A Test Data Compression Scheme Based on Irrational Numbers Stored Coding

Directory of Open Access Journals (Sweden)

Hai-feng Wu

2014-01-01

Full Text Available Test question has already become an important factor to restrict the development of integrated circuit industry. A new test data compression scheme, namely irrational numbers stored (INS, is presented. To achieve the goal of compress test data efficiently, test data is converted into floating-point numbers, stored in the form of irrational numbers. The algorithm of converting floating-point number to irrational number precisely is given. Experimental results for some ISCAS 89 benchmarks show that the compression effect of proposed scheme is better than the coding methods such as FDR, AARLC, INDC, FAVLC, and VRL.

Wavelet-based audio embedding and audio/video compression

Science.gov (United States)

Mendenhall, Michael J.; Claypoole, Roger L., Jr.

2001-12-01

Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit-plane coding, index coding, and Huffman coding. To demonstrate the potential of this audio embedding and audio/video compression algorithm, we embed an audio signal into a video signal and then compress. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33 dB. Finally, the audio signal is extracted from the compressed audio/video signal without error.

Wavelet-based compression of pathological images for telemedicine applications

Science.gov (United States)

Chen, Chang W.; Jiang, Jianfei; Zheng, Zhiyong; Wu, Xue G.; Yu, Lun

2000-05-01

In this paper, we present the performance evaluation of wavelet-based coding techniques as applied to the compression of pathological images for application in an Internet-based telemedicine system. We first study how well suited the wavelet-based coding is as it applies to the compression of pathological images, since these images often contain fine textures that are often critical to the diagnosis of potential diseases. We compare the wavelet-based compression with the DCT-based JPEG compression in the DICOM standard for medical imaging applications. Both objective and subjective measures have been studied in the evaluation of compression performance. These studies are performed in close collaboration with expert pathologists who have conducted the evaluation of the compressed pathological images and communication engineers and information scientists who designed the proposed telemedicine system. These performance evaluations have shown that the wavelet-based coding is suitable for the compression of various pathological images and can be integrated well with the Internet-based telemedicine systems. A prototype of the proposed telemedicine system has been developed in which the wavelet-based coding is adopted for the compression to achieve bandwidth efficient transmission and therefore speed up the communications between the remote terminal and the central server of the telemedicine system.

Telemetry advances in data compression and channel coding

Science.gov (United States)

Miller, Warner H.; Morakis, James C.; Yeh, Pen-Shu

1990-01-01

Addressed in this paper is the dependence of telecommunication channel, forward error correcting coding and source data compression coding on integrated circuit technology. Emphasis is placed on real time high speed Reed Solomon (RS) decoding using full custom VLSI technology. Performance curves of NASA's standard channel coder and a proposed standard lossless data compression coder are presented.

Bit-Wise Arithmetic Coding For Compression Of Data

Science.gov (United States)

Kiely, Aaron

1996-01-01

Bit-wise arithmetic coding is data-compression scheme intended especially for use with uniformly quantized data from source with Gaussian, Laplacian, or similar probability distribution function. Code words of fixed length, and bits treated as being independent. Scheme serves as means of progressive transmission or of overcoming buffer-overflow or rate constraint limitations sometimes arising when data compression used.

Coding For Compression Of Low-Entropy Data

Science.gov (United States)

Yeh, Pen-Shu

1994-01-01

Improved method of encoding digital data provides for efficient lossless compression of partially or even mostly redundant data from low-information-content source. Method of coding implemented in relatively simple, high-speed arithmetic and logic circuits. Also increases coding efficiency beyond that of established Huffman coding method in that average number of bits per code symbol can be less than 1, which is the lower bound for Huffman code.

Compressed Domain Packet Loss Concealment of Sinusoidally Coded Speech

DEFF Research Database (Denmark)

Rødbro, Christoffer A.; Christensen, Mads Græsbøll; Andersen, Søren Vang

2003-01-01

We consider the problem of packet loss concealment for voice over IP (VoIP). The speech signal is compressed at the transmitter using a sinusoidal coding scheme working at 8 kbit/s. At the receiver, packet loss concealment is carried out working directly on the quantized sinusoidal parameters......, based on time-scaling of the packets surrounding the missing ones. Subjective listening tests show promising results indicating the potential of sinusoidal speech coding for VoIP....

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Ran Li

2018-04-01

Full Text Available 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.

Development of Ultrasonic Pulse Compression Using Golay Codes

International Nuclear Information System (INIS)

Kim, Young H.; Kim, Young Gil; Jeong, Peter

1994-01-01

Conventional ultrasonic flaw detection system uses a large amplitude narrow pulse to excite a transducer. However, these systems are limited in pulse energy. An excessively large amplitude causes a dielectric breakage of the transducer, and an excessively long pulse causes decrease of the resolution. Using the pulse compression, a long pulse of pseudorandom signal can be used without sacrificing resolution by signal correlation. In the present work, the pulse compression technique was implemented into an ultrasonic system. Golay code was used as a pseudorandom signal in this system, since pair sum of autocorrelations has no sidelobe. The equivalent input pulse of the Golay code was derived to analyze the pulse compression system. Throughout the experiment, the pulse compression technique has demonstrated for its improved SNR(signal to noise ratio) by reducing the system's white noise. And the experimental data also indicated that the SNR enhancement was proportional to the square root of the code length used. The technique seems to perform particularly well with highly energy-absorbent materials such as polymers, plastics and rubbers

SNR in ultrasonic pluse compression using Golay codes

International Nuclear Information System (INIS)

Kim, Young Hwan; Kim, Young Gil; Jeong, Peter

1994-01-01

The conventional ultrasonic flaw detection system uses a large amplitude narrow pulse to excite a transducer, however, these systems are limited in average transmit power. An excessively large amplitude causes a dielectric breakage of the transducer, and an excessively long pulse cuases decrease of the resolution. Using the pulse compression, a long pulse of psudorandom signal can be used without sacrificing resolution by signal correlation. In the present work, the pulse compression technique was utilized to the ultrasonic system. Golay code was used as a psudorandom signal in this system, since pair sum of auto-correlations has not sidelobe. The equivalent input pulse of the Golay code was proposed to analyze the pulse compression system. In experiment, the material type, material thickness and code length were considered. As results, pulse compression system considerably reduced system's white noise, and approximately 30 dB improvement in SNR was obtained over the conventional ultrasonic system. The technique seems to perform particularly well with highly energy-absorbent materials such as polymers, plastics and rubbers.

MAP-MRF-Based Super-Resolution Reconstruction Approach for Coded Aperture Compressive Temporal Imaging

Directory of Open Access Journals (Sweden)

Tinghua Zhang

2018-02-01

Full Text Available Coded Aperture Compressive Temporal Imaging (CACTI can afford low-cost temporal super-resolution (SR, but limits are imposed by noise and compression ratio on reconstruction quality. To utilize inter-frame redundant information from multiple observations and sparsity in multi-transform domains, a robust reconstruction approach based on maximum a posteriori probability and Markov random field (MAP-MRF model for CACTI is proposed. The proposed approach adopts a weighted 3D neighbor system (WNS and the coordinate descent method to perform joint estimation of model parameters, to achieve the robust super-resolution reconstruction. The proposed multi-reconstruction algorithm considers both total variation (TV and ℓ 2 , 1 norm in wavelet domain to address the minimization problem for compressive sensing, and solves it using an accelerated generalized alternating projection algorithm. The weighting coefficient for different regularizations and frames is resolved by the motion characteristics of pixels. The proposed approach can provide high visual quality in the foreground and background of a scene simultaneously and enhance the fidelity of the reconstruction results. Simulation results have verified the efficacy of our new optimization framework and the proposed reconstruction approach.

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

Science.gov (United States)

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.

Entropy, Coding and Data Compression

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 6; Issue 9. Entropy, Coding and Data Compression. S Natarajan. General Article Volume 6 Issue 9 September 2001 pp 35-45. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/006/09/0035-0045 ...

SRComp: short read sequence compression using burstsort and Elias omega coding.

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Jeremy John Selva

Full Text Available Next-generation sequencing (NGS technologies permit the rapid production of vast amounts of data at low cost. Economical data storage and transmission hence becomes an increasingly important challenge for NGS experiments. In this paper, we introduce a new non-reference based read sequence compression tool called SRComp. It works by first employing a fast string-sorting algorithm called burstsort to sort read sequences in lexicographical order and then Elias omega-based integer coding to encode the sorted read sequences. SRComp has been benchmarked on four large NGS datasets, where experimental results show that it can run 5-35 times faster than current state-of-the-art read sequence compression tools such as BEETL and SCALCE, while retaining comparable compression efficiency for large collections of short read sequences. SRComp is a read sequence compression tool that is particularly valuable in certain applications where compression time is of major concern.

Coding Strategies and Implementations of Compressive Sensing

Science.gov (United States)

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

Optical identity authentication technique based on compressive ghost imaging with QR code

Science.gov (United States)

Wenjie, Zhan; Leihong, Zhang; Xi, Zeng; Yi, Kang

2018-04-01

With the rapid development of computer technology, information security has attracted more and more attention. It is not only related to the information and property security of individuals and enterprises, but also to the security and social stability of a country. Identity authentication is the first line of defense in information security. In authentication systems, response time and security are the most important factors. An optical authentication technology based on compressive ghost imaging with QR codes is proposed in this paper. The scheme can be authenticated with a small number of samples. Therefore, the response time of the algorithm is short. At the same time, the algorithm can resist certain noise attacks, so it offers good security.

Development of 1D Liner Compression Code for IDL

Science.gov (United States)

Shimazu, Akihisa; Slough, John; Pancotti, Anthony

2015-11-01

A 1D liner compression code is developed to model liner implosion dynamics in the Inductively Driven Liner Experiment (IDL) where FRC plasmoid is compressed via inductively-driven metal liners. The driver circuit, magnetic field, joule heating, and liner dynamics calculations are performed at each time step in sequence to couple these effects in the code. To obtain more realistic magnetic field results for a given drive coil geometry, 2D and 3D effects are incorporated into the 1D field calculation through use of correction factor table lookup approach. Commercial low-frequency electromagnetic fields solver, ANSYS Maxwell 3D, is used to solve the magnetic field profile for static liner condition at various liner radius in order to derive correction factors for the 1D field calculation in the code. The liner dynamics results from the code is verified to be in good agreement with the results from commercial explicit dynamics solver, ANSYS Explicit Dynamics, and previous liner experiment. The developed code is used to optimize the capacitor bank and driver coil design for better energy transfer and coupling. FRC gain calculations are also performed using the liner compression data from the code for the conceptual design of the reactor sized system for fusion energy gains.

