necessarily preserve the integrity of scientic data, not to mention the suboptimal performance of 2D compression techniques in compressing 3D images. Herein we report our work on a new low bit-rate wavelet-based compression scheme for multispectral fluorescence biological imaging. The sparsity of signicant coefficients in high-frequency subbands of multispectral microscopic images is found to be much greater than in natural images; therefore a quad-tree concept such as Said et al.'s SPIHT1 along with correlation of insignicant wavelet coefficients has been proposed to further exploit redundancy at high-frequency subbands. Our work propose a 3D extension to SPIHT, incorporating a new hierarchal inter- and intra-spectral relationship amongst the coefficients of 3D wavelet-decomposed image. The new relationship, apart from adopting the parent-child relationship of classical SPIHT, also brought forth the conditional "sibling" relationship by relating only the insignicant wavelet coefficients of subbands at the same level of decomposition. The insignicant quadtrees in dierent subbands in the high-frequency subband class are coded by a combined function to reduce redundancy. A number of experiments conducted on microscopic multispectral images have shown promising results for the proposed method over current state-of-the-art image-compression techniques.

Designing an efficient LT-code with unequal error protection for image transmission

NASA Astrophysics Data System (ADS)

S. Marques, F.; Schwartz, C.; Pinho, M. S.; Finamore, W. A.

2015-10-01

The use of images from earth observation satellites is spread over different applications, such as a car navigation systems and a disaster monitoring. In general, those images are captured by on board imaging devices and must be transmitted to the Earth using a communication system. Even though a high resolution image can produce a better Quality of Service, it leads to transmitters with high bit rate which require a large bandwidth and expend a large amount of energy. Therefore, it is very important to design efficient communication systems. From communication theory, it is well known that a source encoder is crucial in an efficient system. In a remote sensing satellite image transmission, this efficiency is achieved by using an image compressor, to reduce the amount of data which must be transmitted. The Consultative Committee for Space Data Systems (CCSDS), a multinational forum for the development of communications and data system standards for space flight, establishes a recommended standard for a data compression algorithm for images from space systems. Unfortunately, in the satellite communication channel, the transmitted signal is corrupted by the presence of noise, interference signals, etc. Therefore, the receiver of a digital communication system may fail to recover the transmitted bit. Actually, a channel code can be used to reduce the effect of this failure. In 2002, the Luby Transform code (LT-code) was introduced and it was shown that it was very efficient when the binary erasure channel model was used. Since the effect of the bit recovery failure depends on the position of the bit in the compressed image stream, in the last decade many e orts have been made to develop LT-code with unequal error protection. In 2012, Arslan et al. showed improvements when LT-codes with unequal error protection were used in images compressed by SPIHT algorithm. The techniques presented by Arslan et al. can be adapted to work with the algorithm for image compression recommended by CCSDS. In fact, to design a LT-code with an unequal error protection, the bit stream produced by the algorithm recommended by CCSDS must be partitioned in M disjoint sets of bits. Using the weighted approach, the LT-code produces M different failure probabilities for each set of bits, p1, ..., pM leading to a total probability of failure, p which is an average of p1, ..., pM. In general, the parameters of the LT-code with unequal error protection is chosen using a heuristic procedure. In this work, we analyze the problem of choosing the LT-code parameters to optimize two figure of merits: (a) the probability of achieving a minimum acceptable PSNR, and (b) the mean of PSNR, given that the minimum acceptable PSNR has been achieved. Given the rate-distortion curve achieved by CCSDS recommended algorithm, this work establishes a closed form of the mean of PSNR (given that the minimum acceptable PSNR has been achieved) as a function of p1, ..., pM. The main contribution of this work is the study of a criteria to select the parameters p1, ..., pM to optimize the performance of image transmission.

Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

PubMed Central

Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

2014-01-01

Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches. PMID:25110741

Multispectral image compression based on DSC combined with CCSDS-IDC.

PubMed

Li, Jin; Xing, Fei; Sun, Ting; You, Zheng

2014-01-01

Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

Effect of data compression on diagnostic accuracy in digital hand and chest radiography

NASA Astrophysics Data System (ADS)

Sayre, James W.; Aberle, Denise R.; Boechat, Maria I.; Hall, Theodore R.; Huang, H. K.; Ho, Bruce K. T.; Kashfian, Payam; Rahbar, Guita

1992-05-01

Image compression is essential to handle a large volume of digital images including CT, MR, CR, and digitized films in a digital radiology operation. The full-frame bit allocation using the cosine transform technique developed during the last few years has been proven to be an excellent irreversible image compression method. This paper describes the effect of using the hardware compression module on diagnostic accuracy in hand radiographs with subperiosteal resorption and chest radiographs with interstitial disease. Receiver operating characteristic analysis using 71 hand radiographs and 52 chest radiographs with five observers each demonstrates that there is no statistical significant difference in diagnostic accuracy between the original films and the compressed images with a compression ratio as high as 20:1.

Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements

DOE PAGES

Wang, Liming; Huang, Jiaji; Yuan, Xin; ...

2015-09-17

The measurement matrix employed in compressive sensing typically cannot be known precisely a priori and must be estimated via calibration. One may take multiple compressive measurements, from which the measurement matrix and underlying signals may be estimated jointly. This is of interest as well when the measurement matrix may change as a function of the details of what is measured. This problem has been considered recently for Gaussian measurement noise, and here we develop this idea with application to Poisson systems. A collaborative maximum likelihood algorithm and alternating proximal gradient algorithm are proposed, and associated theoretical performance guarantees are establishedmore » based on newly derived concentration-of-measure results. A Bayesian model is then introduced, to improve flexibility and generality. Connections between the maximum likelihood methods and the Bayesian model are developed, and example results are presented for a real compressive X-ray imaging system.« less

Architecture for one-shot compressive imaging using computer-generated holograms.

PubMed

Macfaden, Alexander J; Kindness, Stephen J; Wilkinson, Timothy D

2016-09-10

We propose a synchronous implementation of compressive imaging. This method is mathematically equivalent to prevailing sequential methods, but uses a static holographic optical element to create a spatially distributed spot array from which the image can be reconstructed with an instantaneous measurement. We present the holographic design requirements and demonstrate experimentally that the linear algebra of compressed imaging can be implemented with this technique. We believe this technique can be integrated with optical metasurfaces, which will allow the development of new compressive sensing methods.

JPEG vs. JPEG 2000: an objective comparison of image encoding quality

NASA Astrophysics Data System (ADS)

Ebrahimi, Farzad; Chamik, Matthieu; Winkler, Stefan

2004-11-01

This paper describes an objective comparison of the image quality of different encoders. Our approach is based on estimating the visual impact of compression artifacts on perceived quality. We present a tool that measures these artifacts in an image and uses them to compute a prediction of the Mean Opinion Score (MOS) obtained in subjective experiments. We show that the MOS predictions by our proposed tool are a better indicator of perceived image quality than PSNR, especially for highly compressed images. For the encoder comparison, we compress a set of 29 test images with two JPEG encoders (Adobe Photoshop and IrfanView) and three JPEG2000 encoders (JasPer, Kakadu, and IrfanView) at various compression ratios. We compute blockiness, blur, and MOS predictions as well as PSNR of the compressed images. Our results show that the IrfanView JPEG encoder produces consistently better images than the Adobe Photoshop JPEG encoder at the same data rate. The differences between the JPEG2000 encoders in our test are less pronounced; JasPer comes out as the best codec, closely followed by IrfanView and Kakadu. Comparing the JPEG- and JPEG2000-encoding quality of IrfanView, we find that JPEG has a slight edge at low compression ratios, while JPEG2000 is the clear winner at medium and high compression ratios.

Integration of radiographic images with an electronic medical record.

PubMed Central

Overhage, J. M.; Aisen, A.; Barnes, M.; Tucker, M.; McDonald, C. J.

2001-01-01

Radiographic images are important and expensive diagnostic tests. However, the provider caring for the patient often does not review the images directly due to time constraints. Institutions can use picture archiving and communications systems to make images more available to the provider, but this may not be the best solution. We integrated radiographic image review into the Regenstrief Medical Record System in order to address this problem. To achieve adequate performance, we store JPEG compressed images directly in the RMRS. Currently, physicians review about 5% of all radiographic studies using the RMRS image review function. PMID:11825241

Psychophysical Comparisons in Image Compression Algorithms.

DTIC Science & Technology

1999-03-01

Leister, M., "Lossy Lempel - Ziv Algorithm for Large Alphabet Sources and Applications to Image Compression ," IEEE Proceedings, v.I, pp. 225-228, September...1623-1642, September 1990. Sanford, M.A., An Analysis of Data Compression Algorithms used in the Transmission of Imagery, Master’s Thesis, Naval...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS PSYCHOPHYSICAL COMPARISONS IN IMAGE COMPRESSION ALGORITHMS by % Christopher J. Bodine • March

Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

PubMed

Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

2014-03-24

Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

Successful Treatment with Microvascular Decompression Surgery of a Patient with Hemiparesis Caused by Vertebral Artery Compression of the Medulla Oblongata: Case Report and Review of the Literature.

PubMed

Ren, Jibin; Sun, Hongtao; Diao, Yunfeng; Niu, Xuegang; Wang, Hang; Wei, Zhengjun; Yuan, Fei

2017-12-01

There are few reports on hemiparesis caused by vascular medullary compression, which can occur because of dolichoectasia of the vertebrobasilar arterial system. In this article, we report a case of vertebral artery compression of the medulla oblongata in a 67-year-old woman. The patient was hypertensive, and she developed hemiparesis and intermittent spasms over 5 years. These spasms had worsened during the last year. Cranial nerve magnetic resonance imaging showed compression of the medulla oblongata by the left vertebral artery. A motor evoked potential (MEP) examination showed abnormal conduction of MEPs of bilateral toe abductors. The patient underwent microvascular decompression surgery under general anesthesia through a retrosigmoid keyhole approach. This operation led to relief of vascular compression and symptomatic improvement. Our case suggests that detailed history, imaging studies, and electrophysiologic studies help lead to a correct and early diagnosis of hemiparesis caused by vascular compression of the rostral ventrolateral medulla. Microvascular decompression surgery improves patient symptoms, and intraoperative electrophysiologic monitoring helps to avoid injury to important adjacent nerves. Copyright © 2017 Elsevier Inc. All rights reserved.

Optical image encryption scheme with multiple light paths based on compressive ghost imaging

NASA Astrophysics Data System (ADS)

Zhu, Jinan; Yang, Xiulun; Meng, Xiangfeng; Wang, Yurong; Yin, Yongkai; Sun, Xiaowen; Dong, Guoyan

2018-02-01

An optical image encryption method with multiple light paths is proposed based on compressive ghost imaging. In the encryption process, M random phase-only masks (POMs) are generated by means of logistic map algorithm, and these masks are then uploaded to the spatial light modulator (SLM). The collimated laser light is divided into several beams by beam splitters as it passes through the SLM, and the light beams illuminate the secret images, which are converted into sparse images by discrete wavelet transform beforehand. Thus, the secret images are simultaneously encrypted into intensity vectors by ghost imaging. The distances between the SLM and secret images vary and can be used as the main keys with original POM and the logistic map algorithm coefficient in the decryption process. In the proposed method, the storage space can be significantly decreased and the security of the system can be improved. The feasibility, security and robustness of the method are further analysed through computer simulations.

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Adjustable lossless image compression based on a natural splitting of an image into drawing, shading, and fine-grained components

NASA Technical Reports Server (NTRS)

Novik, Dmitry A.; Tilton, James C.

1993-01-01

The compression, or efficient coding, of single band or multispectral still images is becoming an increasingly important topic. While lossy compression approaches can produce reconstructions that are visually close to the original, many scientific and engineering applications require exact (lossless) reconstructions. However, the most popular and efficient lossless compression techniques do not fully exploit the two-dimensional structural links existing in the image data. We describe here a general approach to lossless data compression that effectively exploits two-dimensional structural links of any length. After describing in detail two main variants on this scheme, we discuss experimental results.

JPEG2000 Image Compression on Solar EUV Images

NASA Astrophysics Data System (ADS)

Fischer, Catherine E.; Müller, Daniel; De Moortel, Ineke

2017-01-01

For future solar missions as well as ground-based telescopes, efficient ways to return and process data have become increasingly important. Solar Orbiter, which is the next ESA/NASA mission to explore the Sun and the heliosphere, is a deep-space mission, which implies a limited telemetry rate that makes efficient onboard data compression a necessity to achieve the mission science goals. Missions like the Solar Dynamics Observatory (SDO) and future ground-based telescopes such as the Daniel K. Inouye Solar Telescope, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New image compression standards address these challenges by implementing efficient and flexible compression algorithms that can be tailored to user requirements. We analyse solar images from the Atmospheric Imaging Assembly (AIA) instrument onboard SDO to study the effect of lossy JPEG2000 (from the Joint Photographic Experts Group 2000) image compression at different bitrates. To assess the quality of compressed images, we use the mean structural similarity (MSSIM) index as well as the widely used peak signal-to-noise ratio (PSNR) as metrics and compare the two in the context of solar EUV images. In addition, we perform tests to validate the scientific use of the lossily compressed images by analysing examples of an on-disc and off-limb coronal-loop oscillation time-series observed by AIA/SDO.

Tomographic Image Compression Using Multidimensional Transforms.

ERIC Educational Resources Information Center

Villasenor, John D.

1994-01-01

Describes a method for compressing tomographic images obtained using Positron Emission Tomography (PET) and Magnetic Resonance (MR) by applying transform compression using all available dimensions. This takes maximum advantage of redundancy of the data, allowing significant increases in compression efficiency and performance. (13 references) (KRN)

Telemedicine + OCT: toward design of optimized algorithms for high-quality compressed images

NASA Astrophysics Data System (ADS)

Mousavi, Mahta; Lurie, Kristen; Land, Julian; Javidi, Tara; Ellerbee, Audrey K.

2014-03-01

Telemedicine is an emerging technology that aims to provide clinical healthcare at a distance. Among its goals, the transfer of diagnostic images over telecommunication channels has been quite appealing to the medical community. When viewed as an adjunct to biomedical device hardware, one highly important consideration aside from the transfer rate and speed is the accuracy of the reconstructed image at the receiver end. Although optical coherence tomography (OCT) is an established imaging technique that is ripe for telemedicine, the effects of OCT data compression, which may be necessary on certain telemedicine platforms, have not received much attention in the literature. We investigate the performance and efficiency of several lossless and lossy compression techniques for OCT data and characterize their effectiveness with respect to achievable compression ratio, compression rate and preservation of image quality. We examine the effects of compression in the interferogram vs. A-scan domain as assessed with various objective and subjective metrics.

Observer performance assessment of JPEG-compressed high-resolution chest images

NASA Astrophysics Data System (ADS)

Good, Walter F.; Maitz, Glenn S.; King, Jill L.; Gennari, Rose C.; Gur, David

1999-05-01

The JPEG compression algorithm was tested on a set of 529 chest radiographs that had been digitized at a spatial resolution of 100 micrometer and contrast sensitivity of 12 bits. Images were compressed using five fixed 'psychovisual' quantization tables which produced average compression ratios in the range 15:1 to 61:1, and were then printed onto film. Six experienced radiologists read all cases from the laser printed film, in each of the five compressed modes as well as in the non-compressed mode. For comparison purposes, observers also read the same cases with reduced pixel resolutions of 200 micrometer and 400 micrometer. The specific task involved detecting masses, pneumothoraces, interstitial disease, alveolar infiltrates and rib fractures. Over the range of compression ratios tested, for images digitized at 100 micrometer, we were unable to demonstrate any statistically significant decrease (p greater than 0.05) in observer performance as measured by ROC techniques. However, the observers' subjective assessments of image quality did decrease significantly as image resolution was reduced and suggested a decreasing, but nonsignificant, trend as the compression ratio was increased. The seeming discrepancy between our failure to detect a reduction in observer performance, and other published studies, is likely due to: (1) the higher resolution at which we digitized our images; (2) the higher signal-to-noise ratio of our digitized films versus typical CR images; and (3) our particular choice of an optimized quantization scheme.

Image compression using singular value decomposition

NASA Astrophysics Data System (ADS)

Swathi, H. R.; Sohini, Shah; Surbhi; Gopichand, G.

2017-11-01

We often need to transmit and store the images in many applications. Smaller the image, less is the cost associated with transmission and storage. So we often need to apply data compression techniques to reduce the storage space consumed by the image. One approach is to apply Singular Value Decomposition (SVD) on the image matrix. In this method, digital image is given to SVD. SVD refactors the given digital image into three matrices. Singular values are used to refactor the image and at the end of this process, image is represented with smaller set of values, hence reducing the storage space required by the image. Goal here is to achieve the image compression while preserving the important features which describe the original image. SVD can be adapted to any arbitrary, square, reversible and non-reversible matrix of m × n size. Compression ratio and Mean Square Error is used as performance metrics.

Watermarking of ultrasound medical images in teleradiology using compressed watermark

PubMed Central

Badshah, Gran; Liew, Siau-Chuin; Zain, Jasni Mohamad; Ali, Mushtaq

2016-01-01

Abstract. The open accessibility of Internet-based medical images in teleradialogy face security threats due to the nonsecured communication media. This paper discusses the spatial domain watermarking of ultrasound medical images for content authentication, tamper detection, and lossless recovery. For this purpose, the image is divided into two main parts, the region of interest (ROI) and region of noninterest (RONI). The defined ROI and its hash value are combined as watermark, lossless compressed, and embedded into the RONI part of images at pixel’s least significant bits (LSBs). The watermark lossless compression and embedding at pixel’s LSBs preserve image diagnostic and perceptual qualities. Different lossless compression techniques including Lempel-Ziv-Welch (LZW) were tested for watermark compression. The performances of these techniques were compared based on more bit reduction and compression ratio. LZW was found better than others and used in tamper detection and recovery watermarking of medical images (TDARWMI) scheme development to be used for ROI authentication, tamper detection, localization, and lossless recovery. TDARWMI performance was compared and found to be better than other watermarking schemes. PMID:26839914

Compressed Sensing Techniques Applied to Ultrasonic Imaging of Cargo Containers.

PubMed

López, Yuri Álvarez; Lorenzo, José Ángel Martínez

2017-01-15

One of the key issues in the fight against the smuggling of goods has been the development of scanners for cargo inspection. X-ray-based radiographic system scanners are the most developed sensing modality. However, they are costly and use bulky sources that emit hazardous, ionizing radiation. Aiming to improve the probability of threat detection, an ultrasonic-based technique, capable of detecting the footprint of metallic containers or compartments concealed within the metallic structure of the inspected cargo, has been proposed. The system consists of an array of acoustic transceivers that is attached to the metallic structure-under-inspection, creating a guided acoustic Lamb wave. Reflections due to discontinuities are detected in the images, provided by an imaging algorithm. Taking into consideration that the majority of those images are sparse, this contribution analyzes the application of Compressed Sensing (CS) techniques in order to reduce the amount of measurements needed, thus achieving faster scanning, without compromising the detection capabilities of the system. A parametric study of the image quality, as a function of the samples needed in spatial and frequency domains, is presented, as well as the dependence on the sampling pattern. For this purpose, realistic cargo inspection scenarios have been simulated.

Compressed Sensing Techniques Applied to Ultrasonic Imaging of Cargo Containers

PubMed Central

Álvarez López, Yuri; Martínez Lorenzo, José Ángel

2017-01-01

One of the key issues in the fight against the smuggling of goods has been the development of scanners for cargo inspection. X-ray-based radiographic system scanners are the most developed sensing modality. However, they are costly and use bulky sources that emit hazardous, ionizing radiation. Aiming to improve the probability of threat detection, an ultrasonic-based technique, capable of detecting the footprint of metallic containers or compartments concealed within the metallic structure of the inspected cargo, has been proposed. The system consists of an array of acoustic transceivers that is attached to the metallic structure-under-inspection, creating a guided acoustic Lamb wave. Reflections due to discontinuities are detected in the images, provided by an imaging algorithm. Taking into consideration that the majority of those images are sparse, this contribution analyzes the application of Compressed Sensing (CS) techniques in order to reduce the amount of measurements needed, thus achieving faster scanning, without compromising the detection capabilities of the system. A parametric study of the image quality, as a function of the samples needed in spatial and frequency domains, is presented, as well as the dependence on the sampling pattern. For this purpose, realistic cargo inspection scenarios have been simulated. PMID:28098841

Acceptable bit-rates for human face identification from CCTV imagery

NASA Astrophysics Data System (ADS)

Tsifouti, Anastasia; Triantaphillidou, Sophie; Bilissi, Efthimia; Larabi, Mohamed-Chaker

2013-01-01

The objective of this investigation is to produce recommendations for acceptable bit-rates of CCTV footage of people onboard London buses. The majority of CCTV recorders on buses use a proprietary format based on the H.264/AVC video coding standard, exploiting both spatial and temporal redundancy. Low bit-rates are favored in the CCTV industry but they compromise the image usefulness of the recorded imagery. In this context usefulness is defined by the presence of enough facial information remaining in the compressed image to allow a specialist to identify a person. The investigation includes four steps: 1) Collection of representative video footage. 2) The grouping of video scenes based on content attributes. 3) Psychophysical investigations to identify key scenes, which are most affected by compression. 4) Testing of recording systems using the key scenes and further psychophysical investigations. The results are highly dependent upon scene content. For example, very dark and very bright scenes were the most challenging to compress, requiring higher bit-rates to maintain useful information. The acceptable bit-rates are also found to be dependent upon the specific CCTV system used to compress the footage, presenting challenges in drawing conclusions about universal `average' bit-rates.