Bi-level image compression with tree coding

DEFF Research Database (Denmark)

Martins, Bo; Forchhammer, Søren

1996-01-01

Presently, tree coders are the best bi-level image coders. The current ISO standard, JBIG, is a good example. By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code. Three general-purpose coders...... are constructed by this principle. A multi-pass free tree coding scheme produces superior compression results for all test images. A multi-pass fast free template coding scheme produces much better results than JBIG for difficult images, such as halftonings. Rissanen's algorithm `Context' is presented in a new...

High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

Directory of Open Access Journals (Sweden)

Nelson Eduardo Diaz

2015-09-01

Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed.  In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

On the Representation of Aquifer Compressibility in General Subsurface Flow Codes: How an Alternate Definition of Aquifer Compressibility Matches Results from the Groundwater Flow Equation

Science.gov (United States)

Birdsell, D.; Karra, S.; Rajaram, H.

2017-12-01

The governing equations for subsurface flow codes in deformable porous media are derived from the fluid mass balance equation. One class of these codes, which we call general subsurface flow (GSF) codes, does not explicitly track the motion of the solid porous media but does accept general constitutive relations for porosity, density, and fluid flux. Examples of GSF codes include PFLOTRAN, FEHM, STOMP, and TOUGH2. Meanwhile, analytical and numerical solutions based on the groundwater flow equation have assumed forms for porosity, density, and fluid flux. We review the derivation of the groundwater flow equation, which uses the form of Darcy's equation that accounts for the velocity of fluids with respect to solids and defines the soil matrix compressibility accordingly. We then show how GSF codes have a different governing equation if they use the form of Darcy's equation that is written only in terms of fluid velocity. The difference is seen in the porosity change, which is part of the specific storage term in the groundwater flow equation. We propose an alternative definition of soil matrix compressibility to correct for the untracked solid velocity. Simulation results show significantly less error for our new compressibility definition than the traditional compressibility when compared to analytical solutions from the groundwater literature. For example, the error in one calculation for a pumped sandstone aquifer goes from 940 to <70 Pa when the new compressibility is used. Code users and developers need to be aware of assumptions in the governing equations and constitutive relations in subsurface flow codes, and our newly-proposed compressibility function should be incorporated into GSF codes.

Image Compression Based On Wavelet, Polynomial and Quadtree

Directory of Open Access Journals (Sweden)

Bushra A. SULTAN

2011-01-01

Full Text Available In this paper a simple and fast image compression scheme is proposed, it is based on using wavelet transform to decompose the image signal and then using polynomial approximation to prune the smoothing component of the image band. The architect of proposed coding scheme is high synthetic where the error produced due to polynomial approximation in addition to the detail sub-band data are coded using both quantization and Quadtree spatial coding. As a last stage of the encoding process shift encoding is used as a simple and efficient entropy encoder to compress the outcomes of the previous stage.The test results indicate that the proposed system can produce a promising compression performance while preserving the image quality level.

Parallelization of one image compression method. Wavelet, Transform, Vector Quantization and Huffman Coding

International Nuclear Information System (INIS)

Moravie, Philippe

1997-01-01

Today, in the digitized satellite image domain, the needs for high dimension increase considerably. To transmit or to stock such images (more than 6000 by 6000 pixels), we need to reduce their data volume and so we have to use real-time image compression techniques. The large amount of computations required by image compression algorithms prohibits the use of common sequential processors, for the benefits of parallel computers. The study presented here deals with parallelization of a very efficient image compression scheme, based on three techniques: Wavelets Transform (WT), Vector Quantization (VQ) and Entropic Coding (EC). First, we studied and implemented the parallelism of each algorithm, in order to determine the architectural characteristics needed for real-time image compression. Then, we defined eight parallel architectures: 3 for Mallat algorithm (WT), 3 for Tree-Structured Vector Quantization (VQ) and 2 for Huffman Coding (EC). As our system has to be multi-purpose, we chose 3 global architectures between all of the 3x3x2 systems available. Because, for technological reasons, real-time is not reached at anytime (for all the compression parameter combinations), we also defined and evaluated two algorithmic optimizations: fix point precision and merging entropic coding in vector quantization. As a result, we defined a new multi-purpose multi-SMIMD parallel machine, able to compress digitized satellite image in real-time. The definition of the best suited architecture for real-time image compression was answered by presenting 3 parallel machines among which one multi-purpose, embedded and which might be used for other applications on board. (author) [fr

Optimization of multi-phase compressible lattice Boltzmann codes on massively parallel multi-core systems

NARCIS (Netherlands)

Biferale, L.; Mantovani, F.; Pivanti, M.; Pozzati, F.; Sbragaglia, M.; Schifano, S.F.; Toschi, F.; Tripiccione, R.

2011-01-01

We develop a Lattice Boltzmann code for computational fluid-dynamics and optimize it for massively parallel systems based on multi-core processors. Our code describes 2D multi-phase compressible flows. We analyze the performance bottlenecks that we find as we gradually expose a larger fraction of

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

Science.gov (United States)

Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Development of compressible density-based steam explosion simulation code ESE-2

International Nuclear Information System (INIS)

Leskovar, M.

2004-01-01

A steam explosion is a fuel coolant interaction process by which the energy of the corium is transferred to water in a time-scale smaller than the time-scale for system pressure relief and induces dynamic loading of surrounding structures. A strong enough steam explosion in a nuclear power plant could jeopardize the containment integrity and so lead to a direct release of radioactive material to the environment. To help finding answers on open questions regarding steam explosion understanding and modelling, the steam explosion simulation code ESE-2 is being developed. In contrast to the developed simulation code ESE-1, where the multiphase flow equations are solved with pressure-based numerical methods (best suited for incompressible flow), in ESE-2 densitybased numerical methods (best suited for compressible flow) are used. Therefore ESE-2 will enable an accurate treatment of the whole steam explosion process, which consists of the premixing, triggering, propagation and expansion phase. In the paper the basic characteristics of the mathematical model and the numerical solution procedure in ESE-2 are described. The essence of the numerical treatment is that the convective terms in the multiphase flow equations are calculated with the AUSM+ scheme, which is very time efficient since no field-by-field wave decomposition is needed, using second order accurate discretization. (author)

A statistical–mechanical view on source coding: physical compression and data compression

International Nuclear Information System (INIS)

Merhav, Neri

2011-01-01

We draw a certain analogy between the classical information-theoretic problem of lossy data compression (source coding) of memoryless information sources and the statistical–mechanical behavior of a certain model of a chain of connected particles (e.g. a polymer) that is subjected to a contracting force. The free energy difference pertaining to such a contraction turns out to be proportional to the rate-distortion function in the analogous data compression model, and the contracting force is proportional to the derivative of this function. Beyond the fact that this analogy may be interesting in its own right, it may provide a physical perspective on the behavior of optimum schemes for lossy data compression (and perhaps also an information-theoretic perspective on certain physical system models). Moreover, it triggers the derivation of lossy compression performance for systems with memory, using analysis tools and insights from statistical mechanics

HVS-based medical image compression

Energy Technology Data Exchange (ETDEWEB)

Kai Xie [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)]. E-mail: xie_kai2001@sjtu.edu.cn; Jie Yang [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China); Min Zhuyue [CREATIS-CNRS Research Unit 5515 and INSERM Unit 630, 69621 Villeurbanne (France); Liang Lixiao [Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 200030 Shanghai (China)

2005-07-01

Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time.

HVS-based medical image compression

International Nuclear Information System (INIS)

Kai Xie; Jie Yang; Min Zhuyue; Liang Lixiao

2005-01-01

Introduction: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. Methods: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. Results: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. Conclusions: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time

A Review on Block Matching Motion Estimation and Automata Theory based Approaches for Fractal Coding

Directory of Open Access Journals (Sweden)

Shailesh Kamble

2016-12-01

Full Text Available Fractal compression is the lossy compression technique in the field of gray/color image and video compression. It gives high compression ratio, better image quality with fast decoding time but improvement in encoding time is a challenge. This review paper/article presents the analysis of most significant existing approaches in the field of fractal based gray/color images and video compression, different block matching motion estimation approaches for finding out the motion vectors in a frame based on inter-frame coding and intra-frame coding i.e. individual frame coding and automata theory based coding approaches to represent an image/sequence of images. Though different review papers exist related to fractal coding, this paper is different in many sense. One can develop the new shape pattern for motion estimation and modify the existing block matching motion estimation with automata coding to explore the fractal compression technique with specific focus on reducing the encoding time and achieving better image/video reconstruction quality. This paper is useful for the beginners in the domain of video compression.

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

Science.gov (United States)

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.

Research on compressive sensing reconstruction algorithm based on total variation model

Science.gov (United States)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

An Implementation Of Elias Delta Code And ElGamal Algorithm In Image Compression And Security

Science.gov (United States)

Rachmawati, Dian; Andri Budiman, Mohammad; Saffiera, Cut Amalia

2018-01-01

In data transmission such as transferring an image, confidentiality, integrity, and efficiency of data storage aspects are highly needed. To maintain the confidentiality and integrity of data, one of the techniques used is ElGamal. The strength of this algorithm is found on the difficulty of calculating discrete logs in a large prime modulus. ElGamal belongs to the class of Asymmetric Key Algorithm and resulted in enlargement of the file size, therefore data compression is required. Elias Delta Code is one of the compression algorithms that use delta code table. The image was first compressed using Elias Delta Code Algorithm, then the result of the compression was encrypted by using ElGamal algorithm. Prime test was implemented using Agrawal Biswas Algorithm. The result showed that ElGamal method could maintain the confidentiality and integrity of data with MSE and PSNR values 0 and infinity. The Elias Delta Code method generated compression ratio and space-saving each with average values of 62.49%, and 37.51%.

Single stock dynamics on high-frequency data: from a compressed coding perspective.

Directory of Open Access Journals (Sweden)

Hsieh Fushing

Full Text Available High-frequency return, trading volume and transaction number are digitally coded via a nonparametric computing algorithm, called hierarchical factor segmentation (HFS, and then are coupled together to reveal a single stock dynamics without global state-space structural assumptions. The base-8 digital coding sequence, which is capable of revealing contrasting aggregation against sparsity of extreme events, is further compressed into a shortened sequence of state transitions. This compressed digital code sequence vividly demonstrates that the aggregation of large absolute returns is the primary driving force for stimulating both the aggregations of large trading volumes and transaction numbers. The state of system-wise synchrony is manifested with very frequent recurrence in the stock dynamics. And this data-driven dynamic mechanism is seen to correspondingly vary as the global market transiting in and out of contraction-expansion cycles. These results not only elaborate the stock dynamics of interest to a fuller extent, but also contradict some classical theories in finance. Overall this version of stock dynamics is potentially more coherent and realistic, especially when the current financial market is increasingly powered by high-frequency trading via computer algorithms, rather than by individual investors.

Wavelet-based compression with ROI coding support for mobile access to DICOM images over heterogeneous radio networks.

Science.gov (United States)

Maglogiannis, Ilias; Doukas, Charalampos; Kormentzas, George; Pliakas, Thomas

2009-07-01

Most of the commercial medical image viewers do not provide scalability in image compression and/or region of interest (ROI) encoding/decoding. Furthermore, these viewers do not take into consideration the special requirements and needs of a heterogeneous radio setting that is constituted by different access technologies [e.g., general packet radio services (GPRS)/ universal mobile telecommunications system (UMTS), wireless local area network (WLAN), and digital video broadcasting (DVB-H)]. This paper discusses a medical application that contains a viewer for digital imaging and communications in medicine (DICOM) images as a core module. The proposed application enables scalable wavelet-based compression, retrieval, and decompression of DICOM medical images and also supports ROI coding/decoding. Furthermore, the presented application is appropriate for use by mobile devices activating in heterogeneous radio settings. In this context, performance issues regarding the usage of the proposed application in the case of a prototype heterogeneous system setup are also discussed.

DNABIT Compress - Genome compression algorithm.

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-22

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, "DNABIT Compress" for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that "DNABIT Compress" algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases.

Code compression for VLIW embedded processors

Science.gov (United States)

Piccinelli, Emiliano; Sannino, Roberto

2004-04-01

The implementation of processors for embedded systems implies various issues: main constraints are cost, power dissipation and die area. On the other side, new terminals perform functions that require more computational flexibility and effort. Long code streams must be loaded into memories, which are expensive and power consuming, to run on DSPs or CPUs. To overcome this issue, the "SlimCode" proprietary algorithm presented in this paper (patent pending technology) can reduce the dimensions of the program memory. It can run offline and work directly on the binary code the compiler generates, by compressing it and creating a new binary file, about 40% smaller than the original one, to be loaded into the program memory of the processor. The decompression unit will be a small ASIC, placed between the Memory Controller and the System bus of the processor, keeping unchanged the internal CPU architecture: this implies that the methodology is completely transparent to the core. We present comparisons versus the state-of-the-art IBM Codepack algorithm, along with its architectural implementation into the ST200 VLIW family core.

Medical Ultrasound Video Coding with H.265/HEVC Based on ROI Extraction.

Science.gov (United States)

Wu, Yueying; Liu, Pengyu; Gao, Yuan; Jia, Kebin

2016-01-01

High-efficiency video compression technology is of primary importance to the storage and transmission of digital medical video in modern medical communication systems. To further improve the compression performance of medical ultrasound video, two innovative technologies based on diagnostic region-of-interest (ROI) extraction using the high efficiency video coding (H.265/HEVC) standard are presented in this paper. First, an effective ROI extraction algorithm based on image textural features is proposed to strengthen the applicability of ROI detection results in the H.265/HEVC quad-tree coding structure. Second, a hierarchical coding method based on transform coefficient adjustment and a quantization parameter (QP) selection process is designed to implement the otherness encoding for ROIs and non-ROIs. Experimental results demonstrate that the proposed optimization strategy significantly improves the coding performance by achieving a BD-BR reduction of 13.52% and a BD-PSNR gain of 1.16 dB on average compared to H.265/HEVC (HM15.0). The proposed medical video coding algorithm is expected to satisfy low bit-rate compression requirements for modern medical communication systems.

Medical Ultrasound Video Coding with H.265/HEVC Based on ROI Extraction.

Directory of Open Access Journals (Sweden)

Yueying Wu

Full Text Available High-efficiency video compression technology is of primary importance to the storage and transmission of digital medical video in modern medical communication systems. To further improve the compression performance of medical ultrasound video, two innovative technologies based on diagnostic region-of-interest (ROI extraction using the high efficiency video coding (H.265/HEVC standard are presented in this paper. First, an effective ROI extraction algorithm based on image textural features is proposed to strengthen the applicability of ROI detection results in the H.265/HEVC quad-tree coding structure. Second, a hierarchical coding method based on transform coefficient adjustment and a quantization parameter (QP selection process is designed to implement the otherness encoding for ROIs and non-ROIs. Experimental results demonstrate that the proposed optimization strategy significantly improves the coding performance by achieving a BD-BR reduction of 13.52% and a BD-PSNR gain of 1.16 dB on average compared to H.265/HEVC (HM15.0. The proposed medical video coding algorithm is expected to satisfy low bit-rate compression requirements for modern medical communication systems.

JPEG2000 COMPRESSION CODING USING HUMAN VISUAL SYSTEM MODEL

Institute of Scientific and Technical Information of China (English)

Xiao Jiang; Wu Chengke

2005-01-01

In order to apply the Human Visual System (HVS) model to JPEG2000 standard,several implementation alternatives are discussed and a new scheme of visual optimization isintroduced with modifying the slope of rate-distortion. The novelty is that the method of visual weighting is not lifting the coefficients in wavelet domain, but is complemented by code stream organization. It remains all the features of Embedded Block Coding with Optimized Truncation (EBCOT) such as resolution progressive, good robust for error bit spread and compatibility of lossless compression. Well performed than other methods, it keeps the shortest standard codestream and decompression time and owns the ability of VIsual Progressive (VIP) coding.

Edge-preserving Intra Depth Coding based on Context-coding and H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Salmistraro, Matteo; Forchhammer, Søren

2013-01-01

Depth map coding plays a crucial role in 3D Video communication systems based on the “Multi-view Video plus Depth” representation as view synthesis performance is strongly affected by the accuracy of depth information, especially at edges in the depth map image. In this paper an efficient algorithm...... for edge-preserving intra depth compression based on H.264/AVC is presented. The proposed method introduces a new Intra mode specifically targeted to depth macroblocks with arbitrarily shaped edges, which are typically not efficiently represented by DCT. Edge macroblocks are partitioned into two regions...... each approximated by a flat surface. Edge information is encoded by means of contextcoding with an adaptive template. As a novel element, the proposed method allows exploiting the edge structure of previously encoded edge macroblocks during the context-coding step to further increase compression...

DNABIT Compress – Genome compression algorithm

Science.gov (United States)

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-01

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, “DNABIT Compress” for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our proposed algorithm achieves the best compression ratio for DNA sequences for larger genome. Significantly better compression results show that “DNABIT Compress” algorithm is the best among the remaining compression algorithms. While achieving the best compression ratios for DNA sequences (Genomes),our new DNABIT Compress algorithm significantly improves the running time of all previous DNA compression programs. Assigning binary bits (Unique BIT CODE) for (Exact Repeats, Reverse Repeats) fragments of DNA sequence is also a unique concept introduced in this algorithm for the first time in DNA compression. This proposed new algorithm could achieve the best compression ratio as much as 1.58 bits/bases where the existing best methods could not achieve a ratio less than 1.72 bits/bases. PMID:21383923

On-Chip Neural Data Compression Based On Compressed Sensing With Sparse Sensing Matrices.

Science.gov (United States)

Zhao, Wenfeng; Sun, Biao; Wu, Tong; Yang, Zhi

2018-02-01

On-chip neural data compression is an enabling technique for wireless neural interfaces that suffer from insufficient bandwidth and power budgets to transmit the raw data. The data compression algorithm and its implementation should be power and area efficient and functionally reliable over different datasets. Compressed sensing is an emerging technique that has been applied to compress various neurophysiological data. However, the state-of-the-art compressed sensing (CS) encoders leverage random but dense binary measurement matrices, which incur substantial implementation costs on both power and area that could offset the benefits from the reduced wireless data rate. In this paper, we propose two CS encoder designs based on sparse measurement matrices that could lead to efficient hardware implementation. Specifically, two different approaches for the construction of sparse measurement matrices, i.e., the deterministic quasi-cyclic array code (QCAC) matrix and -sparse random binary matrix [-SRBM] are exploited. We demonstrate that the proposed CS encoders lead to comparable recovery performance. And efficient VLSI architecture designs are proposed for QCAC-CS and -SRBM encoders with reduced area and total power consumption.

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

Science.gov (United States)

Mojica, Edson; Pertuz, Said; Arguello, Henry

2017-12-01

One of the main challenges in Computed Tomography (CT) is obtaining accurate reconstructions of the imaged object while keeping a low radiation dose in the acquisition process. In order to solve this problem, several researchers have proposed the use of compressed sensing for reducing the amount of measurements required to perform CT. This paper tackles the problem of designing high-resolution coded apertures for compressed sensing computed tomography. In contrast to previous approaches, we aim at designing apertures to be used with low-resolution detectors in order to achieve super-resolution. The proposed method iteratively improves random coded apertures using a gradient descent algorithm subject to constraints in the coherence and homogeneity of the compressive sensing matrix induced by the coded aperture. Experiments with different test sets show consistent results for different transmittances, number of shots and super-resolution factors.

Channel coding/decoding alternatives for compressed TV data on advanced planetary missions.

Science.gov (United States)

Rice, R. F.

1972-01-01

The compatibility of channel coding/decoding schemes with a specific TV compressor developed for advanced planetary missions is considered. Under certain conditions, it is shown that compressed data can be transmitted at approximately the same rate as uncompressed data without any loss in quality. Thus, the full gains of data compression can be achieved in real-time transmission.

Tools for signal compression applications to speech and audio coding

CERN Document Server

Moreau, Nicolas

2013-01-01

This book presents tools and algorithms required to compress/uncompress signals such as speech and music. These algorithms are largely used in mobile phones, DVD players, HDTV sets, etc. In a first rather theoretical part, this book presents the standard tools used in compression systems: scalar and vector quantization, predictive quantization, transform quantization, entropy coding. In particular we show the consistency between these different tools. The second part explains how these tools are used in the latest speech and audio coders. The third part gives Matlab programs simulating t

Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

Directory of Open Access Journals (Sweden)

Jin Li

2014-01-01

Full Text Available 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.