Development and evaluation of a device for simultaneous uniaxial compression and optical imaging of cartilage samples in vitro

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steinert, Marian; Kratz, Marita; Jones, David B.

2014-10-15

In this paper, we present a system that allows imaging of cartilage tissue via optical coherence tomography (OCT) during controlled uniaxial unconfined compression of cylindrical osteochondral cores in vitro. We describe the system design and conduct a static and dynamic performance analysis. While reference measurements yield a full scale maximum deviation of 0.14% in displacement, force can be measured with a full scale standard deviation of 1.4%. The dynamic performance evaluation indicates a high accuracy in force controlled mode up to 25 Hz, but it also reveals a strong effect of variance of sample mechanical properties on the tracking performancemore » under displacement control. In order to counterbalance these disturbances, an adaptive feed forward approach was applied which finally resulted in an improved displacement tracking accuracy up to 3 Hz. A built-in imaging probe allows on-line monitoring of the sample via OCT while being loaded in the cultivation chamber. We show that cartilage topology and defects in the tissue can be observed and demonstrate the visualization of the compression process during static mechanical loading.« less

Comparative Study Of Image Enhancement Algorithms For Digital And Film Mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Delgado-Gonzalez, A.; Sanmiguel, R. E.

2008-08-11

Here we discuss the application of edge enhancement algorithms on images obtained with a Mammography System which has a Selenium Detector and on the other hand, on images obtained from digitized film mammography. Comparative analysis of such images includes the study of technical aspects of image acquisition, storage, compression and display. A protocol for a local database has been created as a result of this study.

Optical image cryptosystem using chaotic phase-amplitude masks encoding and least-data-driven decryption by compressive sensing

NASA Astrophysics Data System (ADS)

Lang, Jun; Zhang, Jing

2015-03-01

In our proposed optical image cryptosystem, two pairs of phase-amplitude masks are generated from the chaotic web map for image encryption in the 4f double random phase-amplitude encoding (DRPAE) system. Instead of transmitting the real keys and the enormous masks codes, only a few observed measurements intermittently chosen from the masks are delivered. Based on compressive sensing paradigm, we suitably refine the series expansions of web map equations to better reconstruct the underlying system. The parameters of the chaotic equations can be successfully calculated from observed measurements and then can be used to regenerate the correct random phase-amplitude masks for decrypting the encoded information. Numerical simulations have been performed to verify the proposed optical image cryptosystem. This cryptosystem can provide a new key management and distribution method. It has the advantages of sufficiently low occupation of the transmitted key codes and security improvement of information transmission without sending the real keys.

Measurements of spatially resolved velocity variations in shock compressed heterogeneous materials using a line-imaging velocity interferometer

NASA Astrophysics Data System (ADS)

Trott, Wayne M.; Knudson, Marcus D.; Chhabildas, Lalit C.; Asay, James R.

2000-04-01

Relatively straightforward changes in the design of a conventional optically recording velocity interferometer system (ORVIS) can be used to produce a line-imaging instrument that allows adjustment of spatial resolution over a wide range. As a result, line-imaging ORVIS can be tailored to various specific applications involving dynamic deformation of heterogeneous materials as required by their characteristic length scales (ranging from a few μm for ferroelectric ceramics to a few mm for concrete). A line-imaging system has been successfully interfaced to a compressed gas gun driver and fielded on numerous tests in combination with simultaneous dual delay-leg, "push-pull" VISAR measurements. These tests include shock loading of glass-reinforced polyester composites, foam reverberation experiments (measurements at the free surface of a thin aluminum plate impacted by foam), and measurements of dispersive velocity in a shock-loaded explosive simulant (sugar). Results are presented that illustrate the capability for recording detailed spatially resolved material response.

Binary video codec for data reduction in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Khursheed, Khursheed; Ahmad, Naeem; Imran, Muhammad; O'Nils, Mattias

2013-02-01

Wireless Visual Sensor Networks (WVSN) is formed by deploying many Visual Sensor Nodes (VSNs) in the field. Typical applications of WVSN include environmental monitoring, health care, industrial process monitoring, stadium/airports monitoring for security reasons and many more. The energy budget in the outdoor applications of WVSN is limited to the batteries and the frequent replacement of batteries is usually not desirable. So the processing as well as the communication energy consumption of the VSN needs to be optimized in such a way that the network remains functional for longer duration. The images captured by VSN contain huge amount of data and require efficient computational resources for processing the images and wide communication bandwidth for the transmission of the results. Image processing algorithms must be designed and developed in such a way that they are computationally less complex and must provide high compression rate. For some applications of WVSN, the captured images can be segmented into bi-level images and hence bi-level image coding methods will efficiently reduce the information amount in these segmented images. But the compression rate of the bi-level image coding methods is limited by the underlined compression algorithm. Hence there is a need for designing other intelligent and efficient algorithms which are computationally less complex and provide better compression rate than that of bi-level image coding methods. Change coding is one such algorithm which is computationally less complex (require only exclusive OR operations) and provide better compression efficiency compared to image coding but it is effective for applications having slight changes between adjacent frames of the video. The detection and coding of the Region of Interest (ROIs) in the change frame efficiently reduce the information amount in the change frame. But, if the number of objects in the change frames is higher than a certain level then the compression efficiency of both the change coding and ROI coding becomes worse than that of image coding. This paper explores the compression efficiency of the Binary Video Codec (BVC) for the data reduction in WVSN. We proposed to implement all the three compression techniques i.e. image coding, change coding and ROI coding at the VSN and then select the smallest bit stream among the results of the three compression techniques. In this way the compression performance of the BVC will never become worse than that of image coding. We concluded that the compression efficiency of BVC is always better than that of change coding and is always better than or equal that of ROI coding and image coding.

Shock Compression Induced Hot Spots in Energetic Material Detected by Thermal Imaging Microscopy

NASA Astrophysics Data System (ADS)

Chen, Ming-Wei; Dlott, Dana

2014-06-01

The chemical reaction of powder energetic material is of great interest in energy and pyrotechnic applications since the high reaction temperature. Under the shock compression, the chemical reaction appears in the sub-microsecond to microsecond time scale, and releases a large amount of energy. Experimental and theoretical research progresses have been made in the past decade, in order to characterize the process under the shock compression. However, the knowledge of energy release and temperature change of this procedure is still limited, due to the difficulties of detecting technologies. We have constructed a thermal imaging microscopy apparatus, and studied the temperature change in energetic materials under the long-wavelength infrared (LWIR) and ultrasound exposure. Additionally, the real-time detection of the localized heating and energy concentration in composite material is capable with our thermal imaging microscopy apparatus. Recently, this apparatus is combined with our laser driven flyer plate system to provide a lab-scale source of shock compression to energetic material. A fast temperature increase of thermite particulars induced by the shock compression is directly observed by thermal imaging with 15-20 μm spatial resolution. Temperature change during the shock loading is evaluated to be at the order of 10^9K/s, through the direct measurement of mid-wavelength infrared (MWIR) emission intensity change. We observe preliminary results to confirm the hot spots appear with shock compression on energetic crystals, and will discuss the data and analysis in further detail. M.-W. Chen, S. You, K. S. Suslick, and D. D. Dlott, {Rev. Sci. Instr., 85, 023705 (2014) M.-W. Chen, S. You, K. S. Suslick, and D. D. Dlott, {Appl. Phys. Lett., 104, 061907 (2014)} K. E. Brown, W. L. Shaw, X. Zheng, and D. D. Dlott, {Rev. Sci. Instr., 83, 103901 (2012)}

An Efficient, Lossless Database for Storing and Transmitting Medical Images

NASA Technical Reports Server (NTRS)

Fenstermacher, Marc J.

1998-01-01

This research aimed in creating new compression methods based on the central idea of Set Redundancy Compression (SRC). Set Redundancy refers to the common information that exists in a set of similar images. SRC compression methods take advantage of this common information and can achieve improved compression of similar images by reducing their Set Redundancy. The current research resulted in the development of three new lossless SRC compression methods: MARS (Median-Aided Region Sorting), MAZE (Max-Aided Zero Elimination) and MaxGBA (Max-Guided Bit Allocation).

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

A System for Compressive Spectral and Polarization Imaging at Short Wave Infrared (SWIR) Wavelengths

DTIC Science & Technology

2017-10-18

2016). H. Rueda, H. Arguello and G. R. Arce, “DMD-based implementation of patterned optical filter arrays for compressive spectral imaging”, Journal...3)  a  set  of   optical   filters  which   allow   to   discriminate   spectrally   the   coded   and   sheared...system   that   includes   objective   lens,   spatial   light   modulator,   dispersive   element,   optical   filters

Integer cosine transform compression for Galileo at Jupiter: A preliminary look

NASA Technical Reports Server (NTRS)

Ekroot, L.; Dolinar, S.; Cheung, K.-M.

1993-01-01

The Galileo low-gain antenna mission has a severely rate-constrained channel over which we wish to send large amounts of information. Because of this link pressure, compression techniques for image and other data are being selected. The compression technique that will be used for images is the integer cosine transform (ICT). This article investigates the compression performance of Galileo's ICT algorithm as applied to Galileo images taken during the early portion of the mission and to images that simulate those expected from the encounter at Jupiter.

A High Performance Image Data Compression Technique for Space Applications

NASA Technical Reports Server (NTRS)

Yeh, Pen-Shu; Venbrux, Jack

2003-01-01

A highly performing image data compression technique is currently being developed for space science applications under the requirement of high-speed and pushbroom scanning. The technique is also applicable to frame based imaging data. The algorithm combines a two-dimensional transform with a bitplane encoding; this results in an embedded bit string with exact desirable compression rate specified by the user. The compression scheme performs well on a suite of test images acquired from spacecraft instruments. It can also be applied to three-dimensional data cube resulting from hyper-spectral imaging instrument. Flight qualifiable hardware implementations are in development. The implementation is being designed to compress data in excess of 20 Msampledsec and support quantization from 2 to 16 bits. This paper presents the algorithm, its applications and status of development.

Comparison of lossless compression techniques for prepress color images

NASA Astrophysics Data System (ADS)

Van Assche, Steven; Denecker, Koen N.; Philips, Wilfried R.; Lemahieu, Ignace L.

1998-12-01

In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. In this paper we present a comparison of three state-of-the-art lossless compression techniques which exploit such color redundancies: IEP (Inter- color Error Prediction) and a KLT-based technique, which are both linear color decorrelation techniques, and Interframe CALIC, which uses a non-linear approach to color decorrelation. It is shown that these techniques are able to exploit color redundancies and that color decorrelation can be done effectively and efficiently. The linear color decorrelators provide a considerable coding gain (about 2 bpp) on some typical prepress images. The non-linear interframe CALIC predictor does not yield better results, but the full interframe CALIC technique does.

Study on the key technology of optical encryption based on compressive ghost imaging with double random-phase encoding

NASA Astrophysics Data System (ADS)

Zhang, Leihong; Pan, Zilan; Liang, Dong; Ma, Xiuhua; Zhang, Dawei

2015-12-01

An optical encryption method based on compressive ghost imaging (CGI) with double random-phase encoding (DRPE), named DRPE-CGI, is proposed. The information is first encrypted by the sender with DRPE, the DRPE-coded image is encrypted by the system of computational ghost imaging with a secret key. The key of N random-phase vectors is generated by the sender and will be shared with the receiver who is the authorized user. The receiver decrypts the DRPE-coded image with the key, with the aid of CGI and a compressive sensing technique, and then reconstructs the original information by the technique of DRPE-decoding. The experiments suggest that cryptanalysts cannot get any useful information about the original image even if they eavesdrop 60% of the key at a given time, so the security of DRPE-CGI is higher than that of the security of conventional ghost imaging. Furthermore, this method can reduce 40% of the information quantity compared with ghost imaging while the qualities of reconstructing the information are the same. It can also improve the quality of the reconstructed plaintext information compared with DRPE-GI with the same sampling times. This technique can be immediately applied to encryption and data storage with the advantages of high security, fast transmission, and high quality of reconstructed information.

An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

PubMed

Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values.

An Object-Oriented Simulator for 3D Digital Breast Tomosynthesis Imaging System

PubMed Central

Cengiz, Kubra

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

Low Complexity Compression and Speed Enhancement for Optical Scanning Holography

PubMed Central

Tsang, P. W. M.; Poon, T.-C.; Liu, J.-P.; Kim, T.; Kim, Y. S.

2016-01-01

In this paper we report a low complexity compression method that is suitable for compact optical scanning holography (OSH) systems with different optical settings. Our proposed method can be divided into 2 major parts. First, an automatic decision maker is applied to select the rows of holographic pixels to be scanned. This process enhances the speed of acquiring a hologram, and also lowers the data rate. Second, each row of down-sampled pixels is converted into a one-bit representation with delta modulation (DM). Existing DM-based hologram compression techniques suffers from the disadvantage that a core parameter, commonly known as the step size, has to be determined in advance. However, the correct value of the step size for compressing each row of hologram is dependent on the dynamic range of the pixels, which could deviate significantly with the object scene, as well as OSH systems with different opical settings. We have overcome this problem by incorporating a dynamic step-size adjustment scheme. The proposed method is applied in the compression of holograms that are acquired with 2 different OSH systems, demonstrating a compression ratio of over two orders of magnitude, while preserving favorable fidelity on the reconstructed images. PMID:27708410

High-speed railway signal trackside equipment patrol inspection system

NASA Astrophysics Data System (ADS)

Wu, Nan

2018-03-01

High-speed railway signal trackside equipment patrol inspection system comprehensively applies TDI (time delay integration), high-speed and highly responsive CMOS architecture, low illumination photosensitive technique, image data compression technique, machine vision technique and so on, installed on high-speed railway inspection train, and achieves the collection, management and analysis of the images of signal trackside equipment appearance while the train is running. The system will automatically filter out the signal trackside equipment images from a large number of the background image, and identify of the equipment changes by comparing the original image data. Combining with ledger data and train location information, the system accurately locate the trackside equipment, conscientiously guiding maintenance.

A generalized Benford's law for JPEG coefficients and its applications in image forensics

NASA Astrophysics Data System (ADS)

Fu, Dongdong; Shi, Yun Q.; Su, Wei

2007-02-01

In this paper, a novel statistical model based on Benford's law for the probability distributions of the first digits of the block-DCT and quantized JPEG coefficients is presented. A parametric logarithmic law, i.e., the generalized Benford's law, is formulated. Furthermore, some potential applications of this model in image forensics are discussed in this paper, which include the detection of JPEG compression for images in bitmap format, the estimation of JPEG compression Qfactor for JPEG compressed bitmap image, and the detection of double compressed JPEG image. The results of our extensive experiments demonstrate the effectiveness of the proposed statistical model.

Data compression for satellite images

NASA Technical Reports Server (NTRS)

Chen, P. H.; Wintz, P. A.

1976-01-01

An efficient data compression system is presented for satellite pictures and two grey level pictures derived from satellite pictures. The compression techniques take advantages of the correlation between adjacent picture elements. Several source coding methods are investigated. Double delta coding is presented and shown to be the most efficient. Both predictive differential quantizing technique and double delta coding can be significantly improved by applying a background skipping technique. An extension code is constructed. This code requires very little storage space and operates efficiently. Simulation results are presented for various coding schemes and source codes.

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images.

PubMed

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-07-21

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

Photoacoustic Image Analysis for Cancer Detection and Building a Novel Ultrasound Imaging System

NASA Astrophysics Data System (ADS)

Sinha, Saugata

Photoacoustic (PA) imaging is a rapidly emerging non-invasive soft tissue imaging modality which has the potential to detect tissue abnormality at early stage. Photoacoustic images map the spatially varying optical absorption property of tissue. In multiwavelength photoacoustic imaging, the soft tissue is imaged with different wavelengths, tuned to the absorption peaks of the specific light absorbing tissue constituents or chromophores to obtain images with different contrasts of the same tissue sample. From those images, spatially varying concentration of the chromophores can be recovered. As multiwavelength PA images can provide important physiological information related to function and molecular composition of the tissue, so they can be used for diagnosis of cancer lesions and differentiation of malignant tumors from benign tumors. In this research, a number of parameters have been extracted from multiwavelength 3D PA images of freshly excised human prostate and thyroid specimens, imaged at five different wavelengths. Using marked histology slides as ground truths, region of interests (ROI) corresponding to cancer, benign and normal regions have been identified in the PA images. The extracted parameters belong to different categories namely chromophore concentration, frequency parameters and PA image pixels and they represent different physiological and optical properties of the tissue specimens. Statistical analysis has been performed to test whether the extracted parameters are significantly different between cancer, benign and normal regions. A multidimensional [29 dimensional] feature set, built with the extracted parameters from the 3D PA images, has been divided randomly into training and testing sets. The training set has been used to train support vector machine (SVM) and neural network (NN) classifiers while the performance of the classifiers in differentiating different tissue pathologies have been determined by the testing dataset. Using the NN classifier, performance of parameters belonging to different categories in differentiating malignant tissue from nonmalignant tissue has been determined. It has been found that, among different categories, the frequency parameters performed best in differentiating malignant from nonmalignant tissue [sensitivity and specificity with testing dataset are 85% and 84%] while performance of all the categories combined was better than that [sensitivity and specificity with testing dataset are 93% and 91%]. However, PA imaging cannot be used to provide the anatomical cues required to determine the position of the detected or suspected malignant tumor region relative to familiar organ landmarks. On the other hand, although accuracy of Ultrasound (US) imaging in detecting cancer lesions is low, major anatomical cues like organ boundaries or presence of nearby major organs are visible in US images. A dual mode PA and US imaging system can potentially detect as well as localize cancer lesions with high accuracy. In this study, we have developed a novel pulse echo US imaging system which can be easily integrated with our existing ex-vivo PA imaging system to produce the dual mode imaging system. Here a Polyvinylidene fluoride (PVDF) film has been used as US transmitter. To improve the anticipated low signal to noise ratio (SNR) of the received US signal due to the low electromechanical coupling coefficient of the PVDF film, we implemented pulse compression technique using chirp signals. Comparisons among the different SNR values obtained with short pulse and after pulse compression with chirp signal show a clear improvement of the SNR for the compressed pulse. The axial resolution of the imaging system improved with increasing sweep bandwidth of input chirp signals, whereas the lateral resolution remained almost constant. This work demonstrates the feasibility of using a PVDF film transducer as an US transmitter and implementing pulse compression technique in an acoustic lens focusing based imaging system.

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Nonlinear pulse compression in pulse-inversion fundamental imaging.

PubMed

Cheng, Yun-Chien; Shen, Che-Chou; Li, Pai-Chi

2007-04-01

Coded excitation can be applied in ultrasound contrast agent imaging to enhance the signal-to-noise ratio with minimal destruction of the microbubbles. Although the axial resolution is usually compromised by the requirement for a long coded transmit waveforms, this can be restored by using a compression filter to compress the received echo. However, nonlinear responses from microbubbles may cause difficulties in pulse compression and result in severe range side-lobe artifacts, particularly in pulse-inversion-based (PI) fundamental imaging. The efficacy of pulse compression in nonlinear contrast imaging was evaluated by investigating several factors relevant to PI fundamental generation using both in-vitro experiments and simulations. The results indicate that the acoustic pressure and the bubble size can alter the nonlinear characteristics of microbubbles and change the performance of the compression filter. When nonlinear responses from contrast agents are enhanced by using a higher acoustic pressure or when more microbubbles are near the resonance size of the transmit frequency, higher range side lobes are produced in both linear imaging and PI fundamental imaging. On the other hand, contrast detection in PI fundamental imaging significantly depends on the magnitude of the nonlinear responses of the bubbles and thus the resultant contrast-to-tissue ratio (CTR) still increases with acoustic pressure and the nonlinear resonance of microbubbles. It should be noted, however, that the CTR in PI fundamental imaging after compression is consistently lower than that before compression due to obvious side-lobe artifacts. Therefore, the use of coded excitation is not beneficial in PI fundamental contrast detection.

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

NASA Technical Reports Server (NTRS)

Jaggi, S.

1993-01-01

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression

NASA Astrophysics Data System (ADS)

Daly, Scott J.

1989-08-01

The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.

Characterization of Diesel and Gasoline Compression Ignition Combustion in a Rapid Compression-Expansion Machine using OH* Chemiluminescence Imaging

NASA Astrophysics Data System (ADS)

Krishnan, Sundar Rajan; Srinivasan, Kalyan Kumar; Stegmeir, Matthew

2015-11-01

Direct-injection compression ignition combustion of diesel and gasoline were studied in a rapid compression-expansion machine (RCEM) using high-speed OH* chemiluminescence imaging. The RCEM (bore = 84 mm, stroke = 110-250 mm) was used to simulate engine-like operating conditions at the start of fuel injection. The fuels were supplied by a high-pressure fuel cart with an air-over-fuel pressure amplification system capable of providing fuel injection pressures up to 2000 bar. A production diesel fuel injector was modified to provide a single fuel spray for both diesel and gasoline operation. Time-resolved combustion pressure in the RCEM was measured using a Kistler piezoelectric pressure transducer mounted on the cylinder head and the instantaneous piston displacement was measured using an inductive linear displacement sensor (0.05 mm resolution). Time-resolved, line-of-sight OH* chemiluminescence images were obtained using a Phantom V611 CMOS camera (20.9 kHz @ 512 x 512 pixel resolution, ~ 48 μs time resolution) coupled with a short wave pass filter (cut-off ~ 348 nm). The instantaneous OH* distributions, which indicate high temperature flame regions within the combustion chamber, were used to discern the characteristic differences between diesel and gasoline compression ignition combustion. The authors gratefully acknowledge facilities support for the present work from the Energy Institute at Mississippi State University.