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

Science.gov (United States)

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.

A Coded Aperture Compressive Imaging Array and Its Visual Detection and Tracking Algorithms for Surveillance Systems

Directory of Open Access Journals (Sweden)

Hanxiao Wu

2012-10-01

Full Text Available In this paper, we propose an application of a compressive imaging system to the problem of wide-area video surveillance systems. A parallel coded aperture compressive imaging system is proposed to reduce the needed high resolution coded mask requirements and facilitate the storage of the projection matrix. Random Gaussian, Toeplitz and binary phase coded masks are utilized to obtain the compressive sensing images. The corresponding motion targets detection and tracking algorithms directly using the compressive sampling images are developed. A mixture of Gaussian distribution is applied in the compressive image space to model the background image and for foreground detection. For each motion target in the compressive sampling domain, a compressive feature dictionary spanned by target templates and noises templates is sparsely represented. An l1 optimization algorithm is used to solve the sparse coefficient of templates. Experimental results demonstrate that low dimensional compressed imaging representation is sufficient to determine spatial motion targets. Compared with the random Gaussian and Toeplitz phase mask, motion detection algorithms using a random binary phase mask can yield better detection results. However using random Gaussian and Toeplitz phase mask can achieve high resolution reconstructed image. Our tracking algorithm can achieve a real time speed that is up to 10 times faster than that of the l1 tracker without any optimization.

Facial Image Compression Based on Structured Codebooks in Overcomplete Domain

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Vila-Forcén JE

2006-01-01

Full Text Available We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.

Block-based wavelet transform coding of mammograms with region-adaptive quantization

Science.gov (United States)

Moon, Nam Su; Song, Jun S.; Kwon, Musik; Kim, JongHyo; Lee, ChoongWoong

1998-06-01

To achieve both high compression ratio and information preserving, it is an efficient way to combine segmentation and lossy compression scheme. Microcalcification in mammogram is one of the most significant sign of early stage of breast cancer. Therefore in coding, detection and segmentation of microcalcification enable us to preserve it well by allocating more bits to it than to other regions. Segmentation of microcalcification is performed both in spatial domain and in wavelet transform domain. Peak error controllable quantization step, which is off-line designed, is suitable for medical image compression. For region-adaptive quantization, block- based wavelet transform coding is adopted and different peak- error-constrained quantizers are applied to blocks according to the segmentation result. In view of preservation of microcalcification, the proposed coding scheme shows better performance than JPEG.

Partial Encryption of Entropy-Coded Video Compression Using Coupled Chaotic Maps

Directory of Open Access Journals (Sweden)

Fadi Almasalha

2014-10-01

Full Text Available Due to pervasive communication infrastructures, a plethora of enabling technologies is being developed over mobile and wired networks. Among these, video streaming services over IP are the most challenging in terms of quality, real-time requirements and security. In this paper, we propose a novel scheme to efficiently secure variable length coded (VLC multimedia bit streams, such as H.264. It is based on code word error diffusion and variable size segment shuffling. The codeword diffusion and the shuffling mechanisms are based on random operations from a secure and computationally efficient chaos-based pseudo-random number generator. The proposed scheme is ubiquitous to the end users and can be deployed at any node in the network. It provides different levels of security, with encrypted data volume fluctuating between 5.5–17%. It works on the compressed bit stream without requiring any decoding. It provides excellent encryption speeds on different platforms, including mobile devices. It is 200% faster and 150% more power efficient when compared with AES software-based full encryption schemes. Regarding security, the scheme is robust to well-known attacks in the literature, such as brute force and known/chosen plain text attacks.

Huffman-based code compression techniques for embedded processors

KAUST Repository

Bonny, Mohamed Talal; Henkel, Jö rg

2010-01-01

% for ARM and MIPS, respectively. In our compression technique, we have conducted evaluations using a representative set of applications and we have applied each technique to two major embedded processor architectures, namely ARM and MIPS. © 2010 ACM.

Fractal Image Compression Based on High Entropy Values Technique

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Douaa Younis Abbaas

2018-04-01

Full Text Available There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression and another lossless technique (in this case entropy coding is used. The entropy technique will reduce size of the domain pool (i. e., number of domain blocks based on the entropy value of each range block and domain block and then comparing the results of full search algorithm and proposed algorithm based on entropy technique to see each of which give best results (such as reduced the encoding time with acceptable values in both compression quali-ty parameters which are C. R (Compression Ratio and PSNR (Image Quality. The experimental results of the proposed algorithm proven that using the proposed entropy technique reduces the encoding time while keeping compression rates and reconstruction image quality good as soon as possible.

Peeling Decoding of LDPC Codes with Applications in Compressed Sensing

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Weijun Zeng

2016-01-01

Full Text Available We present a new approach for the analysis of iterative peeling decoding recovery algorithms in the context of Low-Density Parity-Check (LDPC codes and compressed sensing. The iterative recovery algorithm is particularly interesting for its low measurement cost and low computational complexity. The asymptotic analysis can track the evolution of the fraction of unrecovered signal elements in each iteration, which is similar to the well-known density evolution analysis in the context of LDPC decoding algorithm. Our analysis shows that there exists a threshold on the density factor; if under this threshold, the recovery algorithm is successful; otherwise it will fail. Simulation results are also provided for verifying the agreement between the proposed asymptotic analysis and recovery algorithm. Compared with existing works of peeling decoding algorithm, focusing on the failure probability of the recovery algorithm, our proposed approach gives accurate evolution of performance with different parameters of measurement matrices and is easy to implement. We also show that the peeling decoding algorithm performs better than other schemes based on LDPC codes.

Adaptive variable-length coding for efficient compression of spacecraft television data.

Science.gov (United States)

Rice, R. F.; Plaunt, J. R.

1971-01-01

An adaptive variable length coding system is presented. Although developed primarily for the proposed Grand Tour missions, many features of this system clearly indicate a much wider applicability. Using sample to sample prediction, the coding system produces output rates within 0.25 bit/picture element (pixel) of the one-dimensional difference entropy for entropy values ranging from 0 to 8 bit/pixel. This is accomplished without the necessity of storing any code words. Performance improvements of 0.5 bit/pixel can be simply achieved by utilizing previous line correlation. A Basic Compressor, using concatenated codes, adapts to rapid changes in source statistics by automatically selecting one of three codes to use for each block of 21 pixels. The system adapts to less frequent, but more dramatic, changes in source statistics by adjusting the mode in which the Basic Compressor operates on a line-to-line basis. Furthermore, the compression system is independent of the quantization requirements of the pulse-code modulation system.

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

Science.gov (United States)

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.

Multiple Description Coding with Feedback Based Network Compression

DEFF Research Database (Denmark)

Sørensen, Jesper Hemming; Østergaard, Jan; Popovski, Petar

2010-01-01

and an intermediate node, respectively. A trade-off exists between reducing the delay of the feedback by adapting in the vicinity of the receiver and increasing the gain from compression by adapting close to the source. The analysis shows that adaptation in the network provides a better trade-off than adaptation...

Speech Compression

Directory of Open Access Journals (Sweden)

Jerry D. Gibson

2016-06-01

Full Text Available Speech compression is a key technology underlying digital cellular communications, VoIP, voicemail, and voice response systems. We trace the evolution of speech coding based on the linear prediction model, highlight the key milestones in speech coding, and outline the structures of the most important speech coding standards. Current challenges, future research directions, fundamental limits on performance, and the critical open problem of speech coding for emergency first responders are all discussed.

Identification of Sparse Audio Tampering Using Distributed Source Coding and Compressive Sensing Techniques

Directory of Open Access Journals (Sweden)

Valenzise G

2009-01-01

Full Text Available In the past few years, a large amount of techniques have been proposed to identify whether a multimedia content has been illegally tampered or not. Nevertheless, very few efforts have been devoted to identifying which kind of attack has been carried out, especially due to the large data required for this task. We propose a novel hashing scheme which exploits the paradigms of compressive sensing and distributed source coding to generate a compact hash signature, and we apply it to the case of audio content protection. The audio content provider produces a small hash signature by computing a limited number of random projections of a perceptual, time-frequency representation of the original audio stream; the audio hash is given by the syndrome bits of an LDPC code applied to the projections. At the content user side, the hash is decoded using distributed source coding tools. If the tampering is sparsifiable or compressible in some orthonormal basis or redundant dictionary, it is possible to identify the time-frequency position of the attack, with a hash size as small as 200 bits/second; the bit saving obtained by introducing distributed source coding ranges between 20% to 70%.

Verification testing of the compression performance of the HEVC screen content coding extensions

Science.gov (United States)

Sullivan, Gary J.; Baroncini, Vittorio A.; Yu, Haoping; Joshi, Rajan L.; Liu, Shan; Xiu, Xiaoyu; Xu, Jizheng

2017-09-01

This paper reports on verification testing of the coding performance of the screen content coding (SCC) extensions of the High Efficiency Video Coding (HEVC) standard (Rec. ITU-T H.265 | ISO/IEC 23008-2 MPEG-H Part 2). The coding performance of HEVC screen content model (SCM) reference software is compared with that of the HEVC test model (HM) without the SCC extensions, as well as with the Advanced Video Coding (AVC) joint model (JM) reference software, for both lossy and mathematically lossless compression using All-Intra (AI), Random Access (RA), and Lowdelay B (LB) encoding structures and using similar encoding techniques. Video test sequences in 1920×1080 RGB 4:4:4, YCbCr 4:4:4, and YCbCr 4:2:0 colour sampling formats with 8 bits per sample are tested in two categories: "text and graphics with motion" (TGM) and "mixed" content. For lossless coding, the encodings are evaluated in terms of relative bit-rate savings. For lossy compression, subjective testing was conducted at 4 quality levels for each coding case, and the test results are presented through mean opinion score (MOS) curves. The relative coding performance is also evaluated in terms of Bjøntegaard-delta (BD) bit-rate savings for equal PSNR quality. The perceptual tests and objective metric measurements show a very substantial benefit in coding efficiency for the SCC extensions, and provided consistent results with a high degree of confidence. For TGM video, the estimated bit-rate savings ranged from 60-90% relative to the JM and 40-80% relative to the HM, depending on the AI/RA/LB configuration category and colour sampling format.

A new DWT/MC/DPCM video compression framework based on EBCOT

Science.gov (United States)

Mei, L. M.; Wu, H. R.; Tan, D. M.

2005-07-01

A novel Discrete Wavelet Transform (DWT)/Motion Compensation (MC)/Differential Pulse Code Modulation (DPCM) video compression framework is proposed in this paper. Although the Discrete Cosine Transform (DCT)/MC/DPCM is the mainstream framework for video coders in industry and international standards, the idea of DWT/MC/DPCM has existed for more than one decade in the literature and the investigation is still undergoing. The contribution of this work is twofold. Firstly, the Embedded Block Coding with Optimal Truncation (EBCOT) is used here as the compression engine for both intra- and inter-frame coding, which provides good compression ratio and embedded rate-distortion (R-D) optimization mechanism. This is an extension of the EBCOT application from still images to videos. Secondly, this framework offers a good interface for the Perceptual Distortion Measure (PDM) based on the Human Visual System (HVS) where the Mean Squared Error (MSE) can be easily replaced with the PDM in the R-D optimization. Some of the preliminary results are reported here. They are also compared with benchmarks such as MPEG-2 and MPEG-4 version 2. The results demonstrate that under specified condition the proposed coder outperforms the benchmarks in terms of rate vs. distortion.

A novel ECG data compression method based on adaptive Fourier decomposition

Science.gov (United States)

Tan, Chunyu; Zhang, Liming

2017-12-01

This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

Directory of Open Access Journals (Sweden)

Huiyan Jiang

2012-01-01

Full Text Available 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.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

Science.gov (United States)

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.

Science.gov (United States)

Aktas, Metin; Kuscu, Murat; Dinc, Ergin; Akan, Ozgur B

2018-01-01

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).

A Complete Video Coding Chain Based on Multi-Dimensional Discrete Cosine Transform

Directory of Open Access Journals (Sweden)

T. Fryza

2010-09-01

Full Text Available The paper deals with a video compression method based on the multi-dimensional discrete cosine transform. In the text, the encoder and decoder architectures including the definitions of all mathematical operations like the forward and inverse 3-D DCT, quantization and thresholding are presented. According to the particular number of currently processed pictures, the new quantization tables and entropy code dictionaries are proposed in the paper. The practical properties of the 3-D DCT coding chain compared with the modern video compression methods (such as H.264 and WebM and the computing complexity are presented as well. It will be proved the best compress properties could be achieved by complex H.264 codec. On the other hand the computing complexity - especially on the encoding side - is lower for the 3-D DCT method.

Warped Discrete Cosine Transform-Based Low Bit-Rate Block Coding Using Image Downsampling

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Ertürk Sarp

2007-01-01

Full Text Available This paper presents warped discrete cosine transform (WDCT-based low bit-rate block coding using image downsampling. While WDCT aims to improve the performance of conventional DCT by frequency warping, the WDCT has only been applicable to high bit-rate coding applications because of the overhead required to define the parameters of the warping filter. Recently, low bit-rate block coding based on image downsampling prior to block coding followed by upsampling after the decoding process is proposed to improve the compression performance for low bit-rate block coders. This paper demonstrates that a superior performance can be achieved if WDCT is used in conjunction with image downsampling-based block coding for low bit-rate applications.

High efficiency video coding coding tools and specification

CERN Document Server

Wien, Mathias

2015-01-01

The video coding standard High Efficiency Video Coding (HEVC) targets at improved compression performance for video resolutions of HD and beyond, providing Ultra HD video at similar compressed bit rates as for HD video encoded with the well-established video coding standard H.264 | AVC. Based on known concepts, new coding structures and improved coding tools have been developed and specified in HEVC. The standard is expected to be taken up easily by established industry as well as new endeavors, answering the needs of todays connected and ever-evolving online world. This book presents the High Efficiency Video Coding standard and explains it in a clear and coherent language. It provides a comprehensive and consistently written description, all of a piece. The book targets at both, newbies to video coding as well as experts in the field. While providing sections with introductory text for the beginner, it suits as a well-arranged reference book for the expert. The book provides a comprehensive reference for th...

Adaptable recursive binary entropy coding technique

Science.gov (United States)

Kiely, Aaron B.; Klimesh, Matthew A.

2002-07-01

We present a novel data compression technique, called recursive interleaved entropy coding, that is based on recursive interleaving of variable-to variable length binary source codes. A compression module implementing this technique has the same functionality as arithmetic coding and can be used as the engine in various data compression algorithms. The encoder compresses a bit sequence by recursively encoding groups of bits that have similar estimated statistics, ordering the output in a way that is suited to the decoder. As a result, the decoder has low complexity. The encoding process for our technique is adaptable in that each bit to be encoded has an associated probability-of-zero estimate that may depend on previously encoded bits; this adaptability allows more effective compression. Recursive interleaved entropy coding may have advantages over arithmetic coding, including most notably the admission of a simple and fast decoder. Much variation is possible in the choice of component codes and in the interleaving structure, yielding coder designs of varying complexity and compression efficiency; coder designs that achieve arbitrarily small redundancy can be produced. We discuss coder design and performance estimation methods. We present practical encoding and decoding algorithms, as well as measured performance results.

Assessing the Effects of Data Compression in Simulations Using Physically Motivated Metrics

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Daniel Laney

2014-01-01

Full Text Available This paper examines whether lossy compression can be used effectively in physics simulations as a possible strategy to combat the expected data-movement bottleneck in future high performance computing architectures. We show that, for the codes and simulations we tested, compression levels of 3–5X can be applied without causing significant changes to important physical quantities. Rather than applying signal processing error metrics, we utilize physics-based metrics appropriate for each code to assess the impact of compression. We evaluate three different simulation codes: a Lagrangian shock-hydrodynamics code, an Eulerian higher-order hydrodynamics turbulence modeling code, and an Eulerian coupled laser-plasma interaction code. We compress relevant quantities after each time-step to approximate the effects of tightly coupled compression and study the compression rates to estimate memory and disk-bandwidth reduction. We find that the error characteristics of compression algorithms must be carefully considered in the context of the underlying physics being modeled.

Content Progressive Coding of Limited Bits/pixel Images

DEFF Research Database (Denmark)

Jensen, Ole Riis; Forchhammer, Søren

1999-01-01

A new lossless context based method for content progressive coding of limited bits/pixel images is proposed. Progressive coding is achieved by separating the image into contelnt layers. Digital maps are compressed up to 3 times better than GIF.......A new lossless context based method for content progressive coding of limited bits/pixel images is proposed. Progressive coding is achieved by separating the image into contelnt layers. Digital maps are compressed up to 3 times better than GIF....

SeqCompress: an algorithm for biological sequence compression.

Science.gov (United States)

Sardaraz, Muhammad; Tahir, Muhammad; Ikram, Ataul Aziz; Bajwa, Hassan

2014-10-01

The growth of Next Generation Sequencing technologies presents significant research challenges, specifically to design bioinformatics tools that handle massive amount of data efficiently. Biological sequence data storage cost has become a noticeable proportion of total cost in the generation and analysis. Particularly increase in DNA sequencing rate is significantly outstripping the rate of increase in disk storage capacity, which may go beyond the limit of storage capacity. It is essential to develop algorithms that handle large data sets via better memory management. This article presents a DNA sequence compression algorithm SeqCompress that copes with the space complexity of biological sequences. The algorithm is based on lossless data compression and uses statistical model as well as arithmetic coding to compress DNA sequences. The proposed algorithm is compared with recent specialized compression tools for biological sequences. Experimental results show that proposed algorithm has better compression gain as compared to other existing algorithms. Copyright © 2014 Elsevier Inc. All rights reserved.

A Novel Error Resilient Scheme for Wavelet-based Image Coding Over Packet Networks

OpenAIRE

WenZhu Sun; HongYu Wang; DaXing Qian

2012-01-01

this paper presents a robust transmission strategy for wavelet based scalable bit stream over packet erasure channel. By taking the advantage of the bit plane coding and the multiple description coding, the proposed strategy adopts layered multiple description coding (LMDC) for the embedded wavelet coders to improve the error resistant capability of the important bit planes in the meaning of D(R) function. Then, the post-compression rate-distortion (PCRD) optimization process is used to impro...

3D Scan-Based Wavelet Transform and Quality Control for Video Coding

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Parisot Christophe

2003-01-01

Full Text Available Wavelet coding has been shown to achieve better compression than DCT coding and moreover allows scalability. 2D DWT can be easily extended to 3D and thus applied to video coding. However, 3D subband coding of video suffers from two drawbacks. The first is the amount of memory required for coding large 3D blocks; the second is the lack of temporal quality due to the sequence temporal splitting. In fact, 3D block-based video coders produce jerks. They appear at blocks temporal borders during video playback. In this paper, we propose a new temporal scan-based wavelet transform method for video coding combining the advantages of wavelet coding (performance, scalability with acceptable reduced memory requirements, no additional CPU complexity, and avoiding jerks. We also propose an efficient quality allocation procedure to ensure a constant quality over time.

Atomic effect algebras with compression bases

International Nuclear Information System (INIS)

Caragheorgheopol, Dan; Tkadlec, Josef

2011-01-01

Compression base effect algebras were recently introduced by Gudder [Demonstr. Math. 39, 43 (2006)]. They generalize sequential effect algebras [Rep. Math. Phys. 49, 87 (2002)] and compressible effect algebras [Rep. Math. Phys. 54, 93 (2004)]. The present paper focuses on atomic compression base effect algebras and the consequences of atoms being foci (so-called projections) of the compressions in the compression base. Part of our work generalizes results obtained in atomic sequential effect algebras by Tkadlec [Int. J. Theor. Phys. 47, 185 (2008)]. The notion of projection-atomicity is introduced and studied, and several conditions that force a compression base effect algebra or the set of its projections to be Boolean are found. Finally, we apply some of these results to sequential effect algebras and strengthen a previously established result concerning a sufficient condition for them to be Boolean.