Polarimetric and Indoor Imaging Fusion Based on Compressive Sensing

DTIC Science & Technology

2013-04-01

Signal Process., vol. 57, no. 6, pp. 2275-2284, 2009. [20] A. Gurbuz, J. McClellan, and W. Scott, Jr., "Compressive sensing for subsurface imaging using...SciTech Publishing, 2010, pp. 922- 938. [45] A. C. Gurbuz, J. H. McClellan, and W. R. Scott, Jr., "Compressive sensing for subsurface imaging using

Compression of high-density EMG signals for trapezius and gastrocnemius muscles.

PubMed

Itiki, Cinthia; Furuie, Sergio S; Merletti, Roberto

2014-03-10

New technologies for data transmission and multi-electrode arrays increased the demand for compressing high-density electromyography (HD EMG) signals. This article aims the compression of HD EMG signals recorded by two-dimensional electrode matrices at different muscle-contraction forces. It also shows methodological aspects of compressing HD EMG signals for non-pinnate (upper trapezius) and pinnate (medial gastrocnemius) muscles, using image compression techniques. HD EMG signals were placed in image rows, according to two distinct electrode orders: parallel and perpendicular to the muscle longitudinal axis. For the lossless case, the images obtained from single-differential signals as well as their differences in time were compressed. For the lossy algorithm, the images associated to the recorded monopolar or single-differential signals were compressed for different compression levels. Lossless compression provided up to 59.3% file-size reduction (FSR), with lower contraction forces associated to higher FSR. For lossy compression, a 90.8% reduction on the file size was attained, while keeping the signal-to-noise ratio (SNR) at 21.19 dB. For a similar FSR, higher contraction forces corresponded to higher SNR CONCLUSIONS: The computation of signal differences in time improves the performance of lossless compression while the selection of signals in the transversal order improves the lossy compression of HD EMG, for both pinnate and non-pinnate muscles.

Compression of high-density EMG signals for trapezius and gastrocnemius muscles

PubMed Central

2014-01-01

Background New technologies for data transmission and multi-electrode arrays increased the demand for compressing high-density electromyography (HD EMG) signals. This article aims the compression of HD EMG signals recorded by two-dimensional electrode matrices at different muscle-contraction forces. It also shows methodological aspects of compressing HD EMG signals for non-pinnate (upper trapezius) and pinnate (medial gastrocnemius) muscles, using image compression techniques. Methods HD EMG signals were placed in image rows, according to two distinct electrode orders: parallel and perpendicular to the muscle longitudinal axis. For the lossless case, the images obtained from single-differential signals as well as their differences in time were compressed. For the lossy algorithm, the images associated to the recorded monopolar or single-differential signals were compressed for different compression levels. Results Lossless compression provided up to 59.3% file-size reduction (FSR), with lower contraction forces associated to higher FSR. For lossy compression, a 90.8% reduction on the file size was attained, while keeping the signal-to-noise ratio (SNR) at 21.19 dB. For a similar FSR, higher contraction forces corresponded to higher SNR Conclusions The computation of signal differences in time improves the performance of lossless compression while the selection of signals in the transversal order improves the lossy compression of HD EMG, for both pinnate and non-pinnate muscles. PMID:24612604

A comparison of spectral decorrelation techniques and performance evaluation metrics for a wavelet-based, multispectral data compression algorithm

NASA Technical Reports Server (NTRS)

Matic, Roy M.; Mosley, Judith I.

1994-01-01

Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.

JPEG2000 and dissemination of cultural heritage over the Internet.

PubMed

Politou, Eugenia A; Pavlidis, George P; Chamzas, Christodoulos

2004-03-01

By applying the latest technologies in image compression for managing the storage of massive image data within cultural heritage databases and by exploiting the universality of the Internet we are now able not only to effectively digitize, record and preserve, but also to promote the dissemination of cultural heritage. In this work we present an application of the latest image compression standard JPEG2000 in managing and browsing image databases, focusing on the image transmission aspect rather than database management and indexing. We combine the technologies of JPEG2000 image compression with client-server socket connections and client browser plug-in, as to provide with an all-in-one package for remote browsing of JPEG2000 compressed image databases, suitable for the effective dissemination of cultural heritage.

An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT).

PubMed

Li, Ran; Duan, Xiaomeng; Li, Xu; He, Wei; Li, Yanling

2018-04-17

Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.

Wavelet compression of noisy tomographic images

NASA Astrophysics Data System (ADS)

Kappeler, Christian; Mueller, Stefan P.

1995-09-01

3D data acquisition is increasingly used in positron emission tomography (PET) to collect a larger fraction of the emitted radiation. A major practical difficulty with data storage and transmission in 3D-PET is the large size of the data sets. A typical dynamic study contains about 200 Mbyte of data. PET images inherently have a high level of photon noise and therefore usually are evaluated after being processed by a smoothing filter. In this work we examined lossy compression schemes under the postulate not induce image modifications exceeding those resulting from low pass filtering. The standard we will refer to is the Hanning filter. Resolution and inhomogeneity serve as figures of merit for quantification of image quality. The images to be compressed are transformed to a wavelet representation using Daubechies12 wavelets and compressed after filtering by thresholding. We do not include further compression by quantization and coding here. Achievable compression factors at this level of processing are thirty to fifty.

Implementation of a compressive sampling scheme for wireless sensors to achieve energy efficiency in a structural health monitoring system

NASA Astrophysics Data System (ADS)

O'Connor, Sean M.; Lynch, Jerome P.; Gilbert, Anna C.

2013-04-01

Wireless sensors have emerged to offer low-cost sensors with impressive functionality (e.g., data acquisition, computing, and communication) and modular installations. Such advantages enable higher nodal densities than tethered systems resulting in increased spatial resolution of the monitoring system. However, high nodal density comes at a cost as huge amounts of data are generated, weighing heavy on power sources, transmission bandwidth, and data management requirements, often making data compression necessary. The traditional compression paradigm consists of high rate (>Nyquist) uniform sampling and storage of the entire target signal followed by some desired compression scheme prior to transmission. The recently proposed compressed sensing (CS) framework combines the acquisition and compression stage together, thus removing the need for storage and operation of the full target signal prior to transmission. The effectiveness of the CS approach hinges on the presence of a sparse representation of the target signal in a known basis, similarly exploited by several traditional compressive sensing applications today (e.g., imaging, MRI). Field implementations of CS schemes in wireless SHM systems have been challenging due to the lack of commercially available sensing units capable of sampling methods (e.g., random) consistent with the compressed sensing framework, often moving evaluation of CS techniques to simulation and post-processing. The research presented here describes implementation of a CS sampling scheme to the Narada wireless sensing node and the energy efficiencies observed in the deployed sensors. Of interest in this study is the compressibility of acceleration response signals collected from a multi-girder steel-concrete composite bridge. The study shows the benefit of CS in reducing data requirements while ensuring data analysis on compressed data remain accurate.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

Design of UAV high resolution image transmission system

NASA Astrophysics Data System (ADS)

Gao, Qiang; Ji, Ming; Pang, Lan; Jiang, Wen-tao; Fan, Pengcheng; Zhang, Xingcheng

2017-02-01

In order to solve the problem of the bandwidth limitation of the image transmission system on UAV, a scheme with image compression technology for mini UAV is proposed, based on the requirements of High-definition image transmission system of UAV. The video codec standard H.264 coding module and key technology was analyzed and studied for UAV area video communication. Based on the research of high-resolution image encoding and decoding technique and wireless transmit method, The high-resolution image transmission system was designed on architecture of Android and video codec chip; the constructed system was confirmed by experimentation in laboratory, the bit-rate could be controlled easily, QoS is stable, the low latency could meets most applied requirement not only for military use but also for industrial applications.

Temporal Coding of Volumetric Imagery

NASA Astrophysics Data System (ADS)

Llull, Patrick Ryan

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption. This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications. Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level. Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions. Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z ) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke. Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

[The compression and storage of enhanced external counterpulsation waveform based on DICOM standard].

PubMed

Hu, Ding; Xie, Shuqun; Yu, Donglan; Zheng, Zhensheng; Wang, Kuijian

2010-04-01

The development of external counterpulsation (ECP) local area network system and extensible markup language (XML)-based remote ECP medical information system conformable to digital imaging and communications in medicine (DICOM) standard has been improving the digital interchangeablity and sharability of ECP data. However, the therapy process of ECP is a continuous and longtime supervision which builds a mass of waveform data. In order to reduce the storage space and improve the transmission efficiency, the waveform data with the normative format of ECP data files have to be compressed. In this article, we introduced the compression arithmetic of template matching and improved quick fitting of linear approximation distance thresholding (LADT) in combimation with the characters of enhanced external counterpulsation (EECP) waveform signal. The DICOM standard is used as the storage and transmission standard to make our system compatible with hospital information system. According to the rules of transfer syntaxes, we defined private transfer syntax for one-dimensional compressed waveform data and stored EECP data into a DICOM file. Testing result indicates that the compressed and normative data can be correctly transmitted and displayed between EECP workstations in our EECP laboratory.

Quantization Distortion in Block Transform-Compressed Data

NASA Technical Reports Server (NTRS)

Boden, A. F.

1995-01-01

The popular JPEG image compression standard is an example of a block transform-based compression scheme; the image is systematically subdivided into block that are individually transformed, quantized, and encoded. The compression is achieved by quantizing the transformed data, reducing the data entropy and thus facilitating efficient encoding. A generic block transform model is introduced.

Dental cone-beam CT reconstruction from limited-angle view data based on compressed-sensing (CS) theory for fast, low-dose X-ray imaging

NASA Astrophysics Data System (ADS)

Je, Uikyu; Cho, Hyosung; Lee, Minsik; Oh, Jieun; Park, Yeonok; Hong, Daeki; Park, Cheulkyu; Cho, Heemoon; Choi, Sungil; Koo, Yangseo

2014-06-01

Recently, reducing radiation doses has become an issue of critical importance in the broader radiological community. As a possible technical approach, especially, in dental cone-beam computed tomography (CBCT), reconstruction from limited-angle view data (< 360°) would enable fast scanning with reduced doses to the patient. In this study, we investigated and implemented an efficient reconstruction algorithm based on compressed-sensing (CS) theory for the scan geometry and performed systematic simulation works to investigate the image characteristics. We also performed experimental works by applying the algorithm to a commercially-available dental CBCT system to demonstrate its effectiveness for image reconstruction in incomplete data problems. We successfully reconstructed CBCT images with incomplete projections acquired at selected scan angles of 120, 150, 180, and 200° with a fixed angle step of 1.2° and evaluated the reconstruction quality quantitatively. Both simulation and experimental demonstrations of the CS-based reconstruction from limited-angle view data show that the algorithm can be applied directly to current dental CBCT systems for reducing the imaging doses and further improving the image quality.

GPU implementation of prior image constrained compressed sensing (PICCS)

NASA Astrophysics Data System (ADS)

Nett, Brian E.; Tang, Jie; Chen, Guang-Hong

2010-04-01

The Prior Image Constrained Compressed Sensing (PICCS) algorithm (Med. Phys. 35, pg. 660, 2008) has been applied to several computed tomography applications with both standard CT systems and flat-panel based systems designed for guiding interventional procedures and radiation therapy treatment delivery. The PICCS algorithm typically utilizes a prior image which is reconstructed via the standard Filtered Backprojection (FBP) reconstruction algorithm. The algorithm then iteratively solves for the image volume that matches the measured data, while simultaneously assuring the image is similar to the prior image. The PICCS algorithm has demonstrated utility in several applications including: improved temporal resolution reconstruction, 4D respiratory phase specific reconstructions for radiation therapy, and cardiac reconstruction from data acquired on an interventional C-arm. One disadvantage of the PICCS algorithm, just as other iterative algorithms, is the long computation times typically associated with reconstruction. In order for an algorithm to gain clinical acceptance reconstruction must be achievable in minutes rather than hours. In this work the PICCS algorithm has been implemented on the GPU in order to significantly reduce the reconstruction time of the PICCS algorithm. The Compute Unified Device Architecture (CUDA) was used in this implementation.

Area and power efficient DCT architecture for image compression

NASA Astrophysics Data System (ADS)

Dhandapani, Vaithiyanathan; Ramachandran, Seshasayanan

2014-12-01

The discrete cosine transform (DCT) is one of the major components in image and video compression systems. The final output of these systems is interpreted by the human visual system (HVS), which is not perfect. The limited perception of human visualization allows the algorithm to be numerically approximate rather than exact. In this paper, we propose a new matrix for discrete cosine transform. The proposed 8 × 8 transformation matrix contains only zeros and ones which requires only adders, thus avoiding the need for multiplication and shift operations. The new class of transform requires only 12 additions, which highly reduces the computational complexity and achieves a performance in image compression that is comparable to that of the existing approximated DCT. Another important aspect of the proposed transform is that it provides an efficient area and power optimization while implementing in hardware. To ensure the versatility of the proposal and to further evaluate the performance and correctness of the structure in terms of speed, area, and power consumption, the model is implemented on Xilinx Virtex 7 field programmable gate array (FPGA) device and synthesized with Cadence® RTL Compiler® using UMC 90 nm standard cell library. The analysis obtained from the implementation indicates that the proposed structure is superior to the existing approximation techniques with a 30% reduction in power and 12% reduction in area.

Combined Optical Imaging and Mammography of the Healthy Breast: Optical Contrast Derived From Breast Structure and Compression

PubMed Central

Fang, Qianqian; Carp, Stefan A.; Selb, Juliette; Boverman, Greg; Zhang, Quan; Kopans, Daniel B.; Moore, Richard H.; Miller, Eric L.; Brooks, Dana H.; Boas, David A.

2009-01-01

In this paper, we report new progress in developing the instrument and software platform of a combined X-ray mammography/diffuse optical breast imaging system. Particularly, we focus on system validation using a series of balloon phantom experiments and the optical image analysis of 49 healthy patients. Using the finite-element method for forward modeling and a regularized Gauss-Newton method for parameter reconstruction, we recovered the inclusions inside the phantom and the hemoglobin images of the human breasts. An enhanced coupling coefficient estimation scheme was also incorporated to improve the accuracy and robustness of the reconstructions. The recovered average total hemoglobin concentration (HbT) and oxygen saturation (SO2) from 68 breast measurements are 16.2 μm and 71%, respectively, where the HbT presents a linear trend with breast density. The low HbT value compared to literature is likely due to the associated mammographic compression. From the spatially co-registered optical/X-ray images, we can identify the chest-wall muscle, fatty tissue, and fibroglandular regions with an average HbT of 20.1±6.1 μm for fibroglandular tissue, 15.4±5.0 μm for adipose, and 22.2±7.3 μm for muscle tissue. The differences between fibroglandular tissue and the corresponding adipose tissue are significant (p < 0.0001). At the same time, we recognize that the optical images are influenced, to a certain extent, by mammographical compression. The optical images from a subset of patients show composite features from both tissue structure and pressure distribution. We present mechanical simulations which further confirm this hypothesis. PMID:19116186

Lossless Compression of Classification-Map Data

NASA Technical Reports Server (NTRS)

Hua, Xie; Klimesh, Matthew

2009-01-01

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Breast compression in mammography: how much is enough?

PubMed

Poulos, Ann; McLean, Donald; Rickard, Mary; Heard, Robert

2003-06-01

The amount of breast compression that is applied during mammography potentially influences image quality and the discomfort experienced. The aim of this study was to determine the relationship between applied compression force, breast thickness, reported discomfort and image quality. Participants were women attending routine breast screening by mammography at BreastScreen New South Wales Central and Eastern Sydney. During the mammographic procedure, an 'extra' craniocaudal (CC) film was taken at a reduced level of compression ranging from 10 to 30 Newtons. Breast thickness measurements were recorded for both the normal and the extra CC film. Details of discomfort experienced, cup size, menstrual status, existing breast pain and breast problems were also recorded. Radiologists were asked to compare the image quality of the normal and manipulated film. The results indicated that 24% of women did not experience a difference in thickness when the compression was reduced. This is an important new finding because the aim of breast compression is to reduce breast thickness. If breast thickness is not reduced when compression force is applied then discomfort is increased with no benefit in image quality. This has implications for mammographic practice when determining how much breast compression is sufficient. Radiologists found a decrease in contrast resolution within the fatty area of the breast between the normal and the extra CC film, confirming a decrease in image quality due to insufficient applied compression force.

Using a visual discrimination model for the detection of compression artifacts in virtual pathology images.

PubMed

Johnson, Jeffrey P; Krupinski, Elizabeth A; Yan, Michelle; Roehrig, Hans; Graham, Anna R; Weinstein, Ronald S

2011-02-01

A major issue in telepathology is the extremely large and growing size of digitized "virtual" slides, which can require several gigabytes of storage and cause significant delays in data transmission for remote image interpretation and interactive visualization by pathologists. Compression can reduce this massive amount of virtual slide data, but reversible (lossless) methods limit data reduction to less than 50%, while lossy compression can degrade image quality and diagnostic accuracy. "Visually lossless" compression offers the potential for using higher compression levels without noticeable artifacts, but requires a rate-control strategy that adapts to image content and loss visibility. We investigated the utility of a visual discrimination model (VDM) and other distortion metrics for predicting JPEG 2000 bit rates corresponding to visually lossless compression of virtual slides for breast biopsy specimens. Threshold bit rates were determined experimentally with human observers for a variety of tissue regions cropped from virtual slides. For test images compressed to their visually lossless thresholds, just-noticeable difference (JND) metrics computed by the VDM were nearly constant at the 95th percentile level or higher, and were significantly less variable than peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics. Our results suggest that VDM metrics could be used to guide the compression of virtual slides to achieve visually lossless compression while providing 5-12 times the data reduction of reversible methods.

Technical Note: Comparison of first- and second-generation photon-counting slit-scanning tomosynthesis systems.

PubMed

Berggren, Karl; Cederström, Björn; Lundqvist, Mats; Fredenberg, Erik

2018-02-01

Digital breast tomosynthesis (DBT) is an emerging tool for breast-cancer screening and diagnostics. The purpose of this study is to present a second-generation photon-counting slit-scanning DBT system and compare it to the first-generation system in terms of geometry and image quality. The study presents the first image-quality measurements on the second-generation system. The geometry of the new system is based on a combined rotational and linear motion, in contrast to a purely rotational scan motion in the first generation. In addition, the calibration routines have been updated. Image quality was measured in the center of the image field in terms of in-slice modulation transfer function (MTF), artifact spread function (ASF), and in-slice detective quantum efficiency (DQE). Images were acquired using a W/Al 29 kVp spectrum at 13 mAs with 2 mm Al additional filtration and reconstructed using simple back-projection. The in-slice 50% MTF was improved in the chest-mammilla direction, going from 3.2 to 3.5 lp/mm, and the zero-frequency DQE increased from 0.71 to 0.77. The MTF and ASF were otherwise found to be on par for the two systems. The new system has reduced in-slice variation of the tomographic angle. The new geometry is less curved, which reduces in-slice tomographic-angle variation, and increases the maximum compression height, making the system accessible for a larger population. The improvements in MTF and DQE were attributed to the updated calibration procedures. We conclude that the second-generation system maintains the key features of the photon-counting system while maintaining or improving image quality and improving the maximum compression height. © 2017 American Association of Physicists in Medicine.

Extreme compression for extreme conditions: pilot study to identify optimal compression of CT images using MPEG-4 video compression.

PubMed

Peterson, P Gabriel; Pak, Sung K; Nguyen, Binh; Jacobs, Genevieve; Folio, Les

2012-12-01

This study aims to evaluate the utility of compressed computed tomography (CT) studies (to expedite transmission) using Motion Pictures Experts Group, Layer 4 (MPEG-4) movie formatting in combat hospitals when guiding major treatment regimens. This retrospective analysis was approved by Walter Reed Army Medical Center institutional review board with a waiver for the informed consent requirement. Twenty-five CT chest, abdomen, and pelvis exams were converted from Digital Imaging and Communications in Medicine to MPEG-4 movie format at various compression ratios. Three board-certified radiologists reviewed various levels of compression on emergent CT findings on 25 combat casualties and compared with the interpretation of the original series. A Universal Trauma Window was selected at -200 HU level and 1,500 HU width, then compressed at three lossy levels. Sensitivities and specificities for each reviewer were calculated along with 95 % confidence intervals using the method of general estimating equations. The compression ratios compared were 171:1, 86:1, and 41:1 with combined sensitivities of 90 % (95 % confidence interval, 79-95), 94 % (87-97), and 100 % (93-100), respectively. Combined specificities were 100 % (85-100), 100 % (85-100), and 96 % (78-99), respectively. The introduction of CT in combat hospitals with increasing detectors and image data in recent military operations has increased the need for effective teleradiology; mandating compression technology. Image compression is currently used to transmit images from combat hospital to tertiary care centers with subspecialists and our study demonstrates MPEG-4 technology as a reasonable means of achieving such compression.

Layered compression for high-precision depth data.

PubMed

Miao, Dan; Fu, Jingjing; Lu, Yan; Li, Shipeng; Chen, Chang Wen

2015-12-01

With the development of depth data acquisition technologies, access to high-precision depth with more than 8-b depths has become much easier and determining how to efficiently represent and compress high-precision depth is essential for practical depth storage and transmission systems. In this paper, we propose a layered high-precision depth compression framework based on an 8-b image/video encoder to achieve efficient compression with low complexity. Within this framework, considering the characteristics of the high-precision depth, a depth map is partitioned into two layers: 1) the most significant bits (MSBs) layer and 2) the least significant bits (LSBs) layer. The MSBs layer provides rough depth value distribution, while the LSBs layer records the details of the depth value variation. For the MSBs layer, an error-controllable pixel domain encoding scheme is proposed to exploit the data correlation of the general depth information with sharp edges and to guarantee the data format of LSBs layer is 8 b after taking the quantization error from MSBs layer. For the LSBs layer, standard 8-b image/video codec is leveraged to perform the compression. The experimental results demonstrate that the proposed coding scheme can achieve real-time depth compression with satisfactory reconstruction quality. Moreover, the compressed depth data generated from this scheme can achieve better performance in view synthesis and gesture recognition applications compared with the conventional coding schemes because of the error control algorithm.

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Interleaved EPI diffusion imaging using SPIRiT-based reconstruction with virtual coil compression.

PubMed

Dong, Zijing; Wang, Fuyixue; Ma, Xiaodong; Zhang, Zhe; Dai, Erpeng; Yuan, Chun; Guo, Hua

2018-03-01

To develop a novel diffusion imaging reconstruction framework based on iterative self-consistent parallel imaging reconstruction (SPIRiT) for multishot interleaved echo planar imaging (iEPI), with computation acceleration by virtual coil compression. As a general approach for autocalibrating parallel imaging, SPIRiT improves the performance of traditional generalized autocalibrating partially parallel acquisitions (GRAPPA) methods in that the formulation with self-consistency is better conditioned, suggesting SPIRiT to be a better candidate in k-space-based reconstruction. In this study, a general SPIRiT framework is adopted to incorporate both coil sensitivity and phase variation information as virtual coils and then is applied to 2D navigated iEPI diffusion imaging. To reduce the reconstruction time when using a large number of coils and shots, a novel shot-coil compression method is proposed for computation acceleration in Cartesian sampling. Simulations and in vivo experiments were conducted to evaluate the performance of the proposed method. Compared with the conventional coil compression, the shot-coil compression achieved higher compression rates with reduced errors. The simulation and in vivo experiments demonstrate that the SPIRiT-based reconstruction outperformed the existing method, realigned GRAPPA, and provided superior images with reduced artifacts. The SPIRiT-based reconstruction with virtual coil compression is a reliable method for high-resolution iEPI diffusion imaging. Magn Reson Med 79:1525-1531, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

The wavelet/scalar quantization compression standard for digital fingerprint images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J.N.; Brislawn, C.M.

1994-04-01

A new digital image compression standard has been adopted by the US Federal Bureau of Investigation for use on digitized gray-scale fingerprint images. The algorithm is based on adaptive uniform scalar quantization of a discrete wavelet transform image decomposition and is referred to as the wavelet/scalar quantization standard. The standard produces archival quality images at compression ratios of around 20:1 and will allow the FBI to replace their current database of paper fingerprint cards with digital imagery.

Mammographic compression in Asian women.

PubMed

Lau, Susie; Abdul Aziz, Yang Faridah; Ng, Kwan Hoong

2017-01-01

To investigate: (1) the variability of mammographic compression parameters amongst Asian women; and (2) the effects of reducing compression force on image quality and mean glandular dose (MGD) in Asian women based on phantom study. We retrospectively collected 15818 raw digital mammograms from 3772 Asian women aged 35-80 years who underwent screening or diagnostic mammography between Jan 2012 and Dec 2014 at our center. The mammograms were processed using a volumetric breast density (VBD) measurement software (Volpara) to assess compression force, compression pressure, compressed breast thickness (CBT), breast volume, VBD and MGD against breast contact area. The effects of reducing compression force on image quality and MGD were also evaluated based on measurement obtained from 105 Asian women, as well as using the RMI156 Mammographic Accreditation Phantom and polymethyl methacrylate (PMMA) slabs. Compression force, compression pressure, CBT, breast volume, VBD and MGD correlated significantly with breast contact area (p<0.0001). Compression parameters including compression force, compression pressure, CBT and breast contact area were widely variable between [relative standard deviation (RSD)≥21.0%] and within (p<0.0001) Asian women. The median compression force should be about 8.1 daN compared to the current 12.0 daN. Decreasing compression force from 12.0 daN to 9.0 daN increased CBT by 3.3±1.4 mm, MGD by 6.2-11.0%, and caused no significant effects on image quality (p>0.05). Force-standardized protocol led to widely variable compression parameters in Asian women. Based on phantom study, it is feasible to reduce compression force up to 32.5% with minimal effects on image quality and MGD.

Exploiting sparsity and low-rank structure for the recovery of multi-slice breast MRIs with reduced sampling error.

PubMed

Yin, X X; Ng, B W-H; Ramamohanarao, K; Baghai-Wadji, A; Abbott, D

2012-09-01

It has been shown that, magnetic resonance images (MRIs) with sparsity representation in a transformed domain, e.g. spatial finite-differences (FD), or discrete cosine transform (DCT), can be restored from undersampled k-space via applying current compressive sampling theory. The paper presents a model-based method for the restoration of MRIs. The reduced-order model, in which a full-system-response is projected onto a subspace of lower dimensionality, has been used to accelerate image reconstruction by reducing the size of the involved linear system. In this paper, the singular value threshold (SVT) technique is applied as a denoising scheme to reduce and select the model order of the inverse Fourier transform image, and to restore multi-slice breast MRIs that have been compressively sampled in k-space. The restored MRIs with SVT for denoising show reduced sampling errors compared to the direct MRI restoration methods via spatial FD, or DCT. Compressive sampling is a technique for finding sparse solutions to underdetermined linear systems. The sparsity that is implicit in MRIs is to explore the solution to MRI reconstruction after transformation from significantly undersampled k-space. The challenge, however, is that, since some incoherent artifacts result from the random undersampling, noise-like interference is added to the image with sparse representation. These recovery algorithms in the literature are not capable of fully removing the artifacts. It is necessary to introduce a denoising procedure to improve the quality of image recovery. This paper applies a singular value threshold algorithm to reduce the model order of image basis functions, which allows further improvement of the quality of image reconstruction with removal of noise artifacts. The principle of the denoising scheme is to reconstruct the sparse MRI matrices optimally with a lower rank via selecting smaller number of dominant singular values. The singular value threshold algorithm is performed by minimizing the nuclear norm of difference between the sampled image and the recovered image. It has been illustrated that this algorithm improves the ability of previous image reconstruction algorithms to remove noise artifacts while significantly improving the quality of MRI recovery.

Complex adaptation-based LDR image rendering for 3D image reconstruction

NASA Astrophysics Data System (ADS)

Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

2014-07-01

A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

PCIE interface design for high-speed image storage system based on SSD

NASA Astrophysics Data System (ADS)

Wang, Shiming

2015-02-01

This paper proposes and implements a standard interface of miniaturized high-speed image storage system, which combines PowerPC with FPGA and utilizes PCIE bus as the high speed switching channel. Attached to the PowerPC, mSATA interface SSD(Solid State Drive) realizes RAID3 array storage. At the same time, a high-speed real-time image compression patent IP core also can be embedded in FPGA, which is in the leading domestic level with compression rate and image quality, making that the system can record higher image data rate or achieve longer recording time. The notebook memory card buckle type design is used in the mSATA interface SSD, which make it possible to complete the replacement in 5 seconds just using single hand, thus the total length of repeated recordings is increased. MSI (Message Signaled Interrupts) interruption guarantees the stability and reliability of continuous DMA transmission. Furthermore, only through the gigabit network, the remote display, control and upload to backup function can be realized. According to an optional 25 frame/s or 30 frame/s, upload speeds can be up to more than 84 MB/s. Compared with the existing FLASH array high-speed memory systems, it has higher degree of modularity, better stability and higher efficiency on development, maintenance and upgrading. Its data access rate is up to 300MB/s, realizing the high speed image storage system miniaturization, standardization and modularization, thus it is fit for image acquisition, storage and real-time transmission to server on mobile equipment.

Adaptive compressed sensing of remote-sensing imaging based on the sparsity prediction

NASA Astrophysics Data System (ADS)

Yang, Senlin; Li, Xilong; Chong, Xin

2017-10-01

The conventional compressive sensing works based on the non-adaptive linear projections, and the parameter of its measurement times is usually set empirically. As a result, the quality of image reconstruction is always affected. Firstly, the block-based compressed sensing (BCS) with conventional selection for compressive measurements was given. Then an estimation method for the sparsity of image was proposed based on the two dimensional discrete cosine transform (2D DCT). With an energy threshold given beforehand, the DCT coefficients were processed with both energy normalization and sorting in descending order, and the sparsity of the image can be achieved by the proportion of dominant coefficients. And finally, the simulation result shows that, the method can estimate the sparsity of image effectively, and provides an active basis for the selection of compressive observation times. The result also shows that, since the selection of observation times is based on the sparse degree estimated with the energy threshold provided, the proposed method can ensure the quality of image reconstruction.

An efficient HW and SW design of H.264 video compression, storage and playback on FPGA devices for handheld thermal imaging systems

NASA Astrophysics Data System (ADS)

Gunay, Omer; Ozsarac, Ismail; Kamisli, Fatih

2017-05-01

Video recording is an essential property of new generation military imaging systems. Playback of the stored video on the same device is also desirable as it provides several operational benefits to end users. Two very important constraints for many military imaging systems, especially for hand-held devices and thermal weapon sights, are power consumption and size. To meet these constraints, it is essential to perform most of the processing applied to the video signal, such as preprocessing, compression, storing, decoding, playback and other system functions on a single programmable chip, such as FPGA, DSP, GPU or ASIC. In this work, H.264/AVC (Advanced Video Coding) compatible video compression, storage, decoding and playback blocks are efficiently designed and implemented on FPGA platforms using FPGA fabric and Altera NIOS II soft processor. Many subblocks that are used in video encoding are also used during video decoding in order to save FPGA resources and power. Computationally complex blocks are designed using FPGA fabric, while blocks such as SD card write/read, H.264 syntax decoding and CAVLC decoding are done using NIOS processor to benefit from software flexibility. In addition, to keep power consumption low, the system was designed to require limited external memory access. The design was tested using 640x480 25 fps thermal camera on CYCLONE V FPGA, which is the ALTERA's lowest power FPGA family, and consumes lower than 40% of CYCLONE V 5CEFA7 FPGA resources on average.

Quality and noise measurements in mobile phone video capture

NASA Astrophysics Data System (ADS)

Petrescu, Doina; Pincenti, John

2011-02-01

The quality of videos captured with mobile phones has become increasingly important particularly since resolutions and formats have reached a level that rivals the capabilities available in the digital camcorder market, and since many mobile phones now allow direct playback on large HDTVs. The video quality is determined by the combined quality of the individual parts of the imaging system including the image sensor, the digital color processing, and the video compression, each of which has been studied independently. In this work, we study the combined effect of these elements on the overall video quality. We do this by evaluating the capture under various lighting, color processing, and video compression conditions. First, we measure full reference quality metrics between encoder input and the reconstructed sequence, where the encoder input changes with light and color processing modifications. Second, we introduce a system model which includes all elements that affect video quality, including a low light additive noise model, ISP color processing, as well as the video encoder. Our experiments show that in low light conditions and for certain choices of color processing the system level visual quality may not improve when the encoder becomes more capable or the compression ratio is reduced.

Quality of reconstruction of compressed off-axis digital holograms by frequency filtering and wavelets.

PubMed

Cheremkhin, Pavel A; Kurbatova, Ekaterina A

2018-01-01

Compression of digital holograms can significantly help with the storage of objects and data in 2D and 3D form, its transmission, and its reconstruction. Compression of standard images by methods based on wavelets allows high compression ratios (up to 20-50 times) with minimum losses of quality. In the case of digital holograms, application of wavelets directly does not allow high values of compression to be obtained. However, additional preprocessing and postprocessing can afford significant compression of holograms and the acceptable quality of reconstructed images. In this paper application of wavelet transforms for compression of off-axis digital holograms are considered. The combined technique based on zero- and twin-order elimination, wavelet compression of the amplitude and phase components of the obtained Fourier spectrum, and further additional compression of wavelet coefficients by thresholding and quantization is considered. Numerical experiments on reconstruction of images from the compressed holograms are performed. The comparative analysis of applicability of various wavelets and methods of additional compression of wavelet coefficients is performed. Optimum parameters of compression of holograms by the methods can be estimated. Sizes of holographic information were decreased up to 190 times.

Human movement analysis with image processing in real time

NASA Astrophysics Data System (ADS)

Fauvet, Eric; Paindavoine, Michel; Cannard, F.

1991-04-01

In the field of the human sciences, a lot of applications needs to know the kinematic characteristics of the human movements Psycology is associating the characteristics with the control mechanism, sport and biomechariics are associating them with the performance of the sportman or of the patient. So the trainers or the doctors can correct the gesture of the subject to obtain a better performance if he knows the motion properties. Roherton's studies show the children motion evolution2 . Several investigations methods are able to measure the human movement But now most of the studies are based on image processing. Often the systems are working at the T.V. standard (50 frame per secund ). they permit only to study very slow gesture. A human operator analyses the digitizing sequence of the film manually giving a very expensive, especially long and unprecise operation. On these different grounds many human movement analysis systems were implemented. They consist of: - markers which are fixed to the anatomical interesting points on the subject in motion, - Image compression which is the art to coding picture data. Generally the compression Is limited to the centroid coordinates calculation tor each marker. These systems differ from one other in image acquisition and markers detection.

Performance assessment of a compressive sensing single-pixel imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2017-04-01

Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.

Image interpolation used in three-dimensional range data compression.

PubMed

Zhang, Shaoze; Zhang, Jianqi; Huang, Xi; Liu, Delian

2016-05-20

Advances in the field of three-dimensional (3D) scanning have made the acquisition of 3D range data easier and easier. However, with the large size of 3D range data comes the challenge of storing and transmitting it. To address this challenge, this paper presents a framework to further compress 3D range data using image interpolation. We first use a virtual fringe-projection system to store 3D range data as images, and then apply the interpolation algorithm to the images to reduce their resolution to further reduce the data size. When the 3D range data are needed, the low-resolution image is scaled up to its original resolution by applying the interpolation algorithm, and then the scaled-up image is decoded and the 3D range data are recovered according to the decoded result. Experimental results show that the proposed method could further reduce the data size while maintaining a low rate of error.

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

PubMed Central

Wadduwage, Dushan N.; Singh, Vijay Raj; Choi, Heejin; Yaqoob, Zahid; Heemskerk, Hans; Matsudaira, Paul; So, Peter T. C.

2017-01-01

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability. PMID:29392168

Imaging industry expectations for compressed sensing in MRI

NASA Astrophysics Data System (ADS)

King, Kevin F.; Kanwischer, Adriana; Peters, Rob

2015-09-01

Compressed sensing requires compressible data, incoherent acquisition and a nonlinear reconstruction algorithm to force creation of a compressible image consistent with the acquired data. MRI images are compressible using various transforms (commonly total variation or wavelets). Incoherent acquisition of MRI data by appropriate selection of pseudo-random or non-Cartesian locations in k-space is straightforward. Increasingly, commercial scanners are sold with enough computing power to enable iterative reconstruction in reasonable times. Therefore integration of compressed sensing into commercial MRI products and clinical practice is beginning. MRI frequently requires the tradeoff of spatial resolution, temporal resolution and volume of spatial coverage to obtain reasonable scan times. Compressed sensing improves scan efficiency and reduces the need for this tradeoff. Benefits to the user will include shorter scans, greater patient comfort, better image quality, more contrast types per patient slot, the enabling of previously impractical applications, and higher throughput. Challenges to vendors include deciding which applications to prioritize, guaranteeing diagnostic image quality, maintaining acceptable usability and workflow, and acquisition and reconstruction algorithm details. Application choice depends on which customer needs the vendor wants to address. The changing healthcare environment is putting cost and productivity pressure on healthcare providers. The improved scan efficiency of compressed sensing can help alleviate some of this pressure. Image quality is strongly influenced by image compressibility and acceleration factor, which must be appropriately limited. Usability and workflow concerns include reconstruction time and user interface friendliness and response. Reconstruction times are limited to about one minute for acceptable workflow. The user interface should be designed to optimize workflow and minimize additional customer training. Algorithm concerns include the decision of which algorithms to implement as well as the problem of optimal setting of adjustable parameters. It will take imaging vendors several years to work through these challenges and provide solutions for a wide range of applications.

Cloud Optimized Image Format and Compression

NASA Astrophysics Data System (ADS)

Becker, P.; Plesea, L.; Maurer, T.

2015-04-01

Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

New image compression scheme for digital angiocardiography application

NASA Astrophysics Data System (ADS)

Anastassopoulos, George C.; Lymberopoulos, Dimitris C.; Kotsopoulos, Stavros A.; Kokkinakis, George C.

1993-06-01

The present paper deals with the development and evaluation of a new compression scheme, for angiocardiography images. This scheme provides considerable compression of the medical data file, through two different stages. The first stage obliterates the redundancy inside a single frame domain since the second stage obliterates the redundancy among the sequential frames. Within these stages the employed data compression ratio can be easily adjusted according to the needs of the angiocardiography applications, where still or moving (in slow or full motion) images are hauled. The developed scheme has been tailored on the real needs of the diagnosis oriented conferencing-teleworking processes, where Unified Image Viewing facilities are required.

Science-based Region-of-Interest Image Compression

NASA Technical Reports Server (NTRS)

Wagstaff, K. L.; Castano, R.; Dolinar, S.; Klimesh, M.; Mukai, R.

2004-01-01

As the number of currently active space missions increases, so does competition for Deep Space Network (DSN) resources. Even given unbounded DSN time, power and weight constraints onboard the spacecraft limit the maximum possible data transmission rate. These factors highlight a critical need for very effective data compression schemes. Images tend to be the most bandwidth-intensive data, so image compression methods are particularly valuable. In this paper, we describe a method for prioritizing regions in an image based on their scientific value. Using a wavelet compression method that can incorporate priority information, we ensure that the highest priority regions are transmitted with the highest fidelity.

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

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

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

Implementation of image transmission server system using embedded Linux

NASA Astrophysics Data System (ADS)

Park, Jong-Hyun; Jung, Yeon Sung; Nam, Boo Hee

2005-12-01

In this paper, we performed the implementation of image transmission server system using embedded system that is for the specified object and easy to install and move. Since the embedded system has lower capability than the PC, we have to reduce the quantity of calculation of the baseline JPEG image compression and transmission. We used the Redhat Linux 9.0 OS at the host PC and the target board based on embedded Linux. The image sequences are obtained from the camera attached to the FPGA (Field Programmable Gate Array) board with ALTERA cooperation chip. For effectiveness and avoiding some constraints from the vendor's own, we made the device driver using kernel module.

Design of Restoration Method Based on Compressed Sensing and TwIST Algorithm

NASA Astrophysics Data System (ADS)

Zhang, Fei; Piao, Yan

2018-04-01

In order to improve the subjective and objective quality of degraded images at low sampling rates effectively,save storage space and reduce computational complexity at the same time, this paper proposes a joint restoration algorithm of compressed sensing and two step iterative threshold shrinkage (TwIST). The algorithm applies the TwIST algorithm which used in image restoration to the compressed sensing theory. Then, a small amount of sparse high-frequency information is obtained in frequency domain. The TwIST algorithm based on compressed sensing theory is used to accurately reconstruct the high frequency image. The experimental results show that the proposed algorithm achieves better subjective visual effects and objective quality of degraded images while accurately restoring degraded images.

The FBI compression standard for digitized fingerprint images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brislawn, C.M.; Bradley, J.N.; Onyshczak, R.J.

1996-10-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the currentmore » status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.« less

FBI compression standard for digitized fingerprint images

NASA Astrophysics Data System (ADS)

Brislawn, Christopher M.; Bradley, Jonathan N.; Onyshczak, Remigius J.; Hopper, Thomas

1996-11-01

The FBI has formulated national standards for digitization and compression of gray-scale fingerprint images. The compression algorithm for the digitized images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition, a technique referred to as the wavelet/scalar quantization method. The algorithm produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations. We will review the current status of the FBI standard, including the compliance testing process and the details of the first-generation encoder.