A review on compressed pattern matching

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Surya Prakash Mishra

2016-09-01

Full Text Available Compressed pattern matching (CPM refers to the task of locating all the occurrences of a pattern (or set of patterns inside the body of compressed text. In this type of matching, pattern may or may not be compressed. CPM is very useful in handling large volume of data especially over the network. It has many applications in computational biology, where it is useful in finding similar trends in DNA sequences; intrusion detection over the networks, big data analytics etc. Various solutions have been provided by researchers where pattern is matched directly over the uncompressed text. Such solution requires lot of space and consumes lot of time when handling the big data. Various researchers have proposed the efficient solutions for compression but very few exist for pattern matching over the compressed text. Considering the future trend where data size is increasing exponentially day-by-day, CPM has become a desirable task. This paper presents a critical review on the recent techniques on the compressed pattern matching. The covered techniques includes: Word based Huffman codes, Word Based Tagged Codes; Wavelet Tree Based Indexing. We have presented a comparative analysis of all the techniques mentioned above and highlighted their advantages and disadvantages.

A Compression Algorithm in Wireless Sensor Networks of Bearing Monitoring

International Nuclear Information System (INIS)

Zheng Bin; Meng Qingfeng; Wang Nan; Li Zhi

2011-01-01

The energy consumption of wireless sensor networks (WSNs) is always an important problem in the application of wireless sensor networks. This paper proposes a data compression algorithm to reduce amount of data and energy consumption during the data transmission process in the on-line WSNs-based bearing monitoring system. The proposed compression algorithm is based on lifting wavelets, Zerotree coding and Hoffman coding. Among of that, 5/3 lifting wavelets is used for dividing data into different frequency bands to extract signal characteristics. Zerotree coding is applied to calculate the dynamic thresholds to retain the attribute data. The attribute data are then encoded by Hoffman coding to further enhance the compression ratio. In order to validate the algorithm, simulation is carried out by using Matlab. The result of simulation shows that the proposed algorithm is very suitable for the compression of bearing monitoring data. The algorithm has been successfully used in online WSNs-based bearing monitoring system, in which TI DSP TMS320F2812 is used to realize the algorithm.

Efficient predictive algorithms for image compression

CERN Document Server

Rosário Lucas, Luís Filipe; Maciel de Faria, Sérgio Manuel; Morais Rodrigues, Nuno Miguel; Liberal Pagliari, Carla

2017-01-01

This book discusses efficient prediction techniques for the current state-of-the-art High Efficiency Video Coding (HEVC) standard, focusing on the compression of a wide range of video signals, such as 3D video, Light Fields and natural images. The authors begin with a review of the state-of-the-art predictive coding methods and compression technologies for both 2D and 3D multimedia contents, which provides a good starting point for new researchers in the field of image and video compression. New prediction techniques that go beyond the standardized compression technologies are then presented and discussed. In the context of 3D video, the authors describe a new predictive algorithm for the compression of depth maps, which combines intra-directional prediction, with flexible block partitioning and linear residue fitting. New approaches are described for the compression of Light Field and still images, which enforce sparsity constraints on linear models. The Locally Linear Embedding-based prediction method is in...

Highly Efficient Compression Algorithms for Multichannel EEG.

Science.gov (United States)

Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Adaptive Binary Arithmetic Coder-Based Image Feature and Segmentation in the Compressed Domain

Directory of Open Access Journals (Sweden)

Hsi-Chin Hsin

2012-01-01

Full Text Available Image compression is necessary in various applications, especially for efficient transmission over a band-limited channel. It is thus desirable to be able to segment an image in the compressed domain directly such that the burden of decompressing computation can be avoided. Motivated by the adaptive binary arithmetic coder (MQ coder of JPEG2000, we propose an efficient scheme to segment the feature vectors that are extracted from the code stream of an image. We modify the Compression-based Texture Merging (CTM algorithm to alleviate the influence of overmerging problem by making use of the rate distortion information. Experimental results show that the MQ coder-based image segmentation is preferable in terms of the boundary displacement error (BDE measure. It has the advantage of saving computational cost as the segmentation results even at low rates of bits per pixel (bpp are satisfactory.

Image Coding Based on Address Vector Quantization.

Science.gov (United States)

Feng, Yushu

Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing

Context-Aware Image Compression.

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Jacky C K Chan

Full Text Available We describe a physics-based data compression method inspired by the photonic time stretch wherein information-rich portions of the data are dilated in a process that emulates the effect of group velocity dispersion on temporal signals. With this coding operation, the data can be downsampled at a lower rate than without it. In contrast to previous implementation of the warped stretch compression, here the decoding can be performed without the need of phase recovery. We present rate-distortion analysis and show improvement in PSNR compared to compression via uniform downsampling.

Model-Based Speech Signal Coding Using Optimized Temporal Decomposition for Storage and Broadcasting Applications

Science.gov (United States)

Athaudage, Chandranath R. N.; Bradley, Alan B.; Lech, Margaret

2003-12-01

A dynamic programming-based optimization strategy for a temporal decomposition (TD) model of speech and its application to low-rate speech coding in storage and broadcasting is presented. In previous work with the spectral stability-based event localizing (SBEL) TD algorithm, the event localization was performed based on a spectral stability criterion. Although this approach gave reasonably good results, there was no assurance on the optimality of the event locations. In the present work, we have optimized the event localizing task using a dynamic programming-based optimization strategy. Simulation results show that an improved TD model accuracy can be achieved. A methodology of incorporating the optimized TD algorithm within the standard MELP speech coder for the efficient compression of speech spectral information is also presented. The performance evaluation results revealed that the proposed speech coding scheme achieves 50%-60% compression of speech spectral information with negligible degradation in the decoded speech quality.

Survey Of Lossless Image Coding Techniques

Science.gov (United States)

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.

Volumetric Medical Image Coding: An Object-based, Lossy-to-lossless and Fully Scalable Approach

Science.gov (United States)

Danyali, Habibiollah; Mertins, Alfred

2011-01-01

In this article, an object-based, highly scalable, lossy-to-lossless 3D wavelet coding approach for volumetric medical image data (e.g., magnetic resonance (MR) and computed tomography (CT)) is proposed. The new method, called 3DOBHS-SPIHT, is based on the well-known set partitioning in the hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. The 3D input data is grouped into groups of slices (GOS) and each GOS is encoded and decoded as a separate unit. The symmetric tree definition of the original 3DSPIHT is improved by introducing a new asymmetric tree structure. While preserving the compression efficiency, the new tree structure allows for a small size of each GOS, which not only reduces memory consumption during the encoding and decoding processes, but also facilitates more efficient random access to certain segments of slices. To achieve more compression efficiency, the algorithm only encodes the main object of interest in each 3D data set, which can have any arbitrary shape, and ignores the unnecessary background. The experimental results on some MR data sets show the good performance of the 3DOBHS-SPIHT algorithm for multi-resolution lossy-to-lossless coding. The compression efficiency, full scalability, and object-based features of the proposed approach, beside its lossy-to-lossless coding support, make it a very attractive candidate for volumetric medical image information archiving and transmission applications. PMID:22606653

RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure

Directory of Open Access Journals (Sweden)

Chen Chun

2008-03-01

Full Text Available Abstract Background With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression. Results RNACompress employs an efficient grammar-based model to compress RNA sequences and their secondary structures. The main goals of this algorithm are two fold: (1 present a robust and effective way for RNA structural data compression; (2 design a suitable model to represent RNA secondary structure as well as derive the informational complexity of the structural data based on compression. Our extensive tests have shown that RNACompress achieves a universally better compression ratio compared with other sequence-specific or common text-specific compression algorithms, such as Gencompress, winrar and gzip. Moreover, a test of the activities of distinct GTP-binding RNAs (aptamers compared with their structural complexity shows that our defined informational complexity can be used to describe how complexity varies with activity. These results lead to an objective means of comparing the functional properties of heteropolymers from the information perspective. Conclusion A universal algorithm for the compression of RNA secondary structure as well as the evaluation of its informational complexity is discussed in this paper. We have developed RNACompress, as a useful tool

CoGI: Towards Compressing Genomes as an Image.

Science.gov (United States)

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.

Physics Based Modeling of Compressible Turbulance

Science.gov (United States)

2016-11-07

AFRL-AFOSR-VA-TR-2016-0345 PHYSICS -BASED MODELING OF COMPRESSIBLE TURBULENCE PARVIZ MOIN LELAND STANFORD JUNIOR UNIV CA Final Report 09/13/2016...on the AFOSR project (FA9550-11-1-0111) entitled: Physics based modeling of compressible turbulence. The period of performance was, June 15, 2011...by ANSI Std. Z39.18 Page 1 of 2FORM SF 298 11/10/2016https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll PHYSICS -BASED MODELING OF COMPRESSIBLE

Reliability-Based Approach for the Determination of the Required Compressive Strength of Concrete in Mix Design

OpenAIRE

Okasha , Nader M

2017-01-01

International audience; Concrete is recognized as the second most consumed product in our modern life after water. The variability in concrete properties is inevitable. The concrete mix is designed for a compressive strength that is different from, typically higher than, the value specified by the structural designer. Ways to calculate the compressive strength to be used in the mix design are provided in building and structural codes. These ways are all based on criteria related purely and on...

Password Authentication Based on Fractal Coding Scheme

Directory of Open Access Journals (Sweden)

Nadia M. G. Al-Saidi

2012-01-01

Full Text Available Password authentication is a mechanism used to authenticate user identity over insecure communication channel. In this paper, a new method to improve the security of password authentication is proposed. It is based on the compression capability of the fractal image coding to provide an authorized user a secure access to registration and login process. In the proposed scheme, a hashed password string is generated and encrypted to be captured together with the user identity using text to image mechanisms. The advantage of fractal image coding is to be used to securely send the compressed image data through a nonsecured communication channel to the server. The verification of client information with the database system is achieved in the server to authenticate the legal user. The encrypted hashed password in the decoded fractal image is recognized using optical character recognition. The authentication process is performed after a successful verification of the client identity by comparing the decrypted hashed password with those which was stored in the database system. The system is analyzed and discussed from the attacker’s viewpoint. A security comparison is performed to show that the proposed scheme provides an essential security requirement, while their efficiency makes it easier to be applied alone or in hybrid with other security methods. Computer simulation and statistical analysis are presented.

MULTISTAGE BITRATE REDUCTION IN ABSOLUTE MOMENT BLOCK TRUNCATION CODING FOR IMAGE COMPRESSION

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S. Vimala

2012-05-01

Full Text Available Absolute Moment Block Truncation Coding (AMBTC is one of the lossy image compression techniques. The computational complexity involved is less and the quality of the reconstructed images is appreciable. The normal AMBTC method requires 2 bits per pixel (bpp. In this paper, two novel ideas have been incorporated as part of AMBTC method to improve the coding efficiency. Generally, the quality degrades with the reduction in the bit-rate. But in the proposed method, the quality of the reconstructed image increases with the decrease in the bit-rate. The proposed method has been tested with standard images like Lena, Barbara, Bridge, Boats and Cameraman. The results obtained are better than that of the existing AMBTC method in terms of bit-rate and the quality of the reconstructed images.