Ultrasound Elasticity Imaging System with Chirp-Coded Excitation for Assessing Biomechanical Properties of Elasticity Phantom

PubMed Central

Chun, Guan-Chun; Chiang, Hsing-Jung; Lin, Kuan-Hung; Li, Chien-Ming; Chen, Pei-Jarn; Chen, Tainsong

2015-01-01

The biomechanical properties of soft tissues vary with pathological phenomenon. Ultrasound elasticity imaging is a noninvasive method used to analyze the local biomechanical properties of soft tissues in clinical diagnosis. However, the echo signal-to-noise ratio (eSNR) is diminished because of the attenuation of ultrasonic energy by soft tissues. Therefore, to improve the quality of elastography, the eSNR and depth of ultrasound penetration must be increased using chirp-coded excitation. Moreover, the low axial resolution of ultrasound images generated by a chirp-coded pulse must be increased using an appropriate compression filter. The main aim of this study is to develop an ultrasound elasticity imaging system with chirp-coded excitation using a Tukey window for assessing the biomechanical properties of soft tissues. In this study, we propose an ultrasound elasticity imaging system equipped with a 7.5-MHz single-element transducer and polymethylpentene compression plate to measure strains in soft tissues. Soft tissue strains were analyzed using cross correlation (CC) and absolution difference (AD) algorithms. The optimal parameters of CC and AD algorithms used for the ultrasound elasticity imaging system with chirp-coded excitation were determined by measuring the elastographic signal-to-noise ratio (SNRe) of a homogeneous phantom. Moreover, chirp-coded excitation and short pulse excitation were used to measure the elasticity properties of the phantom. The elastographic qualities of the tissue-mimicking phantom were assessed in terms of Young’s modulus and elastographic contrast-to-noise ratio (CNRe). The results show that the developed ultrasound elasticity imaging system with chirp-coded excitation modulated by a Tukey window can acquire accurate, high-quality elastography images. PMID:28793718

Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Hart, S. D.; Shi, X.; Siegel, V. L.

2004-01-01

We are developing an automated science analysis system that could be utilized by robotic or human explorers on Mars (or even in remote locations on Earth) to improve the quality and quantity of science data returned. Three components of this system (our rock, layer, and horizon detectors) [1] have been incorporated into the JPL CLARITY system for possible use by MSL and future Mars robotic missions. Two other components include a multi-spectral image compression (SPEC) algorithm for pancam-type images with multiple filters and image fusion algorithms that identify the in focus regions of individual images in an image focal series [2]. Recently, we have been working to combine image and spectral data, and other knowledge to identify both rocks and minerals. Here we present our progress on developing an igneous rock detection system.

Multi-frame X-ray Phase Contrast Imaging (MPCI) for Dynamic Experiments

NASA Astrophysics Data System (ADS)

Iverson, Adam; Carlson, Carl; Sanchez, Nathaniel; Jensen, Brian

2017-06-01

Recent advances in coupling synchrotron X-ray diagnostics to dynamic experiments are providing new information about the response of materials at extremes. For example, propagation based X-ray Phase Contrast Imaging (PCI) which is sensitive to differences in density has been successfully used to study a wide range of phenomena, e.g. jet-formation, compression of additive manufactured (AM) materials, and detonator dynamics. In this talk, we describe the current multi-frame X-ray phase contrast imaging (MPCI) system which allows up to eight frames per experiment, remote optimization, and an improved optical design that increases optical efficiency and accommodates dual-magnification during a dynamic event. Data will be presented that used the dual-magnification feature to obtain multiple images of an exploding foil initiator. In addition, results from static testing will be presented that used a multiple scintillator configuration required to extend the density retrieval to multi-constituent, or heterogeneous systems. The continued development of this diagnostic is fundamentally important to capabilities at the APS including IMPULSE and the Dynamic Compression Sector (DCS), and will benefit future facilities such as MaRIE at Los Alamos National Laboratory.

Determining building interior structures using compressive sensing

NASA Astrophysics Data System (ADS)

Lagunas, Eva; Amin, Moeness G.; Ahmad, Fauzia; Nájar, Montse

2013-04-01

We consider imaging of the building interior structures using compressive sensing (CS) with applications to through-the-wall imaging and urban sensing. We consider a monostatic synthetic aperture radar imaging system employing stepped frequency waveform. The proposed approach exploits prior information of building construction practices to form an appropriate sparse representation of the building interior layout. We devise a dictionary of possible wall locations, which is consistent with the fact that interior walls are typically parallel or perpendicular to the front wall. The dictionary accounts for the dominant normal angle reflections from exterior and interior walls for the monostatic imaging system. CS is applied to a reduced set of observations to recover the true positions of the walls. Additional information about interior walls can be obtained using a dictionary of possible corner reflectors, which is the response of the junction of two walls. Supporting results based on simulation and laboratory experiments are provided. It is shown that the proposed sparsifying basis outperforms the conventional through-the-wall CS model, the wavelet sparsifying basis, and the block sparse model for building interior layout detection.

Phoenix Telemetry Processor

NASA Technical Reports Server (NTRS)

Stanboli, Alice

2013-01-01

Phxtelemproc is a C/C++ based telemetry processing program that processes SFDU telemetry packets from the Telemetry Data System (TDS). It generates Experiment Data Records (EDRs) for several instruments including surface stereo imager (SSI); robotic arm camera (RAC); robotic arm (RA); microscopy, electrochemistry, and conductivity analyzer (MECA); and the optical microscope (OM). It processes both uncompressed and compressed telemetry, and incorporates unique subroutines for the following compression algorithms: JPEG Arithmetic, JPEG Huffman, Rice, LUT3, RA, and SX4. This program was in the critical path for the daily command cycle of the Phoenix mission. The products generated by this program were part of the RA commanding process, as well as the SSI, RAC, OM, and MECA image and science analysis process. Its output products were used to advance science of the near polar regions of Mars, and were used to prove that water is found in abundance there. Phxtelemproc is part of the MIPL (Multi-mission Image Processing Laboratory) system. This software produced Level 1 products used to analyze images returned by in situ spacecraft. It ultimately assisted in operations, planning, commanding, science, and outreach.

Hyperspectral image compressing using wavelet-based method

NASA Astrophysics Data System (ADS)

Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

2017-10-01

Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

Coil Compression for Accelerated Imaging with Cartesian Sampling

PubMed Central

Zhang, Tao; Pauly, John M.; Vasanawala, Shreyas S.; Lustig, Michael

2012-01-01

MRI using receiver arrays with many coil elements can provide high signal-to-noise ratio and increase parallel imaging acceleration. At the same time, the growing number of elements results in larger datasets and more computation in the reconstruction. This is of particular concern in 3D acquisitions and in iterative reconstructions. Coil compression algorithms are effective in mitigating this problem by compressing data from many channels into fewer virtual coils. In Cartesian sampling there often are fully sampled k-space dimensions. In this work, a new coil compression technique for Cartesian sampling is presented that exploits the spatially varying coil sensitivities in these non-subsampled dimensions for better compression and computation reduction. Instead of directly compressing in k-space, coil compression is performed separately for each spatial location along the fully-sampled directions, followed by an additional alignment process that guarantees the smoothness of the virtual coil sensitivities. This important step provides compatibility with autocalibrating parallel imaging techniques. Its performance is not susceptible to artifacts caused by a tight imaging fieldof-view. High quality compression of in-vivo 3D data from a 32 channel pediatric coil into 6 virtual coils is demonstrated. PMID:22488589

Subjective evaluations of integer cosine transform compressed Galileo solid state imagery

NASA Technical Reports Server (NTRS)

Haines, Richard F.; Gold, Yaron; Grant, Terry; Chuang, Sherry

1994-01-01

This paper describes a study conducted for the Jet Propulsion Laboratory, Pasadena, California, using 15 evaluators from 12 institutions involved in the Galileo Solid State Imaging (SSI) experiment. The objective of the study was to determine the impact of integer cosine transform (ICT) compression using specially formulated quantization (q) tables and compression ratios on acceptability of the 800 x 800 x 8 monochromatic astronomical images as evaluated visually by Galileo SSI mission scientists. Fourteen different images in seven image groups were evaluated. Each evaluator viewed two versions of the same image side by side on a high-resolution monitor; each was compressed using a different q level. First the evaluators selected the image with the highest overall quality to support them in their visual evaluations of image content. Next they rated each image using a scale from one to five indicating its judged degree of usefulness. Up to four preselected types of images with and without noise were presented to each evaluator.

Computational Simulation of Breast Compression Based on Segmented Breast and Fibroglandular Tissues on Magnetic Resonance Images

PubMed Central

Shih, Tzu-Ching; Chen, Jeon-Hor; Liu, Dongxu; Nie, Ke; Sun, Lizhi; Lin, Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying

2010-01-01

This study presents a finite element based computational model to simulate the three-dimensional deformation of the breast and the fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and the craniocaudal and mediolateral oblique compression as used in mammography was applied. The geometry of whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo® 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the non-linear elastic tissue deformation under compression, using the MSC.Marc® software package. The model was tested in 4 cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these 4 cases at 60% compression ratio was in the range of 5-7 cm, which is the typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at 60% compression ratio was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on MRI, which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density measurements needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities – such as MRI, mammography, whole breast ultrasound, and molecular imaging – that are performed using different body positions and different compression conditions. PMID:20601773

Image segmentation by iterative parallel region growing with application to data compression and image analysis

NASA Technical Reports Server (NTRS)

Tilton, James C.

1988-01-01

Image segmentation can be a key step in data compression and image analysis. However, the segmentation results produced by most previous approaches to region growing are suspect because they depend on the order in which portions of the image are processed. An iterative parallel segmentation algorithm avoids this problem by performing globally best merges first. Such a segmentation approach, and two implementations of the approach on NASA's Massively Parallel Processor (MPP) are described. Application of the segmentation approach to data compression and image analysis is then described, and results of such application are given for a LANDSAT Thematic Mapper image.

An ultra-low-power image compressor for capsule endoscope.

PubMed

Lin, Meng-Chun; Dung, Lan-Rong; Weng, Ping-Kuo

2006-02-25

Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam. We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture. As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.

Color image lossy compression based on blind evaluation and prediction of noise characteristics

NASA Astrophysics Data System (ADS)

Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Lepisto, Leena

2011-03-01

The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

Image compression software for the SOHO LASCO and EIT experiments

NASA Technical Reports Server (NTRS)

Grunes, Mitchell R.; Howard, Russell A.; Hoppel, Karl; Mango, Stephen A.; Wang, Dennis

1994-01-01

This paper describes the lossless and lossy image compression algorithms to be used on board the Solar Heliospheric Observatory (SOHO) in conjunction with the Large Angle Spectrometric Coronograph and Extreme Ultraviolet Imaging Telescope experiments. It also shows preliminary results obtained using similar prior imagery and discusses the lossy compression artifacts which will result. This paper is in part intended for the use of SOHO investigators who need to understand the results of SOHO compression in order to better allocate the transmission bits which they have been allocated.

Selection of bi-level image compression method for reduction of communication energy in wireless visual sensor networks

NASA Astrophysics Data System (ADS)

Khursheed, Khursheed; Imran, Muhammad; Ahmad, Naeem; O'Nils, Mattias

2012-06-01

Wireless Visual Sensor Network (WVSN) is an emerging field which combines image sensor, on board computation unit, communication component and energy source. Compared to the traditional wireless sensor network, which operates on one dimensional data, such as temperature, pressure values etc., WVSN operates on two dimensional data (images) which requires higher processing power and communication bandwidth. Normally, WVSNs are deployed in areas where installation of wired solutions is not feasible. The energy budget in these networks is limited to the batteries, because of the wireless nature of the application. Due to the limited availability of energy, the processing at Visual Sensor Nodes (VSN) and communication from VSN to server should consume as low energy as possible. Transmission of raw images wirelessly consumes a lot of energy and requires higher communication bandwidth. Data compression methods reduce data efficiently and hence will be effective in reducing communication cost in WVSN. In this paper, we have compared the compression efficiency and complexity of six well known bi-level image compression methods. The focus is to determine the compression algorithms which can efficiently compress bi-level images and their computational complexity is suitable for computational platform used in WVSNs. These results can be used as a road map for selection of compression methods for different sets of constraints in WVSN.

Perceptual compression of magnitude-detected synthetic aperture radar imagery

NASA Technical Reports Server (NTRS)

Gorman, John D.; Werness, Susan A.

1994-01-01

A perceptually-based approach for compressing synthetic aperture radar (SAR) imagery is presented. Key components of the approach are a multiresolution wavelet transform, a bit allocation mask based on an empirical human visual system (HVS) model, and hybrid scalar/vector quantization. Specifically, wavelet shrinkage techniques are used to segregate wavelet transform coefficients into three components: local means, edges, and texture. Each of these three components is then quantized separately according to a perceptually-based bit allocation scheme. Wavelet coefficients associated with local means and edges are quantized using high-rate scalar quantization while texture information is quantized using low-rate vector quantization. The impact of the perceptually-based multiresolution compression algorithm on visual image quality, impulse response, and texture properties is assessed for fine-resolution magnitude-detected SAR imagery; excellent image quality is found at bit rates at or above 1 bpp along with graceful performance degradation at rates below 1 bpp.

High-grade video compression of echocardiographic studies: a multicenter validation study of selected motion pictures expert groups (MPEG)-4 algorithms.

PubMed

Barbier, Paolo; Alimento, Marina; Berna, Giovanni; Celeste, Fabrizio; Gentile, Francesco; Mantero, Antonio; Montericcio, Vincenzo; Muratori, Manuela

2007-05-01

Large files produced by standard compression algorithms slow down spread of digital and tele-echocardiography. We validated echocardiographic video high-grade compression with the new Motion Pictures Expert Groups (MPEG)-4 algorithms with a multicenter study. Seven expert cardiologists blindly scored (5-point scale) 165 uncompressed and compressed 2-dimensional and color Doppler video clips, based on combined diagnostic content and image quality (uncompressed files as references). One digital video and 3 MPEG-4 algorithms (WM9, MV2, and DivX) were used, the latter at 3 compression levels (0%, 35%, and 60%). Compressed file sizes decreased from 12 to 83 MB to 0.03 to 2.3 MB (1:1051-1:26 reduction ratios). Mean SD of differences was 0.81 for intraobserver variability (uncompressed and digital video files). Compared with uncompressed files, only the DivX mean score at 35% (P = .04) and 60% (P = .001) compression was significantly reduced. At subcategory analysis, these differences were still significant for gray-scale and fundamental imaging but not for color or second harmonic tissue imaging. Original image quality, session sequence, compression grade, and bitrate were all independent determinants of mean score. Our study supports use of MPEG-4 algorithms to greatly reduce echocardiographic file sizes, thus facilitating archiving and transmission. Quality evaluation studies should account for the many independent variables that affect image quality grading.

Single image non-uniformity correction using compressive sensing

NASA Astrophysics Data System (ADS)

Jian, Xian-zhong; Lu, Rui-zhi; Guo, Qiang; Wang, Gui-pu

2016-05-01

A non-uniformity correction (NUC) method for an infrared focal plane array imaging system was proposed. The algorithm, based on compressive sensing (CS) of single image, overcame the disadvantages of "ghost artifacts" and bulk calculating costs in traditional NUC algorithms. A point-sampling matrix was designed to validate the measurements of CS on the time domain. The measurements were corrected using the midway infrared equalization algorithm, and the missing pixels were solved with the regularized orthogonal matching pursuit algorithm. Experimental results showed that the proposed method can reconstruct the entire image with only 25% pixels. A small difference was found between the correction results using 100% pixels and the reconstruction results using 40% pixels. Evaluation of the proposed method on the basis of the root-mean-square error, peak signal-to-noise ratio, and roughness index (ρ) proved the method to be robust and highly applicable.

Transfer Error and Correction Approach in Mobile Network

NASA Astrophysics Data System (ADS)

Xiao-kai, Wu; Yong-jin, Shi; Da-jin, Chen; Bing-he, Ma; Qi-li, Zhou

With the development of information technology and social progress, human demand for information has become increasingly diverse, wherever and whenever people want to be able to easily, quickly and flexibly via voice, data, images and video and other means to communicate. Visual information to the people direct and vivid image, image / video transmission also been widespread attention. Although the third generation mobile communication systems and the emergence and rapid development of IP networks, making video communications is becoming the main business of the wireless communications, however, the actual wireless and IP channel will lead to error generation, such as: wireless channel multi- fading channels generated error and blocking IP packet loss and so on. Due to channel bandwidth limitations, the video communication compression coding of data is often beyond the data, and compress data after the error is very sensitive to error conditions caused a serious decline in image quality.

Compressive sensing sectional imaging for single-shot in-line self-interference incoherent holography

NASA Astrophysics Data System (ADS)

Weng, Jiawen; Clark, David C.; Kim, Myung K.

2016-05-01

A numerical reconstruction method based on compressive sensing (CS) for self-interference incoherent digital holography (SIDH) is proposed to achieve sectional imaging by single-shot in-line self-interference incoherent hologram. The sensing operator is built up based on the physical mechanism of SIDH according to CS theory, and a recovery algorithm is employed for image restoration. Numerical simulation and experimental studies employing LEDs as discrete point-sources and resolution targets as extended sources are performed to demonstrate the feasibility and validity of the method. The intensity distribution and the axial resolution along the propagation direction of SIDH by angular spectrum method (ASM) and by CS are discussed. The analysis result shows that compared to ASM the reconstruction by CS can improve the axial resolution of SIDH, and achieve sectional imaging. The proposed method may be useful to 3D analysis of dynamic systems.

Development of a Mars Surface Imager

NASA Technical Reports Server (NTRS)

Squyres, Steve W.

1994-01-01

The Mars Surface Imager (MSI) is a multispectral, stereoscopic, panoramic imager that allows imaging of the full scene around a Mars lander from the lander body to the zenith. It has two functional components: panoramic imaging and sky imaging. In the most recent version of the MSI, called PIDDP-cam, a very long multi-line color CCD, an innovative high-performance drive system, and a state-of-the-art wavelet image compression code have been integrated into a single package. The requirements for the flight version of the MSI and the current design are presented.

Using PACS and wavelet-based image compression in a wide-area network to support radiation therapy imaging applications for satellite hospitals

NASA Astrophysics Data System (ADS)

Smith, Charles L.; Chu, Wei-Kom; Wobig, Randy; Chao, Hong-Yang; Enke, Charles

1999-07-01

An ongoing PACS project at our facility has been expanded to include providing and managing images used for routine clinical operation of the department of radiation oncology. The intent of our investigation has been to enable out clinical radiotherapy service to enter the tele-medicine environment through the use of a PACS system initially implemented in the department of radiology. The backbone for the imaging network includes five CT and three MR scanners located across three imaging centers. A PC workstation in the department of radiation oncology was used to transmit CT imags to a satellite facility located approximately 60 miles from the primary center. Chest CT images were used to analyze network transmission performance. Connectivity established between the primary department and satellite has fulfilled all image criteria required by the oncologist. Establishing the link tot eh oncologist at the satellite diminished bottlenecking of imaging related tasks at the primary facility due to physician absence. A 30:1 compression ratio using a wavelet-based algorithm provided clinically acceptable images treatment planning. Clinical radiotherapy images can be effectively managed in a wide- area-network to link satellite facilities to larger clinical centers.

An L1-norm phase constraint for half-Fourier compressed sensing in 3D MR imaging.

PubMed

Li, Guobin; Hennig, Jürgen; Raithel, Esther; Büchert, Martin; Paul, Dominik; Korvink, Jan G; Zaitsev, Maxim

2015-10-01

In most half-Fourier imaging methods, explicit phase replacement is used. In combination with parallel imaging, or compressed sensing, half-Fourier reconstruction is usually performed in a separate step. The purpose of this paper is to report that integration of half-Fourier reconstruction into iterative reconstruction minimizes reconstruction errors. The L1-norm phase constraint for half-Fourier imaging proposed in this work is compared with the L2-norm variant of the same algorithm, with several typical half-Fourier reconstruction methods. Half-Fourier imaging with the proposed phase constraint can be seamlessly combined with parallel imaging and compressed sensing to achieve high acceleration factors. In simulations and in in-vivo experiments half-Fourier imaging with the proposed L1-norm phase constraint enables superior performance both reconstruction of image details and with regard to robustness against phase estimation errors. The performance and feasibility of half-Fourier imaging with the proposed L1-norm phase constraint is reported. Its seamless combination with parallel imaging and compressed sensing enables use of greater acceleration in 3D MR imaging.

[Research and realization of signal processing algorithms based on FPGA in digital ophthalmic ultrasonography imaging].

PubMed

Fang, Simin; Zhou, Sheng; Wang, Xiaochun; Ye, Qingsheng; Tian, Ling; Ji, Jianjun; Wang, Yanqun

2015-01-01

To design and improve signal processing algorithms of ophthalmic ultrasonography based on FPGA. Achieved three signal processing modules: full parallel distributed dynamic filter, digital quadrature demodulation, logarithmic compression, using Verilog HDL hardware language in Quartus II. Compared to the original system, the hardware cost is reduced, the whole image shows clearer and more information of the deep eyeball contained in the image, the depth of detection increases from 5 cm to 6 cm. The new algorithms meet the design requirements and achieve the system's optimization that they can effectively improve the image quality of existing equipment.

Time reversal and phase coherent music techniques for super-resolution ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Labyed, Yassin

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

[Improvement of Digital Capsule Endoscopy System and Image Interpolation].