Evaluation of peripheral compression and auditory nerve fiber intensity coding using auditory steady-state responses

DEFF Research Database (Denmark)

Encina Llamas, Gerard; M. Harte, James; Epp, Bastian

2015-01-01

. Evaluation of these properties provides information about the health state of the system. It has been shown that a loss of outer hair cells leads to a reduction in peripheral compression. It has also recently been shown in animal studies that noise over-exposure, producing temporary threshold shifts, can....... The results indicate that the slope of the ASSR level growth function can be used to estimate peripheral compression simultaneously at four frequencies below 60 dB SPL, while the slope above 60 dB SPL may provide information about the integrity of intensity coding of low-SR fibers.......The compressive nonlinearity of the auditory system is assumed to be an epiphenomenon of a healthy cochlea and, particularly, of outer-hair cell function. Another ability of the healthy auditory system is to enable communication in acoustical environments with high-level background noises...

Composite Techniques Based Color Image Compression

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Zainab Ibrahim Abood

2017-03-01

Full Text Available Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S, composite wavelet technique (W and composite multi-wavelet technique (M. For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM in M technique which has the highest values of energy (En and compression ratio (CR and least values of bit per pixel (bpp, time (T and rate distortion R(D. Also the values of the compression parameters of the color image are nearly the same as the average values of the compression parameters of the three bands of the same image.

A joint multi-view plus depth image coding scheme based on 3D-warping

DEFF Research Database (Denmark)

Zamarin, Marco; Zanuttigh, Pietro; Milani, Simone

2011-01-01

on the scene structure that can be effectively exploited to improve the performance of multi-view coding schemes. In this paper we introduce a novel coding architecture that replaces the inter-view motion prediction operation with a 3D warping approach based on depth information to improve the coding......Free viewpoint video applications and autostereoscopic displays require the transmission of multiple views of a scene together with depth maps. Current compression and transmission solutions just handle these two data streams as separate entities. However, depth maps contain key information...

USING H.264/AVC-INTRA FOR DCT BASED SEGMENTATION DRIVEN COMPOUND IMAGE COMPRESSION

Directory of Open Access Journals (Sweden)

S. Ebenezer Juliet

2011-08-01

Full Text Available This paper presents a one pass block classification algorithm for efficient coding of compound images which consists of multimedia elements like text, graphics and natural images. The objective is to minimize the loss of visual quality of text during compression by separating text information which needs high special resolution than the pictures and background. It segments computer screen images into text/graphics and picture/background classes based on DCT energy in each 4x4 block, and then compresses both text/graphics pixels and picture/background blocks by H.264/AVC with variable quantization parameter. Experimental results show that the single H.264/AVC-INTRA coder with variable quantization outperforms single coders such as JPEG, JPEG-2000 for compound images. Also the proposed method improves the PSNR value significantly than standard JPEG, JPEG-2000 and while keeping competitive compression ratios.

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

Science.gov (United States)

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.

Highly parallel line-based image coding for many cores.

Science.gov (United States)

Peng, Xiulian; Xu, Jizheng; Zhou, You; Wu, Feng

2012-01-01

Computers are developing along with a new trend from the dual-core and quad-core processors to ones with tens or even hundreds of cores. Multimedia, as one of the most important applications in computers, has an urgent need to design parallel coding algorithms for compression. Taking intraframe/image coding as a start point, this paper proposes a pure line-by-line coding scheme (LBLC) to meet the need. In LBLC, an input image is processed line by line sequentially, and each line is divided into small fixed-length segments. The compression of all segments from prediction to entropy coding is completely independent and concurrent at many cores. Results on a general-purpose computer show that our scheme can get a 13.9 times speedup with 15 cores at the encoder and a 10.3 times speedup at the decoder. Ideally, such near-linear speeding relation with the number of cores can be kept for more than 100 cores. In addition to the high parallelism, the proposed scheme can perform comparatively or even better than the H.264 high profile above middle bit rates. At near-lossless coding, it outperforms H.264 more than 10 dB. At lossless coding, up to 14% bit-rate reduction is observed compared with H.264 lossless coding at the high 4:4:4 profile.

Depth-based Multi-View 3D Video Coding

DEFF Research Database (Denmark)

Zamarin, Marco

techniques are used to extract dense motion information and generate improved candidate side information. Multiple candidates are merged employing multi-hypothesis strategies. Promising rate-distortion performance improvements compared with state-of-the-art Wyner-Ziv decoders are reported, both when texture......-view video. Depth maps are typically used to synthesize the desired output views, and the performance of view synthesis algorithms strongly depends on the accuracy of depth information. In this thesis, novel algorithms for efficient depth map compression in MVD scenarios are proposed, with particular focus...... on edge-preserving solutions. In a proposed scheme, texture-depth correlation is exploited to predict surface shapes in the depth signal. In this way depth coding performance can be improved in terms of both compression gain and edge-preservation. Another solution proposes a new intra coding mode targeted...

Context adaptive coding of bi-level images

DEFF Research Database (Denmark)

Forchhammer, Søren

2008-01-01

With the advent of sequential arithmetic coding, the focus of highly efficient lossless data compression is placed on modelling the data. Rissanen's Algorithm Context provided an elegant solution to universal coding with optimal convergence rate. Context based arithmetic coding laid the grounds f...

Subset-sum phase transitions and data compression

Science.gov (United States)

Merhav, Neri

2011-09-01

We propose a rigorous analysis approach for the subset-sum problem in the context of lossless data compression, where the phase transition of the subset-sum problem is directly related to the passage between ambiguous and non-ambiguous decompression, for a compression scheme that is based on specifying the sequence composition. The proposed analysis lends itself to straightforward extensions in several directions of interest, including non-binary alphabets, incorporation of side information at the decoder (Slepian-Wolf coding), and coding schemes based on multiple subset sums. It is also demonstrated that the proposed technique can be used to analyze the critical behavior in a more involved situation where the sequence composition is not specified by the encoder.

A secure approach for encrypting and compressing biometric information employing orthogonal code and steganography

Science.gov (United States)

Islam, Muhammad F.; Islam, Mohammed N.

2012-04-01

The objective of this paper is to develop a novel approach for encryption and compression of biometric information utilizing orthogonal coding and steganography techniques. Multiple biometric signatures are encrypted individually using orthogonal codes and then multiplexed together to form a single image, which is then embedded in a cover image using the proposed steganography technique. The proposed technique employs three least significant bits for this purpose and a secret key is developed to choose one from among these bits to be replaced by the corresponding bit of the biometric image. The proposed technique offers secure transmission of multiple biometric signatures in an identification document which will be protected from unauthorized steganalysis attempt.

Lossless, Near-Lossless, and Refinement Coding of Bi-level Images

DEFF Research Database (Denmark)

Martins, Bo; Forchhammer, Søren Otto

1999-01-01

We present general and unified algorithms for lossy/lossless coding of bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general...... to the specialized soft pattern matching techniques which work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless......, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bi-level images....

Magnetic resonance image compression using scalar-vector quantization

Science.gov (United States)

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.

Lossless quantum data compression and variable-length coding

International Nuclear Information System (INIS)

Bostroem, Kim; Felbinger, Timo

2002-01-01

In order to compress quantum messages without loss of information it is necessary to allow the length of the encoded messages to vary. We develop a general framework for variable-length quantum messages in close analogy to the classical case and show that lossless compression is only possible if the message to be compressed is known to the sender. The lossless compression of an ensemble of messages is bounded from below by its von-Neumann entropy. We show that it is possible to reduce the number of qbits passing through a quantum channel even below the von Neumann entropy by adding a classical side channel. We give an explicit communication protocol that realizes lossless and instantaneous quantum data compression and apply it to a simple example. This protocol can be used for both online quantum communication and storage of quantum data

Relation between temporal envelope coding, pitch discrimination, and compression estimates in listeners with sensorineural hearing loss

DEFF Research Database (Denmark)

Bianchi, Federica; Santurette, Sébastien; Fereczkowski, Michal

2015-01-01

Recent physiological studies in animals showed that noise-induced sensorineural hearing loss (SNHL) increased the amplitude of envelope coding in single auditory-nerve fibers. The present study investigated whether SNHL in human listeners was associated with enhanced temporal envelope coding...... resolvability. For the unresolved conditions, all five HI listeners performed as good as or better than NH listeners with matching musical experience. Two HI listeners showed lower amplitude-modulation detection thresholds than NH listeners for low modulation rates, and one of these listeners also showed a loss......, whether this enhancement affected pitch discrimination performance, and whether loss of compression following SNHL was a potential factor in envelope coding enhancement. Envelope processing was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in a behavioral amplitude...

A hybrid video compression based on zerotree wavelet structure

International Nuclear Information System (INIS)

Kilic, Ilker; Yilmaz, Reyat

2009-01-01

A video compression algorithm comparable to the standard techniques at low bit rates is presented in this paper. The overlapping block motion compensation (OBMC) is combined with discrete wavelet transform which followed by Lloyd-Max quantization and zerotree wavelet (ZTW) structure. The novel feature of this coding scheme is the combination of hierarchical finite state vector quantization (HFSVQ) with the ZTW to encode the quantized wavelet coefficients. It is seen that the proposed video encoder (ZTW-HFSVQ) performs better than the MPEG-4 and Zerotree Entropy Coding (ZTE). (author)

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks.

Science.gov (United States)

Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

2016-09-22

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It's theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

Piecewise spectrally band-pass for compressive coded aperture spectral imaging

International Nuclear Information System (INIS)

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

2015-01-01

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

Compression-Based Tools for Navigation with an Image Database

Directory of Open Access Journals (Sweden)

Giovanni Motta

2012-01-01

Full Text Available We present tools that can be used within a larger system referred to as a passive assistant. The system receives information from a mobile device, as well as information from an image database such as Google Street View, and employs image processing to provide useful information about a local urban environment to a user who is visually impaired. The first stage acquires and computes accurate location information, the second stage performs texture and color analysis of a scene, and the third stage provides specific object recognition and navigation information. These second and third stages rely on compression-based tools (dimensionality reduction, vector quantization, and coding that are enhanced by knowledge of (approximate location of objects.