PubMed

Zhao, Shaopeng; Yan, Guozheng; Liu, Gang; Kuang, Shuai

2016-01-01

Traditional capsule image collects and transmits analog image, with weak anti-interference ability, low frame rate, low resolution. This paper presents a new digital image capsule, which collects and transmits digital image, with frame rate up to 30 frames/sec and pixels resolution of 400 x 400. The image is compressed in the capsule, and is transmitted to the outside of the capsule for decompression and interpolation. A new type of interpolation algorithm is proposed, which is based on the relationship between the image planes, to obtain higher quality colour images. capsule endoscopy, digital image, SCCB protocol, image interpolation

Influence of image compression on the interpretation of spectral-domain optical coherence tomography in exudative age-related macular degeneration

PubMed Central

Kim, J H; Kang, S W; Kim, J-r; Chang, Y S

2014-01-01

Purpose To evaluate the effect of image compression of spectral-domain optical coherence tomography (OCT) images in the examination of eyes with exudative age-related macular degeneration (AMD). Methods Thirty eyes from 30 patients who were diagnosed with exudative AMD were included in this retrospective observational case series. The horizontal OCT scans centered at the center of the fovea were conducted using spectral-domain OCT. The images were exported to Tag Image File Format (TIFF) and 100, 75, 50, 25 and 10% quality of Joint Photographic Experts Group (JPEG) format. OCT images were taken before and after intravitreal ranibizumab injections, and after relapse. The prevalence of subretinal and intraretinal fluids was determined. Differences in choroidal thickness between the TIFF and JPEG images were compared with the intra-observer variability. Results The prevalence of subretinal and intraretinal fluids was comparable regardless of the degree of compression. However, the chorio–scleral interface was not clearly identified in many images with a high degree of compression. In images with 25 and 10% quality of JPEG, the difference in choroidal thickness between the TIFF images and the respective JPEG images was significantly greater than the intra-observer variability of the TIFF images (P=0.029 and P=0.024, respectively). Conclusions In OCT images of eyes with AMD, 50% of the quality of the JPEG format would be an optimal degree of compression for efficient data storage and transfer without sacrificing image quality. PMID:24788012

Vector quantizer based on brightness maps for image compression with the polynomial transform

NASA Astrophysics Data System (ADS)

Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

2002-11-01

We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be a unique tool to structurally classify the image block within a given lattice. This particular operation intends to be one of the main contributions of this work. The fifth section will fuse the proposals derived from the study of the three main topics- addressed in the last sections- in order to propose an image compression model that takes advantage of vector quantizers inside the brightness transformed domain to determine the most important structures, finding the energy distribution inside the Hermite domain. Sixth and last section will show some results obtained while testing the coding-decoding model. The guidelines to evaluate the image compressing performance were the compression ratio, SNR and psycho-visual quality. Some conclusions derived from the research and possible unexplored paths will be shown on this section as well.

Mugshot Identification Database (MID)

National Institute of Standards and Technology Data Gateway

NIST Mugshot Identification Database (MID) (Web, free access)   NIST Special Database 18 is being distributed for use in development and testing of automated mugshot identification systems. The database consists of three CD-ROMs, containing a total of 3248 images of variable size using lossless compression. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

Nonlinear Multiscale Transformations: From Synchronization to Error Control

DTIC Science & Technology

2001-07-01

transformation (plus the quantization step) has taken place, a lossless Lempel - Ziv compression algorithm is applied to reduce the size of the transformed... compressed data are all very close, however the visual quality of the reconstructed image is significantly better for the EC compression algorithm ...used in recent times in the first step of transform coding algorithms for image compression . Ideally, a multiscale transformation allows for an

The Polygon-Ellipse Method of Data Compression of Weather Maps

DTIC Science & Technology

1994-03-28

Report No. DOT’•FAAJRD-9416 Pr•oject Report AD-A278 958 ATC-213 The Polygon-Ellipse Method of Data Compression of Weather Maps ELDCT E J.L. GerIz 28...a o means must he- found to Compress this image. The l’olygion.Ellip.e (PE.) encoding algorithm develop.ed in this report rt-premrnt. weather regions...severely compress the image. For example, Mode S would require approximately a 10-fold compression . In addition, the algorithms used to perform the

High-resolution three-dimensional imaging with compress sensing

NASA Astrophysics Data System (ADS)

Wang, Jingyi; Ke, Jun

2016-10-01

LIDAR three-dimensional imaging technology have been used in many fields, such as military detection. However, LIDAR require extremely fast data acquisition speed. This makes the manufacture of detector array for LIDAR system is very difficult. To solve this problem, we consider using compress sensing which can greatly decrease the data acquisition and relax the requirement of a detection device. To use the compressive sensing idea, a spatial light modulator will be used to modulate the pulsed light source. Then a photodetector is used to receive the reflected light. A convex optimization problem is solved to reconstruct the 2D depth map of the object. To improve the resolution in transversal direction, we use multiframe image restoration technology. For each 2D piecewise-planar scene, we move the SLM half-pixel each time. Then the position where the modulated light illuminates will changed accordingly. We repeat moving the SLM to four different directions. Then we can get four low-resolution depth maps with different details of the same plane scene. If we use all of the measurements obtained by the subpixel movements, we can reconstruct a high-resolution depth map of the sense. A linear minimum-mean-square error algorithm is used for the reconstruction. By combining compress sensing and multiframe image restoration technology, we reduce the burden on data analyze and improve the efficiency of detection. More importantly, we obtain high-resolution depth maps of a 3D scene.

Optical edge effects create conjunctival indentation thickness artefacts.

PubMed

Sorbara, Luigina; Simpson, Trefford L; Maram, Jyotsna; Song, Eun Sun; Bizheva, Kostadinka; Hutchings, Natalie

2015-05-01

Conjunctival compression observed in ultrahigh resolution optical coherence tomography (UHR-OCT) images of contact lens edges could be actual tissue alteration, may be an optical artefact arising from the difference between the refractive indexes of the lens material and the conjunctival tissue, or could be a combination of the two. The purpose of this study is to image the artefact with contact lenses on a non-biological (non-indentable) medium and to determine the origins of the observed conjunctival compression. Two-dimensional cross-sectional images of the edges of a selection of marketed silicone hydrogel and hydrogel lenses (refractive index ranging from 1.40 to 1.43) were acquired with a research grade UHR-OCT system. The lenses were placed on three continuous surfaces, a glass sphere (refractive index n = 1.52), a rigid contact lens (n = 1.376) and the cornea of a healthy human subject (average n = 1.376). The displacement observed was analysed using ImageJ. The observed optical displacement ranged between 5.39(0.06) μm with Acuvue Advance and 11.99(0.18) μm with Air Optix Night & Day when the lens was imaged on the glass reference sphere. Similarly, on a rigid contact lens displacement ranged between 5.51(0.03) and 9.72(0.12) μm. Displacement was also observed when the lenses were imaged on the human conjunctiva and ranged from 6.49(0.80) μm for the 1-day Acuvue Moist to 17.4(0.22) μm for the Pure Vision contact lens. An optical displacement artefact was observed when imaging a contact lens on two rigid continuous surfaces with UHR-OCT where compression or indentation of the surface could not have been a factor. Contact lenses imaged in situ also exhibited displacement at the intersection of the contact lens edge and the conjunctiva, likely a manifestation of both the artefact and compression of the conjunctiva. © 2015 The Authors Ophthalmic & Physiological Optics © 2015 The College of Optometrists.

Compressive passive millimeter wave imager

DOEpatents

Gopalsami, Nachappa; Liao, Shaolin; Elmer, Thomas W; Koehl, Eugene R; Heifetz, Alexander; Raptis, Apostolos C

2015-01-27

A compressive scanning approach for millimeter wave imaging and sensing. A Hadamard mask is positioned to receive millimeter waves from an object to be imaged. A subset of the full set of Hadamard acquisitions is sampled. The subset is used to reconstruct an image representing the object.

Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors

PubMed Central

Lee, Sungju; Kim, Heegon; Chung, Yongwha; Park, Daihee

2012-01-01

In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still hinder its adoption for practical use. However, it is anticipated that high-performance handheld multi-core devices will be used as VSN processing nodes in the near future. In this paper, we propose a way to improve the energy efficiency of image and video compression with multi-core processors while maintaining the image/video quality. We improve the compression efficiency at the algorithmic level or derive the optimal parameters for the combination of a machine and compression based on the tradeoff between the energy consumption and the image/video quality. Based on experimental results, we confirm that the proposed approach can improve the energy efficiency of the straightforward approach by a factor of 2∼5 without compromising image/video quality. PMID:23202181

CoGI: Towards Compressing Genomes as an Image.

PubMed

Xie, Xiaojing; Zhou, Shuigeng; Guan, Jihong

2015-01-01

Genomic science is now facing an explosive increase of data thanks to the fast development of sequencing technology. This situation poses serious challenges to genomic data storage and transferring. It is desirable to compress data to reduce storage and transferring cost, and thus to boost data distribution and utilization efficiency. Up to now, a number of algorithms / tools have been developed for compressing genomic sequences. Unlike the existing algorithms, most of which treat genomes as one-dimensional text strings and compress them based on dictionaries or probability models, this paper proposes a novel approach called CoGI (the abbreviation of Compressing Genomes as an Image) for genome compression, which transforms the genomic sequences to a two-dimensional binary image (or bitmap), then applies a rectangular partition coding algorithm to compress the binary image. CoGI can be used as either a reference-based compressor or a reference-free compressor. For the former, we develop two entropy-based algorithms to select a proper reference genome. Performance evaluation is conducted on various genomes. Experimental results show that the reference-based CoGI significantly outperforms two state-of-the-art reference-based genome compressors GReEn and RLZ-opt in both compression ratio and compression efficiency. It also achieves comparable compression ratio but two orders of magnitude higher compression efficiency in comparison with XM--one state-of-the-art reference-free genome compressor. Furthermore, our approach performs much better than Gzip--a general-purpose and widely-used compressor, in both compression speed and compression ratio. So, CoGI can serve as an effective and practical genome compressor. The source code and other related documents of CoGI are available at: http://admis.fudan.edu.cn/projects/cogi.htm.

Image processing techniques and applications to the Earth Resources Technology Satellite program

NASA Technical Reports Server (NTRS)

Polge, R. J.; Bhagavan, B. K.; Callas, L.

1973-01-01

The Earth Resources Technology Satellite system is studied, with emphasis on sensors, data processing requirements, and image data compression using the Fast Fourier and Hadamard transforms. The ERTS-A system and the fundamentals of remote sensing are discussed. Three user applications (forestry, crops, and rangelands) are selected and their spectral signatures are described. It is shown that additional sensors are needed for rangeland management. An on-board information processing system is recommended to reduce the amount of data transmitted.

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

NASA Astrophysics Data System (ADS)

Siddeq, M. M.; Rodrigues, M. A.

2015-09-01

Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation.

PubMed

Sturgeon, Gregory M; Kiarashi, Nooshin; Lo, Joseph Y; Samei, E; Segars, W P

2016-05-01

The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast.

Lossless compression algorithm for REBL direct-write e-beam lithography system

NASA Astrophysics Data System (ADS)

Cramer, George; Liu, Hsin-I.; Zakhor, Avideh

2010-03-01

Future lithography systems must produce microchips with smaller feature sizes, while maintaining throughputs comparable to those of today's optical lithography systems. This places stringent constraints on the effective data throughput of any maskless lithography system. In recent years, we have developed a datapath architecture for direct-write lithography systems, and have shown that compression plays a key role in reducing throughput requirements of such systems. Our approach integrates a low complexity hardware-based decoder with the writers, in order to decompress a compressed data layer in real time on the fly. In doing so, we have developed a spectrum of lossless compression algorithms for integrated circuit layout data to provide a tradeoff between compression efficiency and hardware complexity, the latest of which is Block Golomb Context Copy Coding (Block GC3). In this paper, we present a modified version of Block GC3 called Block RGC3, specifically tailored to the REBL direct-write E-beam lithography system. Two characteristic features of the REBL system are a rotary stage resulting in arbitrarily-rotated layout imagery, and E-beam corrections prior to writing the data, both of which present significant challenges to lossless compression algorithms. Together, these effects reduce the effectiveness of both the copy and predict compression methods within Block GC3. Similar to Block GC3, our newly proposed technique Block RGC3, divides the image into a grid of two-dimensional "blocks" of pixels, each of which copies from a specified location in a history buffer of recently-decoded pixels. However, in Block RGC3 the number of possible copy locations is significantly increased, so as to allow repetition to be discovered along any angle of orientation, rather than horizontal or vertical. Also, by copying smaller groups of pixels at a time, repetition in layout patterns is easier to find and take advantage of. As a side effect, this increases the total number of copy locations to transmit; this is combated with an extra region-growing step, which enforces spatial coherence among neighboring copy locations, thereby improving compression efficiency. We characterize the performance of Block RGC3 in terms of compression efficiency and encoding complexity on a number of rotated Metal 1, Poly, and Via layouts at various angles, and show that Block RGC3 provides higher compression efficiency than existing lossless compression algorithms, including JPEG-LS, ZIP, BZIP2, and Block GC3.

Modeling And Simulation Of Multimedia Communication Networks

NASA Astrophysics Data System (ADS)

Vallee, Richard; Orozco-Barbosa, Luis; Georganas, Nicolas D.

1989-05-01

In this paper, we present a simulation study of a browsing system involving radiological image servers. The proposed IEEE 802.6 DQDB MAN standard is designated as the computer network to transfer radiological images from file servers to medical workstations, and to simultaneously support real time voice communications. Storage and transmission of original raster scanned images and images compressed according to pyramid data structures are considered. Different types of browsing as well as various image sizes and bit rates in the DQDB MAN are also compared. The elapsed time, measured from the time an image request is issued until the image is displayed on the monitor, is the parameter considered to evaluate the system performance. Simulation results show that image browsing can be supported by the DQDB MAN.

Distinguishing one from many using super-resolution compressive sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anthony, Stephen Michael; Mulcahy-Stanislawczyk, Johnathan; Shields, Eric A.

We present that distinguishing whether a signal corresponds to a single source or a limited number of highly overlapping point spread functions (PSFs) is a ubiquitous problem across all imaging scales, whether detecting receptor-ligand interactions in cells or detecting binary stars. Super-resolution imaging based upon compressed sensing exploits the relative sparseness of the point sources to successfully resolve sources which may be separated by much less than the Rayleigh criterion. However, as a solution to an underdetermined system of linear equations, compressive sensing requires the imposition of constraints which may not always be valid. One typical constraint is that themore » PSF is known. However, the PSF of the actual optical system may reflect aberrations not present in the theoretical ideal optical system. Even when the optics are well characterized, the actual PSF may reflect factors such as non-uniform emission of the point source (e.g. fluorophore dipole emission). As such, the actual PSF may differ from the PSF used as a constraint. Similarly, multiple different regularization constraints have been suggested including the l 1-norm, l 0-norm, and generalized Gaussian Markov random fields (GGMRFs), each of which imposes a different constraint. Other important factors include the signal-to-noise ratio of the point sources and whether the point sources vary in intensity. In this work, we explore how these factors influence super-resolution image recovery robustness, determining the sensitivity and specificity. In conclusion, we determine an approach that is more robust to the types of PSF errors present in actual optical systems.« less

Distinguishing one from many using super-resolution compressive sensing

DOE PAGES

Anthony, Stephen Michael; Mulcahy-Stanislawczyk, Johnathan; Shields, Eric A.; ...

2018-05-14

We present that distinguishing whether a signal corresponds to a single source or a limited number of highly overlapping point spread functions (PSFs) is a ubiquitous problem across all imaging scales, whether detecting receptor-ligand interactions in cells or detecting binary stars. Super-resolution imaging based upon compressed sensing exploits the relative sparseness of the point sources to successfully resolve sources which may be separated by much less than the Rayleigh criterion. However, as a solution to an underdetermined system of linear equations, compressive sensing requires the imposition of constraints which may not always be valid. One typical constraint is that themore » PSF is known. However, the PSF of the actual optical system may reflect aberrations not present in the theoretical ideal optical system. Even when the optics are well characterized, the actual PSF may reflect factors such as non-uniform emission of the point source (e.g. fluorophore dipole emission). As such, the actual PSF may differ from the PSF used as a constraint. Similarly, multiple different regularization constraints have been suggested including the l 1-norm, l 0-norm, and generalized Gaussian Markov random fields (GGMRFs), each of which imposes a different constraint. Other important factors include the signal-to-noise ratio of the point sources and whether the point sources vary in intensity. In this work, we explore how these factors influence super-resolution image recovery robustness, determining the sensitivity and specificity. In conclusion, we determine an approach that is more robust to the types of PSF errors present in actual optical systems.« less

Compressive hyperspectral sensor for LWIR gas detection

NASA Astrophysics Data System (ADS)

Russell, Thomas A.; McMackin, Lenore; Bridge, Bob; Baraniuk, Richard

2012-06-01

Focal plane arrays with associated electronics and cooling are a substantial portion of the cost, complexity, size, weight, and power requirements of Long-Wave IR (LWIR) imagers. Hyperspectral LWIR imagers add significant data volume burden as they collect a high-resolution spectrum at each pixel. We report here on a LWIR Hyperspectral Sensor that applies Compressive Sensing (CS) in order to achieve benefits in these areas. The sensor applies single-pixel detection technology demonstrated by Rice University. The single-pixel approach uses a Digital Micro-mirror Device (DMD) to reflect and multiplex the light from a random assortment of pixels onto the detector. This is repeated for a number of measurements much less than the total number of scene pixels. We have extended this architecture to hyperspectral LWIR sensing by inserting a Fabry-Perot spectrometer in the optical path. This compressive hyperspectral imager collects all three dimensions on a single detection element, greatly reducing the size, weight and power requirements of the system relative to traditional approaches, while also reducing data volume. The CS architecture also supports innovative adaptive approaches to sensing, as the DMD device allows control over the selection of spatial scene pixels to be multiplexed on the detector. We are applying this advantage to the detection of plume gases, by adaptively locating and concentrating target energy. A key challenge in this system is the diffraction loss produce by the DMD in the LWIR. We report the results of testing DMD operation in the LWIR, as well as system spatial and spectral performance.

Cluster compression algorithm: A joint clustering/data compression concept

NASA Technical Reports Server (NTRS)

Hilbert, E. E.

1977-01-01

The Cluster Compression Algorithm (CCA), which was developed to reduce costs associated with transmitting, storing, distributing, and interpreting LANDSAT multispectral image data is described. The CCA is a preprocessing algorithm that uses feature extraction and data compression to more efficiently represent the information in the image data. The format of the preprocessed data enables simply a look-up table decoding and direct use of the extracted features to reduce user computation for either image reconstruction, or computer interpretation of the image data. Basically, the CCA uses spatially local clustering to extract features from the image data to describe spectral characteristics of the data set. In addition, the features may be used to form a sequence of scalar numbers that define each picture element in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. Various forms of the CCA are defined and experimental results are presented to show trade-offs and characteristics of the various implementations. Examples are provided that demonstrate the application of the cluster compression concept to multi-spectral images from LANDSAT and other sources.

Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Kiely, Aaron B.; Klimesh, Matthew A.

2010-01-01

A two-stage predictive method was developed for lossless compression of calibrated hyperspectral imagery. The first prediction stage uses a conventional linear predictor intended to exploit spatial and/or spectral dependencies in the data. The compressor tabulates counts of the past values of the difference between this initial prediction and the actual sample value. To form the ultimate predicted value, in the second stage, these counts are combined with an adaptively updated weight function intended to capture information about data regularities introduced by the calibration process. Finally, prediction residuals are losslessly encoded using adaptive arithmetic coding. Algorithms of this type are commonly tested on a readily available collection of images from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imager. On the standard calibrated AVIRIS hyperspectral images that are most widely used for compression benchmarking, the new compressor provides more than 0.5 bits/sample improvement over the previous best compression results. The algorithm has been implemented in Mathematica. The compression algorithm was demonstrated as beneficial on 12-bit calibrated AVIRIS images.

Ultra high-speed x-ray imaging of laser-driven shock compression using synchrotron light

NASA Astrophysics Data System (ADS)

Olbinado, Margie P.; Cantelli, Valentina; Mathon, Olivier; Pascarelli, Sakura; Grenzer, Joerg; Pelka, Alexander; Roedel, Melanie; Prencipe, Irene; Laso Garcia, Alejandro; Helbig, Uwe; Kraus, Dominik; Schramm, Ulrich; Cowan, Tom; Scheel, Mario; Pradel, Pierre; De Resseguier, Thibaut; Rack, Alexander

2018-02-01

A high-power, nanosecond pulsed laser impacting the surface of a material can generate an ablation plasma that drives a shock wave into it; while in situ x-ray imaging can provide a time-resolved probe of the shock-induced material behaviour on macroscopic length scales. Here, we report on an investigation into laser-driven shock compression of a polyurethane foam and a graphite rod by means of single-pulse synchrotron x-ray phase-contrast imaging with MHz frame rate. A 6 J, 10 ns pulsed laser was used to generate shock compression. Physical processes governing the laser-induced dynamic response such as elastic compression, compaction, pore collapse, fracture, and fragmentation have been imaged; and the advantage of exploiting the partial spatial coherence of a synchrotron source for studying low-density, carbon-based materials is emphasized. The successful combination of a high-energy laser and ultra high-speed x-ray imaging using synchrotron light demonstrates the potentiality of accessing complementary information from scientific studies of laser-driven shock compression.

Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation.

PubMed

Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

2017-01-27

Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

Compressive Hyperspectral Imaging and Anomaly Detection

DTIC Science & Technology

2010-02-01

Level Set Systems 1058 Embury Street Pacific Palisades , CA 90272 8. PERFORMING ORGANIZATION REPORT NUMBER 1A-2010 9. SPONSORING/MONITORING...were obtained from a simple algorithm, namely, the atoms in the trained image were very similar to the simple cell receptive fields in early vision...Field, "Emergence of simple- cell receptive field properties by learning a sparse code for natural images,’" Nature 381(6583), pp. 607-609, 1996. M

Survey of adaptive image coding techniques

NASA Technical Reports Server (NTRS)

Habibi, A.

1977-01-01

The general problem of image data compression is discussed briefly with attention given to the use of Karhunen-Loeve transforms, suboptimal systems, and block quantization. A survey is then conducted encompassing the four categories of adaptive systems: (1) adaptive transform coding (adaptive sampling, adaptive quantization, etc.), (2) adaptive predictive coding (adaptive delta modulation, adaptive DPCM encoding, etc.), (3) adaptive cluster coding (blob algorithms and the multispectral cluster coding technique), and (4) adaptive entropy coding.

High-quality compressive ghost imaging

NASA Astrophysics Data System (ADS)

Huang, Heyan; Zhou, Cheng; Tian, Tian; Liu, Dongqi; Song, Lijun

2018-04-01

We propose a high-quality compressive ghost imaging method based on projected Landweber regularization and guided filter, which effectively reduce the undersampling noise and improve the resolution. In our scheme, the original object is reconstructed by decomposing of regularization and denoising steps instead of solving a minimization problem in compressive reconstruction process. The simulation and experimental results show that our method can obtain high ghost imaging quality in terms of PSNR and visual observation.

A Novel Image Compression Algorithm for High Resolution 3D Reconstruction

NASA Astrophysics Data System (ADS)

Siddeq, M. M.; Rodrigues, M. A.

2014-06-01

This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm is concerned with compressing such images to a high degree with minimum loss without adversely affecting 3D reconstruction. The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. The sub-band LL is transformed by DCT yielding a DC-matrix and an AC-matrix. The Minimize-Matrix-Size Algorithm is used to compress the AC-matrix while a DWT is applied again to the DC-matrix resulting in LL2, HL2, LH2 and HH2 sub-bands. The LL2 sub-band is transformed by DCT, while the Minimize-Matrix-Size Algorithm is applied to the other sub-bands. The proposed algorithm has been tested with images of different sizes within a 3D reconstruction scenario. The algorithm is demonstrated to be more effective than JPEG2000 and JPEG concerning higher compression rates with equivalent perceived quality and the ability to more accurately reconstruct the 3D models.

Development of intelligent surveillance system (ISS) in region of interest (ROI) using Kalman filter and camshift on Raspberry Pi 2

NASA Astrophysics Data System (ADS)

Park, Junghun; Hong, Kicheon

2017-06-01

Due to the improvement of the picture quality of closed-circuit television (CCTV), the demand for CCTV has increased rapidly and its market size has also increased. The current system structure of CCTV transfers compressed images without analysis received from CCTV to a control center. The compressed images are suitable for the evidence required for a criminal arrest, but they cannot prevent crime in real time, which has been considered a limitation. Thus, the present paper proposes a system implementation that can prevent crimes by applying a situation awareness system at the back end of the CCTV cameras for image acquisition to prevent crimes efficiently. In the system implemented in the present paper, the region of interest (ROI) is set virtually within the image data when a barrier, such as fence, cannot be installed in actual sites and unauthorized intruders are tracked constantly through data analysis and recognized in the ROI via the developed algorithm. Additionally, a searchlight or alarm sound is activated to prevent crime in real time and the urgent information is transferred to the control center. The system was implemented in the Raspberry Pi 2 board to be run in real time. The experiment results showed that the recognition success rate was 85% or higher and the track accuracy was 90% or higher. By utilizing the system, crime prevention can be achieved by implementing a social safety network.

An image compression algorithm for a high-resolution digital still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

The Electronic Still Camera (ESC) project will provide for the capture and transmission of high-quality images without the use of film. The image quality will be superior to video and will approach the quality of 35mm film. The camera, which will have the same general shape and handling as a 35mm camera, will be able to send images to earth in near real-time. Images will be stored in computer memory (RAM) in removable cartridges readable by a computer. To save storage space, the image will be compressed and reconstructed at the time of viewing. Both lossless and loss-y image compression algorithms are studied, described, and compared.

Spectral images browsing using principal component analysis and set partitioning in hierarchical tree

NASA Astrophysics Data System (ADS)

Ma, Long; Zhao, Deping

2011-12-01

Spectral imaging technology have been used mostly in remote sensing, but have recently been extended to new area requiring high fidelity color reproductions like telemedicine, e-commerce, etc. These spectral imaging systems are important because they offer improved color reproduction quality not only for a standard observer under a particular illuminantion, but for any other individual exhibiting normal color vision capability under another illuminantion. A possibility for browsing of the archives is needed. In this paper, the authors present a new spectral image browsing architecture. The architecture for browsing is expressed as follow: (1) The spectral domain of the spectral image is reduced with the PCA transform. As a result of the PCA transform the eigenvectors and the eigenimages are obtained. (2) We quantize the eigenimages with the original bit depth of spectral image (e.g. if spectral image is originally 8bit, then quantize eigenimage to 8bit), and use 32bit floating numbers for the eigenvectors. (3) The first eigenimage is lossless compressed by JPEG-LS, the other eigenimages were lossy compressed by wavelet based SPIHT algorithm. For experimental evalution, the following measures were used. We used PSNR as the measurement for spectral accuracy. And for the evaluation of color reproducibility, ΔE was used.here standard D65 was used as a light source. To test the proposed method, we used FOREST and CORAL spectral image databases contrain 12 and 10 spectral images, respectively. The images were acquired in the range of 403-696nm. The size of the images were 128*128, the number of bands was 40 and the resolution was 8 bits per sample. Our experiments show the proposed compression method is suitable for browsing, i.e., for visual purpose.

Lossy compression of weak lensing data

DOE PAGES

Vanderveld, R. Ali; Bernstein, Gary M.; Stoughton, Chris; ...

2011-07-12

Future orbiting observatories will survey large areas of sky in order to constrain the physics of dark matter and dark energy using weak gravitational lensing and other methods. Lossy compression of the resultant data will improve the cost and feasibility of transmitting the images through the space communication network. We evaluate the consequences of the lossy compression algorithm of Bernstein et al. (2010) for the high-precision measurement of weak-lensing galaxy ellipticities. This square-root algorithm compresses each pixel independently, and the information discarded is by construction less than the Poisson error from photon shot noise. For simulated space-based images (without cosmicmore » rays) digitized to the typical 16 bits per pixel, application of the lossy compression followed by image-wise lossless compression yields images with only 2.4 bits per pixel, a factor of 6.7 compression. We demonstrate that this compression introduces no bias in the sky background. The compression introduces a small amount of additional digitization noise to the images, and we demonstrate a corresponding small increase in ellipticity measurement noise. The ellipticity measurement method is biased by the addition of noise, so the additional digitization noise is expected to induce a multiplicative bias on the galaxies measured ellipticities. After correcting for this known noise-induced bias, we find a residual multiplicative ellipticity bias of m {approx} -4 x 10 -4. This bias is small when compared to the many other issues that precision weak lensing surveys must confront, and furthermore we expect it to be reduced further with better calibration of ellipticity measurement methods.« less

Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2018-06-01

To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

The impact of skull bone intensity on the quality of compressed CT neuro images

NASA Astrophysics Data System (ADS)

Kowalik-Urbaniak, Ilona; Vrscay, Edward R.; Wang, Zhou; Cavaro-Menard, Christine; Koff, David; Wallace, Bill; Obara, Boguslaw

2012-02-01

The increasing use of technologies such as CT and MRI, along with a continuing improvement in their resolution, has contributed to the explosive growth of digital image data being generated. Medical communities around the world have recognized the need for efficient storage, transmission and display of medical images. For example, the Canadian Association of Radiologists (CAR) has recommended compression ratios for various modalities and anatomical regions to be employed by lossy JPEG and JPEG2000 compression in order to preserve diagnostic quality. Here we investigate the effects of the sharp skull edges present in CT neuro images on JPEG and JPEG2000 lossy compression. We conjecture that this atypical effect is caused by the sharp edges between the skull bone and the background regions as well as between the skull bone and the interior regions. These strong edges create large wavelet coefficients that consume an unnecessarily large number of bits in JPEG2000 compression because of its bitplane coding scheme, and thus result in reduced quality at the interior region, which contains most diagnostic information in the image. To validate the conjecture, we investigate a segmentation based compression algorithm based on simple thresholding and morphological operators. As expected, quality is improved in terms of PSNR as well as the structural similarity (SSIM) image quality measure, and its multiscale (MS-SSIM) and informationweighted (IW-SSIM) versions. This study not only supports our conjecture, but also provides a solution to improve the performance of JPEG and JPEG2000 compression for specific types of CT images.

Investigation of the possibility of gamma-ray diagnostic imaging of target compression at NIF

PubMed Central

Lemieux, Daniel A.; Baudet, Camille; Grim, Gary P.; Barber, H. Bradford; Miller, Brian W.; Fasje, David; Furenlid, Lars R.

2013-01-01

The National Ignition Facility at Lawrence Livermore National Laboratory is the world’s leading facility to study the physics of igniting plasmas. Plasmas of hot deuterium and tritium, undergo d(t,n)α reactions that produce a 14.1 MeV neutron and 3.5 MeV a particle, in the center of mass. As these neutrons pass through the materials surrounding the hot core, they may undergo subsequent (n,x) reactions. For example, 12C(n,n’γ)12C reactions occur in remnant debris from the polymer ablator resulting in a significant fluence of 4.44 MeV gamma-rays. Imaging of these gammas will enable the determination of the volumetric size and symmetry of the ablation; large size and high asymmetry is expected to correlate with poor compression and lower fusion yield. Results from a gamma-ray imaging system are expected to be complimentary to a neutron imaging diagnostic system already in place at the NIF. This paper describes initial efforts to design a gamma-ray imaging system for the NIF using the existing neutron imaging system as a baseline for study. Due to the cross-section and expected range of ablator areal densities, the gamma flux should be approximately 10−3 of the neutron flux. For this reason, care must be taken to maximize the efficiency of the gamma-ray imaging system because it will be gamma starved. As with the neutron imager, use of pinholes and/or coded apertures are anticipated. Along with aperture and detector design, the selection of an appropriate scintillator is discussed. The volume of energy deposition of the interacting 4.44 MeV gamma-rays is a critical parameter limiting the imaging system spatial resolution. The volume of energy deposition is simulated with GEANT4, and plans to measure the volume of energy deposition experimentally are described. Results of tests on a pixellated LYSO scintillator are also presented. PMID:23420688

Investigation of the possibility of gamma-ray diagnostic imaging of target compression at NIF

NASA Astrophysics Data System (ADS)

Lemieux, Daniel A.; Baudet, Camille; Grim, Gary P.; Barber, H. Bradford; Miller, Brian W.; Fasje, David; Furenlid, Lars R.

2011-09-01

The National Ignition Facility at Lawrence Livermore National Laboratory is the world's leading facility to study the physics of igniting plasmas. Plasmas of hot deuterium and tritium, undergo d(t,n)α reactions that produce a 14.1 MeV neutron and 3.5 MeV a particle, in the center of mass. As these neutrons pass through the materials surrounding the hot core, they may undergo subsequent (n,x) reactions. For example, 12C(n,n'γ)12C reactions occur in remnant debris from the polymer ablator resulting in a significant fluence of 4.44 MeV gamma-rays. Imaging of these gammas will enable the determination of the volumetric size and symmetry of the ablation; large size and high asymmetry is expected to correlate with poor compression and lower fusion yield. Results from a gamma-ray imaging system are expected to be complimentary to a neutron imaging diagnostic system already in place at the NIF. This paper describes initial efforts to design a gamma-ray imaging system for the NIF using the existing neutron imaging system as a baseline for study. Due to the cross-section and expected range of ablator areal densities, the gamma flux should be approximately 10-3 of the neutron flux. For this reason, care must be taken to maximize the efficiency of the gamma-ray imaging system because it will be gamma starved. As with the neutron imager, use of pinholes and/or coded apertures are anticipated. Along with aperture and detector design, the selection of an appropriate scintillator is discussed. The volume of energy deposition of the interacting 4.44 MeV gamma-rays is a critical parameter limiting the imaging system spatial resolution. The volume of energy deposition is simulated with GEANT4, and plans to measure the volume of energy deposition experimentally are described. Results of tests on a pixellated LYSO scintillator are also presented.

Investigation of the possibility of gamma-ray diagnostic imaging of target compression at NIF.

PubMed

Lemieux, Daniel A; Baudet, Camille; Grim, Gary P; Barber, H Bradford; Miller, Brian W; Fasje, David; Furenlid, Lars R

2011-09-23

The National Ignition Facility at Lawrence Livermore National Laboratory is the world's leading facility to study the physics of igniting plasmas. Plasmas of hot deuterium and tritium, undergo d(t,n)α reactions that produce a 14.1 MeV neutron and 3.5 MeV a particle, in the center of mass. As these neutrons pass through the materials surrounding the hot core, they may undergo subsequent (n,x) reactions. For example, (12)C(n,n'γ)(12)C reactions occur in remnant debris from the polymer ablator resulting in a significant fluence of 4.44 MeV gamma-rays. Imaging of these gammas will enable the determination of the volumetric size and symmetry of the ablation; large size and high asymmetry is expected to correlate with poor compression and lower fusion yield. Results from a gamma-ray imaging system are expected to be complimentary to a neutron imaging diagnostic system already in place at the NIF. This paper describes initial efforts to design a gamma-ray imaging system for the NIF using the existing neutron imaging system as a baseline for study. Due to the cross-section and expected range of ablator areal densities, the gamma flux should be approximately 10(-3) of the neutron flux. For this reason, care must be taken to maximize the efficiency of the gamma-ray imaging system because it will be gamma starved. As with the neutron imager, use of pinholes and/or coded apertures are anticipated. Along with aperture and detector design, the selection of an appropriate scintillator is discussed. The volume of energy deposition of the interacting 4.44 MeV gamma-rays is a critical parameter limiting the imaging system spatial resolution. The volume of energy deposition is simulated with GEANT4, and plans to measure the volume of energy deposition experimentally are described. Results of tests on a pixellated LYSO scintillator are also presented.

Fluid Flow Characterization of High Turbulent Intensity Compressible Flow Using Particle Image Velocimetry

DTIC Science & Technology

2015-08-01

completed in order to begin further experimentation. A 10 kHz Time Resolved Particle Image Velocimetry (TR-PIV) system and a 3 kHz Planer Laser ...9 2.3.2 Planar Laser Induced Fluorescence (PLIF...35 Figure 4.4: Solenoid valve (a), proportional control valve (b) and flowmeter (c) ...................................... 36 Figure 4.5

2D-pattern matching image and video compression: theory, algorithms, and experiments.

PubMed

Alzina, Marc; Szpankowski, Wojciech; Grama, Ananth

2002-01-01

In this paper, we propose a lossy data compression framework based on an approximate two-dimensional (2D) pattern matching (2D-PMC) extension of the Lempel-Ziv (1977, 1978) lossless scheme. This framework forms the basis upon which higher level schemes relying on differential coding, frequency domain techniques, prediction, and other methods can be built. We apply our pattern matching framework to image and video compression and report on theoretical and experimental results. Theoretically, we show that the fixed database model used for video compression leads to suboptimal but computationally efficient performance. The compression ratio of this model is shown to tend to the generalized entropy. For image compression, we use a growing database model for which we provide an approximate analysis. The implementation of 2D-PMC is a challenging problem from the algorithmic point of view. We use a range of techniques and data structures such as k-d trees, generalized run length coding, adaptive arithmetic coding, and variable and adaptive maximum distortion level to achieve good compression ratios at high compression speeds. We demonstrate bit rates in the range of 0.25-0.5 bpp for high-quality images and data rates in the range of 0.15-0.5 Mbps for a baseline video compression scheme that does not use any prediction or interpolation. We also demonstrate that this asymmetric compression scheme is capable of extremely fast decompression making it particularly suitable for networked multimedia applications.

Lossless and lossy compression of quantitative phase images of red blood cells obtained by digital holographic imaging.

PubMed

Jaferzadeh, Keyvan; Gholami, Samaneh; Moon, Inkyu

2016-12-20

In this paper, we evaluate lossless and lossy compression techniques to compress quantitative phase images of red blood cells (RBCs) obtained by an off-axis digital holographic microscopy (DHM). The RBC phase images are numerically reconstructed from their digital holograms and are stored in 16-bit unsigned integer format. In the case of lossless compression, predictive coding of JPEG lossless (JPEG-LS), JPEG2000, and JP3D are evaluated, and compression ratio (CR) and complexity (compression time) are compared against each other. It turns out that JP2k can outperform other methods by having the best CR. In the lossy case, JP2k and JP3D with different CRs are examined. Because some data is lost in a lossy way, the degradation level is measured by comparing different morphological and biochemical parameters of RBC before and after compression. Morphological parameters are volume, surface area, RBC diameter, sphericity index, and the biochemical cell parameter is mean corpuscular hemoglobin (MCH). Experimental results show that JP2k outperforms JP3D not only in terms of mean square error (MSE) when CR increases, but also in compression time in the lossy compression way. In addition, our compression results with both algorithms demonstrate that with high CR values the three-dimensional profile of RBC can be preserved and morphological and biochemical parameters can still be within the range of reported values.

A hierarchical storage management (HSM) scheme for cost-effective on-line archival using lossy compression.

PubMed

Avrin, D E; Andriole, K P; Yin, L; Gould, R G; Arenson, R L

2001-03-01

A hierarchical storage management (HSM) scheme for cost-effective on-line archival of image data using lossy compression is described. This HSM scheme also provides an off-site tape backup mechanism and disaster recovery. The full-resolution image data are viewed originally for primary diagnosis, then losslessly compressed and sent off site to a tape backup archive. In addition, the original data are wavelet lossy compressed (at approximately 25:1 for computed radiography, 10:1 for computed tomography, and 5:1 for magnetic resonance) and stored on a large RAID device for maximum cost-effective, on-line storage and immediate retrieval of images for review and comparison. This HSM scheme provides a solution to 4 problems in image archiving, namely cost-effective on-line storage, disaster recovery of data, off-site tape backup for the legal record, and maximum intermediate storage and retrieval through the use of on-site lossy compression.

Temporal compressive imaging for video

NASA Astrophysics Data System (ADS)

Zhou, Qun; Zhang, Linxia; Ke, Jun

2018-01-01

In many situations, imagers are required to have higher imaging speed, such as gunpowder blasting analysis and observing high-speed biology phenomena. However, measuring high-speed video is a challenge to camera design, especially, in infrared spectrum. In this paper, we reconstruct a high-frame-rate video from compressive video measurements using temporal compressive imaging (TCI) with a temporal compression ratio T=8. This means that, 8 unique high-speed temporal frames will be obtained from a single compressive frame using a reconstruction algorithm. Equivalently, the video frame rates is increased by 8 times. Two methods, two-step iterative shrinkage/threshold (TwIST) algorithm and the Gaussian mixture model (GMM) method, are used for reconstruction. To reduce reconstruction time and memory usage, each frame of size 256×256 is divided into patches of size 8×8. The influence of different coded mask to reconstruction is discussed. The reconstruction qualities using TwIST and GMM are also compared.

Correlation estimation and performance optimization for distributed image compression

NASA Astrophysics Data System (ADS)

He, Zhihai; Cao, Lei; Cheng, Hui

2006-01-01

Correlation estimation plays a critical role in resource allocation and rate control for distributed data compression. A Wyner-Ziv encoder for distributed image compression is often considered as a lossy source encoder followed by a lossless Slepian-Wolf encoder. The source encoder consists of spatial transform, quantization, and bit plane extraction. In this work, we find that Gray code, which has been extensively used in digital modulation, is able to significantly improve the correlation between the source data and its side information. Theoretically, we analyze the behavior of Gray code within the context of distributed image compression. Using this theoretical model, we are able to efficiently allocate the bit budget and determine the code rate of the Slepian-Wolf encoder. Our experimental results demonstrate that the Gray code, coupled with accurate correlation estimation and rate control, significantly improves the picture quality, by up to 4 dB, over the existing methods for distributed image compression.

Three-Dimensional Inverse Transport Solver Based on Compressive Sensing Technique

NASA Astrophysics Data System (ADS)

Cheng, Yuxiong; Wu, Hongchun; Cao, Liangzhi; Zheng, Youqi

2013-09-01

According to the direct exposure measurements from flash radiographic image, a compressive sensing-based method for three-dimensional inverse transport problem is presented. The linear absorption coefficients and interface locations of objects are reconstructed directly at the same time. It is always very expensive to obtain enough measurements. With limited measurements, compressive sensing sparse reconstruction technique orthogonal matching pursuit is applied to obtain the sparse coefficients by solving an optimization problem. A three-dimensional inverse transport solver is developed based on a compressive sensing-based technique. There are three features in this solver: (1) AutoCAD is employed as a geometry preprocessor due to its powerful capacity in graphic. (2) The forward projection matrix rather than Gauss matrix is constructed by the visualization tool generator. (3) Fourier transform and Daubechies wavelet transform are adopted to convert an underdetermined system to a well-posed system in the algorithm. Simulations are performed and numerical results in pseudo-sine absorption problem, two-cube problem and two-cylinder problem when using compressive sensing-based solver agree well with the reference value.

Application of a high-repetition-rate laser diagnostic system for single-cycle-resolved imaging in internal combustion engines.

PubMed

Hult, Johan; Richter, Mattias; Nygren, Jenny; Aldén, Marcus; Hultqvist, Anders; Christensen, Magnus; Johansson, Bengt

2002-08-20

High-repetition-rate laser-induced fluorescence measurements of fuel and OH concentrations in internal combustion engines are demonstrated. Series of as many as eight fluorescence images, with a temporal resolution ranging from 10 micros to 1 ms, are acquired within one engine cycle. A multiple-laser system in combination with a multiple-CCD camera is used for cycle-resolved imaging in spark-ignition, direct-injection stratified-charge, and homogeneous-charge compression-ignition engines. The recorded data reveal unique information on cycle-to-cycle variations in fuel transport and combustion. Moreover, the imaging system in combination with a scanning mirror is used to perform instantaneous three-dimensional fuel-concentration measurements.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

PubMed Central

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. PMID:23049544

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

PubMed

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

Diffusion tensor imaging with quantitative evaluation and fiber tractography of lumbar nerve roots in sciatica.

PubMed

Shi, Yin; Zong, Min; Xu, Xiaoquan; Zou, Yuefen; Feng, Yang; Liu, Wei; Wang, Chuanbing; Wang, Dehang

2015-04-01

To quantitatively evaluate nerve roots by measuring fractional anisotropy (FA) values in healthy volunteers and sciatica patients, visualize nerve roots by tractography, and compare the diagnostic efficacy between conventional magnetic resonance imaging (MRI) and DTI. Seventy-five sciatica patients and thirty-six healthy volunteers underwent MR imaging using DTI. FA values for L5-S1 lumbar nerve roots were calculated at three levels from DTI images. Tractography was performed on L3-S1 nerve roots. ROC analysis was performed for FA values. The lumbar nerve roots were visualized and FA values were calculated in all subjects. FA values decreased in compressed nerve roots and declined from proximal to distal along the compressed nerve tracts. Mean FA values were more sensitive and specific than MR imaging for differentiating compressed nerve roots, especially in the far lateral zone at distal nerves. DTI can quantitatively evaluate compressed nerve roots, and DTT enables visualization of abnormal nerve tracts, providing vivid anatomic information and localization of probable nerve compression. DTI has great potential utility for evaluating lumbar nerve compression in sciatica. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

NASA Technical Reports Server (NTRS)

Jayroe, R. R.

1994-01-01

Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available evaluation criteria basically compare the observed results with the expected results. For the image reconstruction processes of registration and compression, the expected results are usually the original data or some selected characteristics of the original data. For classification processes the expected result is the ground truth of the scene. Thus, the comparison process consists of determining what changes occur in processing, where the changes occur, how much change occurs, and the amplitude of the change. The package includes evaluation routines for performing such comparisons as average uncertainty, average information transfer, chi-square statistics, multidimensional histograms, and computation of contingency matrices. This collection of routines is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 662K of 8 bit bytes. This collection of image processing and evaluation routines was developed in 1979.

ICER-3D Hyperspectral Image Compression Software

NASA Technical Reports Server (NTRS)

Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

2010-01-01

Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received prior to the loss can be used to reconstruct that partition at lower fidelity. By virtue of the compression improvement it achieves relative to previous means of onboard data compression, this software enables (1) increased return of hyperspectral scientific data in the presence of limits on the rates of transmission of data from spacecraft to Earth via radio communication links and/or (2) reduction in spacecraft radio-communication power and/or cost through reduction in the amounts of data required to be downlinked and stored onboard prior to downlink. The software is also suitable for compressing hyperspectral images for ground storage or archival purposes.

Comparison of Open Source Compression Algorithms on Vhr Remote Sensing Images for Efficient Storage Hierarchy

NASA Astrophysics Data System (ADS)

Akoguz, A.; Bozkurt, S.; Gozutok, A. A.; Alp, G.; Turan, E. G.; Bogaz, M.; Kent, S.

2016-06-01

High resolution level in satellite imagery came with its fundamental problem as big amount of telemetry data which is to be stored after the downlink operation. Moreover, later the post-processing and image enhancement steps after the image is acquired, the file sizes increase even more and then it gets a lot harder to store and consume much more time to transmit the data from one source to another; hence, it should be taken into account that to save even more space with file compression of the raw and various levels of processed data is a necessity for archiving stations to save more space. Lossless data compression algorithms that will be examined in this study aim to provide compression without any loss of data holding spectral information. Within this objective, well-known open source programs supporting related compression algorithms have been implemented on processed GeoTIFF images of Airbus Defence & Spaces SPOT 6 & 7 satellites having 1.5 m. of GSD, which were acquired and stored by ITU Center for Satellite Communications and Remote Sensing (ITU CSCRS), with the algorithms Lempel-Ziv-Welch (LZW), Lempel-Ziv-Markov chain Algorithm (LZMA & LZMA2), Lempel-Ziv-Oberhumer (LZO), Deflate & Deflate 64, Prediction by Partial Matching (PPMd or PPM2), Burrows-Wheeler Transform (BWT) in order to observe compression performances of these algorithms over sample datasets in terms of how much of the image data can be compressed by ensuring lossless compression.

[Elastography as an additional tool in breast sonography. Technical principles and clinical applications].

PubMed

Rjosk-Dendorfer, D; Reichelt, A; Clevert, D-A

2014-03-01

In recent years the use of elastography in addition to sonography has become a routine clinical tool for the characterization of breast masses. Whereas free hand compression elastography results in qualitative imaging of tissue stiffness due to induced compression, shear wave elastography displays quantitative information of tissue displacement. Recent studies have investigated the use of elastography in addition to sonography and improvement of specificity in differentiating benign from malignant breast masses could be shown. Therefore, additional use of elastography could help to reduce the number of unnecessary biopsies in benign breast lesions especially in category IV lesions of the ultrasound breast imaging reporting data system (US-BI-RADS).

Cost-effective handling of digital medical images in the telemedicine environment.

PubMed

Choong, Miew Keen; Logeswaran, Rajasvaran; Bister, Michel

2007-09-01

This paper concentrates on strategies for less costly handling of medical images. Aspects of digitization using conventional digital cameras, lossy compression with good diagnostic quality, and visualization through less costly monitors are discussed. For digitization of film-based media, subjective evaluation of the suitability of digital cameras as an alternative to the digitizer was undertaken. To save on storage, bandwidth and transmission time, the acceptable degree of compression with diagnostically no loss of important data was studied through randomized double-blind tests of the subjective image quality when compression noise was kept lower than the inherent noise. A diagnostic experiment was undertaken to evaluate normal low cost computer monitors as viable viewing displays for clinicians. The results show that conventional digital camera images of X-ray images were diagnostically similar to the expensive digitizer. Lossy compression, when used moderately with the imaging noise to compression noise ratio (ICR) greater than four, can bring about image improvement with better diagnostic quality than the original image. Statistical analysis shows that there is no diagnostic difference between expensive high quality monitors and conventional computer monitors. The results presented show good potential in implementing the proposed strategies to promote widespread cost-effective telemedicine and digital medical environments. 2006 Elsevier Ireland Ltd

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

Compression of Encrypted Images Using Set Partitioning In Hierarchical Trees Algorithm

NASA Astrophysics Data System (ADS)

Sarika, G.; Unnithan, Harikuttan; Peter, Smitha

2011-10-01

When it is desired to transmit redundant data over an insecure channel, it is customary to encrypt the data. For encrypted real world sources such as images, the use of Markova properties in the slepian-wolf decoder does not work well for gray scale images. Here in this paper we propose a method of compression of an encrypted image. In the encoder section, the image is first encrypted and then it undergoes compression in resolution. The cipher function scrambles only the pixel values, but does not shuffle the pixel locations. After down sampling, each sub-image is encoded independently and the resulting syndrome bits are transmitted. The received image undergoes a joint decryption and decompression in the decoder section. By using the local statistics based on the image, it is recovered back. Here the decoder gets only lower resolution version of the image. In addition, this method provides only partial access to the current source at the decoder side, which improves the decoder's learning of the source statistics. The source dependency is exploited to improve the compression efficiency. This scheme provides better coding efficiency and less computational complexity.

Survey Of Lossless Image Coding Techniques

NASA Astrophysics Data System (ADS)

Melnychuck, Paul W.; Rabbani, Majid

1989-04-01

Many image transmission/storage applications requiring some form of data compression additionally require that the decoded image be an exact replica of the original. Lossless image coding algorithms meet this requirement by generating a decoded image that is numerically identical to the original. Several lossless coding techniques are modifications of well-known lossy schemes, whereas others are new. Traditional Markov-based models and newer arithmetic coding techniques are applied to predictive coding, bit plane processing, and lossy plus residual coding. Generally speaking, the compression ratio offered by these techniques are in the area of 1.6:1 to 3:1 for 8-bit pictorial images. Compression ratios for 12-bit radiological images approach 3:1, as these images have less detailed structure, and hence, their higher pel correlation leads to a greater removal of image redundancy.

Spectral Prior Image Constrained Compressed Sensing (Spectral PICCS) for Photon-Counting Computed Tomography

PubMed Central

Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.

2016-01-01

Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in-vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43~73%) without sacrificing CT number accuracy or spatial resolution. PMID:27551878

Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography

NASA Astrophysics Data System (ADS)

Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.

2016-09-01

Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43-73%) without sacrificing CT number accuracy or spatial resolution.

Pharmacokinetics of colon-specific pH and time-dependent flurbiprofen tablets.

PubMed

Vemula, Sateesh Kumar; Veerareddy, Prabhakar Reddy; Devadasu, Venkat Ratnam

2015-09-01

Present research deals with the development of compression-coated flurbiprofen colon-targeted tablets to retard the drug release in the upper gastro intestinal system, but progressively release the drug in the colon. Flurbiprofen core tablets were prepared by direct compression method and were compression coated using sodium alginate and Eudragit S100. The formulation is optimized based on the in vitro drug release study and further evaluated by X-ray imaging and pharmacokinetic studies in healthy humans for colonic delivery. The optimized formulation showed negligible drug release (4.33 ± 0.06 %) in the initial lag period followed by progressive release (100.78 ± 0.64 %) for 24 h. The X-ray imaging in human volunteers showed that the tablets reached the colon without disintegrating in the upper gastrointestinal tract. The C max of colon-targeted tablets was 12,374.67 ng/ml at T max 10 h, where as in case of immediate release tablets the C max was 15,677.52 ng/ml at T max 3 h, that signifies the ability of compression-coated tablets to target the colon. Development of compression-coated tablets using combination of time-dependent and pH-sensitive approaches was suitable to target the flurbiprofen to colon.

Anthropomorphic breast phantoms for preclinical imaging evaluation with transmission or emission imaging

NASA Astrophysics Data System (ADS)

Tornai, Martin P.; McKinley, Randolph L.; Bryzmialkiewicz, Caryl N.; Cutler, Spencer J.; Crotty, Dominic J.

2005-04-01

With the development of several classes of dedicated emission and transmission imaging technologies utilizing ionizing radiation for improved breast cancer detection and in vivo characterization, it is extremely useful to have available anthropomorphic breast phantoms in a variety of shapes, sizes and malleability prior to clinical imaging. These anthropomorphic phantoms can be used to evaluate the implemented imaging approaches given a known quantity, the phantom, and to evaluate the variability of the measurement due to the imaging system chain. Thus, we have developed a set of fillable and incompressible breast phantoms ranging in volume from 240 to 1730mL with nipple-to-chest distances from 3.8 to 12cm. These phantoms are mountable and exchangeable on either a uniform chest plate or anthropomorphic torso phantom containing tissue equivalent bones and surface tissue. Another fillable ~700mL breast phantom with solid anterior chest plate is intentionally compressible, and can be used for direct comparisons between standard planar imaging approaches using mild-to-severe compression, partially compressed tomosynthesis, and uncompressed computed mammotomography applications. These phantoms can be filled with various fluids (water and oil based liquids) to vary the fatty tissue background composition. Shaped cellulose sponges with two cell densities are fabricated and can be added to the breasts to simulate connective tissue. Additionally, microcalcifications can be simulated by peppering slits in the sponges with oyster shell fragments. These phantoms have a utility in helping to evaluate clinical imaging paradigms with known input object parameters using basic imaging characterization, in an effort to further evaluate contemporary and next generation imaging tools. They may additionally provide a means to collect known data samples for task based optimization studies.

Reliability analysis of the epidural spinal cord compression scale.

PubMed

Bilsky, Mark H; Laufer, Ilya; Fourney, Daryl R; Groff, Michael; Schmidt, Meic H; Varga, Peter Paul; Vrionis, Frank D; Yamada, Yoshiya; Gerszten, Peter C; Kuklo, Timothy R

2010-09-01

The evolution of imaging techniques, along with highly effective radiation options has changed the way metastatic epidural tumors are treated. While high-grade epidural spinal cord compression (ESCC) frequently serves as an indication for surgical decompression, no consensus exists in the literature about the precise definition of this term. The advancement of the treatment paradigms in patients with metastatic tumors for the spine requires a clear grading scheme of ESCC. The degree of ESCC often serves as a major determinant in the decision to operate or irradiate. The purpose of this study was to determine the reliability and validity of a 6-point, MR imaging-based grading system for ESCC. To determine the reliability of the grading scale, a survey was distributed to 7 spine surgeons who participate in the Spine Oncology Study Group. The MR images of 25 cervical or thoracic spinal tumors were distributed consisting of 1 sagittal image and 3 axial images at the identical level including T1-weighted, T2-weighted, and Gd-enhanced T1-weighted images. The survey was administered 3 times at 2-week intervals. The inter- and intrarater reliability was assessed. The inter- and intrarater reliability ranged from good to excellent when surgeons were asked to rate the degree of spinal cord compression using T2-weighted axial images. The T2-weighted images were superior indicators of ESCC compared with T1-weighted images with and without Gd. The ESCC scale provides a valid and reliable instrument that may be used to describe the degree of ESCC based on T2-weighted MR images. This scale accounts for recent advances in the treatment of spinal metastases and may be used to provide an ESCC classification scheme for multicenter clinical trial and outcome studies.

System and method for compressive scanning electron microscopy

DOEpatents

Reed, Bryan W

2015-01-13

A scanning transmission electron microscopy (STEM) system is disclosed. The system may make use of an electron beam scanning system configured to generate a plurality of electron beam scans over substantially an entire sample, with each scan varying in electron-illumination intensity over a course of the scan. A signal acquisition system may be used for obtaining at least one of an image, a diffraction pattern, or a spectrum from the scans, the image, diffraction pattern, or spectrum representing only information from at least one of a select subplurality or linear combination of all pixel locations comprising the image. A dataset may be produced from the information. A subsystem may be used for mathematically analyzing the dataset to predict actual information that would have been produced by each pixel location of the image.

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

NASA Technical Reports Server (NTRS)

Maki, Justin N.; Litwin, Todd; Herkenhoff, Ken

2005-01-01

This slide presentation details the Mars Exploration Rover (MER) imaging system. Over 144,000 images have been gathered from all Mars Missions, with 83.5% of them being gathered by MER. Each Rover has 9 cameras (Navcam, front and rear Hazcam, Pancam, Microscopic Image, Descent Camera, Engineering Camera, Science Camera) and produces 1024 x 1024 (1 Megapixel) images in the same format. All onboard image processing code is implemented in flight software and includes extensive processing capabilities such as autoexposure, flat field correction, image orientation, thumbnail generation, subframing, and image compression. Ground image processing is done at the Jet Propulsion Laboratory's Multimission Image Processing Laboratory using Video Image Communication and Retrieval (VICAR) while stereo processing (left/right pairs) is provided for raw image, radiometric correction; solar energy maps,triangulation (Cartesian 3-spaces) and slope maps.

Wavelet compression techniques for hyperspectral data

NASA Technical Reports Server (NTRS)

Evans, Bruce; Ringer, Brian; Yeates, Mathew

1994-01-01

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Modeling of video compression effects on target acquisition performance

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Preece, Bradley; Espinola, Richard L.

2009-05-01

The effect of video compression on image quality was investigated from the perspective of target acquisition performance modeling. Human perception tests were conducted recently at the U.S. Army RDECOM CERDEC NVESD, measuring identification (ID) performance on simulated military vehicle targets at various ranges. These videos were compressed with different quality and/or quantization levels utilizing motion JPEG, motion JPEG2000, and MPEG-4 encoding. To model the degradation on task performance, the loss in image quality is fit to an equivalent Gaussian MTF scaled by the Structural Similarity Image Metric (SSIM). Residual compression artifacts are treated as 3-D spatio-temporal noise. This 3-D noise is found by taking the difference of the uncompressed frame, with the estimated equivalent blur applied, and the corresponding compressed frame. Results show good agreement between the experimental data and the model prediction. This method has led to a predictive performance model for video compression by correlating various compression levels to particular blur and noise input parameters for NVESD target acquisition performance model suite.

Clinical efficacy of telemedicine in emergency radiotherapy for malignant spinal cord compression.

PubMed

Hashimoto, S; Shirato, H; Kaneko, K; Ooshio, W; Nishioka, T; Miyasaka, K

2001-09-01

The authors developed a Telecommunication-HElped Radiotherapy Planning and Information SysTem (THERAPIST), then estimated its clinical benefit in radiotherapy in district hospitals where consultation with the university hospital was required. The system consists of a personal computer with an image scanner and a digital camera, set up in district hospitals and directly connected via ISDN to an image server, and a treatment planning device set up in a university hospital. Image data and consultative reports are sent to the server. Radiation oncologists at the university hospital determine a treatment schedule and verify actual treatment fields. From 1998 to 1999, 12 patients with malignant spinal cord compression (MSCC) were treated by emergency radiotherapy with the help of this system. Image quality, transmission time, and cost benefit also were satisfactory for clinical use. The mean time between the onset of symptoms and the start of radiotherapy was reduced significantly from 7.1 days to 0.8 days (P < .05) by the introduction of the system. Five of 6 nonambulant patients became ambulant after the introduction of THERAPIST compared with 2 of 8 before the introduction of THERAPIST. The treatment outcome was significantly better after the introduction of the system (P < .05), and suggested to be beyond the international standard. The telecommunication-helped radiotherapy and information system was useful in emergency radiotherapy in district hospitals for patients with MSCC for whom consultation with experienced radiation oncologists at a university hospital was required.

Light intensity compressor

DOEpatents

Rushford, Michael C.

1990-02-06

In a system for recording images having vastly differing light intensities over the face of the image, a light intensity compressor is provided that utilizes the properties of twisted nematic liquid crystals to compress the image intensity. A photoconductor or photodiode material that is responsive to the wavelength of radiation being recorded is placed adjacent a layer of twisted nematic liquid crystal material. An electric potential applied to a pair of electrodes that are disposed outside of the liquid crystal/photoconductor arrangement to provide an electric field in the vicinity of the liquid crystal material. The electrodes are substantially transparent to the form of radiation being recorded. A pair of crossed polarizers are provided on opposite sides of the liquid crystal. The front polarizer linearly polarizes the light, while the back polarizer cooperates with the front polarizer and the liquid crystal material to compress the intensity of a viewed scene. Light incident upon the intensity compressor activates the photoconductor in proportion to the intensity of the light, thereby varying the field applied to the liquid crystal. The increased field causes the liquid crystal to have less of a twisting effect on the incident linearly polarized light, which will cause an increased percentage of the light to be absorbed by the back polarizer. The intensity of an image may be compressed by forming an image on the light intensity compressor.

Light intensity compressor

DOEpatents

Rushford, Michael C.

1990-01-01

In a system for recording images having vastly differing light intensities over the face of the image, a light intensity compressor is provided that utilizes the properties of twisted nematic liquid crystals to compress the image intensity. A photoconductor or photodiode material that is responsive to the wavelength of radiation being recorded is placed adjacent a layer of twisted nematic liquid crystal material. An electric potential applied to a pair of electrodes that are disposed outside of the liquid crystal/photoconductor arrangement to provide an electric field in the vicinity of the liquid crystal material. The electrodes are substantially transparent to the form of radiation being recorded. A pair of crossed polarizers are provided on opposite sides of the liquid crystal. The front polarizer linearly polarizes the light, while the back polarizer cooperates with the front polarizer and the liquid crystal material to compress the intensity of a viewed scene. Light incident upon the intensity compressor activates the photoconductor in proportion to the intensity of the light, thereby varying the field applied to the liquid crystal. The increased field causes the liquid crystal to have less of a twisting effect on the incident linearly polarized light, which will cause an increased percentage of the light to be absorbed by the back polarizer. The intensity of an image may be compressed by forming an image on the light intensity compressor.