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node

Directory of Open Access Journals (Sweden)

Kan Luo

2018-01-01

Full Text Available Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS- based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node’s specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM, block sparse Bayesian learning (BSBL method, and discrete cosine transform (DCT basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

A Digital Compressed Sensing-Based Energy-Efficient Single-Spot Bluetooth ECG Node.

Science.gov (United States)

Luo, Kan; Cai, Zhipeng; Du, Keqin; Zou, Fumin; Zhang, Xiangyu; Li, Jianqing

2018-01-01

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth ECG node is proposed to deal with the challenge in wireless ECG application. A periodic sleep/wake-up scheme and a CS-based compression algorithm are implemented in a node, which consists of ultra-low-power analog front-end, microcontroller, Bluetooth 4.0 communication module, and so forth. The efficiency improvement and the node's specifics are evidenced by the experiments using the ECG signals sampled by the proposed node under daily activities of lay, sit, stand, walk, and run. Under using sparse binary matrix (SBM), block sparse Bayesian learning (BSBL) method, and discrete cosine transform (DCT) basis, all ECG signals were essentially undistorted recovered with root-mean-square differences (PRDs) which are less than 6%. The proposed sleep/wake-up scheme and data compression can reduce the airtime over energy-hungry wireless links, the energy consumption of proposed node is 6.53 mJ, and the energy consumption of radio decreases 77.37%. Moreover, the energy consumption increase caused by CS code execution is negligible, which is 1.3% of the total energy consumption.

Task-oriented lossy compression of magnetic resonance images

Science.gov (United States)

Anderson, Mark C.; Atkins, M. Stella; Vaisey, Jacques

1996-04-01

A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

Vertical Object Layout and Compression for Fixed Heaps

Science.gov (United States)

Titzer, Ben L.; Palsberg, Jens

Research into embedded sensor networks has placed increased focus on the problem of developing reliable and flexible software for microcontroller-class devices. Languages such as nesC [10] and Virgil [20] have brought higher-level programming idioms to this lowest layer of software, thereby adding expressiveness. Both languages are marked by the absence of dynamic memory allocation, which removes the need for a runtime system to manage memory. While nesC offers code modules with statically allocated fields, arrays and structs, Virgil allows the application to allocate and initialize arbitrary objects during compilation, producing a fixed object heap for runtime. This paper explores techniques for compressing fixed object heaps with the goal of reducing the RAM footprint of a program. We explore table-based compression and introduce a novel form of object layout called vertical object layout. We provide experimental results that measure the impact on RAM size, code size, and execution time for a set of Virgil programs. Our results show that compressed vertical layout has better execution time and code size than table-based compression while achieving more than 20% heap reduction on 6 of 12 benchmark programs and 2-17% heap reduction on the remaining 6. We also present a formalization of vertical object layout and prove tight relationships between three styles of object layout.

Coding visual features extracted from video sequences.

Science.gov (United States)

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

Research on compression performance of ultrahigh-definition videos

Science.gov (United States)

Li, Xiangqun; He, Xiaohai; Qing, Linbo; Tao, Qingchuan; Wu, Di

2017-11-01

With the popularization of high-definition (HD) images and videos (1920×1080 pixels and above), there are even 4K (3840×2160) television signals and 8 K (8192×4320) ultrahigh-definition videos. The demand for HD images and videos is increasing continuously, along with the increasing data volume. The storage and transmission cannot be properly solved only by virtue of the expansion capacity of hard disks and the update and improvement of transmission devices. Based on the full use of the coding standard high-efficiency video coding (HEVC), super-resolution reconstruction technology, and the correlation between the intra- and the interprediction, we first put forward a "division-compensation"-based strategy to further improve the compression performance of a single image and frame I. Then, by making use of the above thought and HEVC encoder and decoder, a video compression coding frame is designed. HEVC is used inside the frame. Last, with the super-resolution reconstruction technology, the reconstructed video quality is further improved. The experiment shows that by the proposed compression method for a single image (frame I) and video sequence here, the performance is superior to that of HEVC in a low bit rate environment.

A compressed sensing based method with support refinement for impulse noise cancelation in DSL

KAUST Repository

Quadeer, Ahmed Abdul

2013-06-01

This paper presents a compressed sensing based method to suppress impulse noise in digital subscriber line (DSL). The proposed algorithm exploits the sparse nature of the impulse noise and utilizes the carriers, already available in all practical DSL systems, for its estimation and cancelation. Specifically, compressed sensing is used for a coarse estimate of the impulse position, an a priori information based maximum aposteriori probability (MAP) metric for its refinement, followed by least squares (LS) or minimum mean square error (MMSE) estimation for estimating the impulse amplitudes. Simulation results show that the proposed scheme achieves higher rate as compared to other known sparse estimation algorithms in literature. The paper also demonstrates the superior performance of the proposed scheme compared to the ITU-T G992.3 standard that utilizes RS-coding for impulse noise refinement in DSL signals. © 2013 IEEE.

Evaluation of a new image compression technique

International Nuclear Information System (INIS)

Algra, P.R.; Kroon, H.M.; Noordveld, R.B.; DeValk, J.P.J.; Seeley, G.W.; Westerink, P.H.

1988-01-01

The authors present the evaluation of a new image compression technique, subband coding using vector quantization, on 44 CT examinations of the upper abdomen. Three independent radiologists reviewed the original images and compressed versions. The compression ratios used were 16:1 and 20:1. Receiver operating characteristic analysis showed no difference in the diagnostic contents between originals and their compressed versions. Subjective visibility of anatomic structures was equal. Except for a few 20:1 compressed images, the observers could not distinguish compressed versions from original images. They conclude that subband coding using vector quantization is a valuable method for data compression in CT scans of the abdomen

Subjective evaluation of compressed image quality

Science.gov (United States)

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.

Data compression of scanned halftone images

DEFF Research Database (Denmark)

Forchhammer, Søren; Jensen, Kim S.

1994-01-01

with the halftone grid, and converted to a gray level representation. A new digital description of (halftone) grids has been developed for this purpose. The gray level values are coded according to a scheme based on states derived from a segmentation of gray values. To enable real-time processing of high resolution...... scanner output, the coding has been parallelized and implemented on a transputer system. For comparison, the test image was coded using existing (lossless) methods giving compression rates of 2-7. The best of these, a combination of predictive and binary arithmetic coding was modified and optimized...

A method of loss free compression for the data of nuclear spectrum

International Nuclear Information System (INIS)

Sun Mingshan; Wu Shiying; Chen Yantao; Xu Zurun

2000-01-01

A new method of loss free compression based on the feature of the data of nuclear spectrum is provided, from which a practicable algorithm is successfully derived. A compression rate varying from 0.50 to 0.25 is obtained and the distribution of the processed data becomes even more suitable to be reprocessed by another compression such as Huffman Code to improve the compression rate

An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Donghao Wang

2016-09-01

Full Text Available To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

Application of content-based image compression to telepathology

Science.gov (United States)

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.

Picture data compression coder using subband/transform coding with a Lempel-Ziv-based coder

Science.gov (United States)

Glover, Daniel R. (Inventor)

1995-01-01

Digital data coders/decoders are used extensively in video transmission. A digitally encoded video signal is separated into subbands. Separating the video into subbands allows transmission at low data rates. Once the data is separated into these subbands it can be coded and then decoded by statistical coders such as the Lempel-Ziv based coder.

Code Team Training: Demonstrating Adherence to AHA Guidelines During Pediatric Code Blue Activations.

Science.gov (United States)

Stewart, Claire; Shoemaker, Jamie; Keller-Smith, Rachel; Edmunds, Katherine; Davis, Andrew; Tegtmeyer, Ken

2017-10-16

Pediatric code blue activations are infrequent events with a high mortality rate despite the best effort of code teams. The best method for training these code teams is debatable; however, it is clear that training is needed to assure adherence to American Heart Association (AHA) Resuscitation Guidelines and to prevent the decay that invariably occurs after Pediatric Advanced Life Support training. The objectives of this project were to train a multidisciplinary, multidepartmental code team and to measure this team's adherence to AHA guidelines during code simulation. Multidisciplinary code team training sessions were held using high-fidelity, in situ simulation. Sessions were held several times per month. Each session was filmed and reviewed for adherence to 5 AHA guidelines: chest compression rate, ventilation rate, chest compression fraction, use of a backboard, and use of a team leader. After the first study period, modifications were made to the code team including implementation of just-in-time training and alteration of the compression team. Thirty-eight sessions were completed, with 31 eligible for video analysis. During the first study period, 1 session adhered to all AHA guidelines. During the second study period, after alteration of the code team and implementation of just-in-time training, no sessions adhered to all AHA guidelines; however, there was an improvement in percentage of sessions adhering to ventilation rate and chest compression rate and an improvement in median ventilation rate. We present a method for training a large code team drawn from multiple hospital departments and a method of assessing code team performance. Despite subjective improvement in code team positioning, communication, and role completion and some improvement in ventilation rate and chest compression rate, we failed to consistently demonstrate improvement in adherence to all guidelines.

Compression of surface myoelectric signals using MP3 encoding.

Science.gov (United States)

Chan, Adrian D C

2011-01-01

The potential of MP3 compression of surface myoelectric signals is explored in this paper. MP3 compression is a perceptual-based encoder scheme, used traditionally to compress audio signals. The ubiquity of MP3 compression (e.g., portable consumer electronics and internet applications) makes it an attractive option for remote monitoring and telemedicine applications. The effects of muscle site and contraction type are examined at different MP3 encoding bitrates. Results demonstrate that MP3 compression is sensitive to the myoelectric signal bandwidth, with larger signal distortion associated with myoelectric signals that have higher bandwidths. Compared to other myoelectric signal compression techniques reported previously (embedded zero-tree wavelet compression and adaptive differential pulse code modulation), MP3 compression demonstrates superior performance (i.e., lower percent residual differences for the same compression ratios).

Human Motion Capture Data Tailored Transform Coding.

Science.gov (United States)

Junhui Hou; Lap-Pui Chau; Magnenat-Thalmann, Nadia; Ying He

2015-07-01

Human motion capture (mocap) is a widely used technique for digitalizing human movements. With growing usage, compressing mocap data has received increasing attention, since compact data size enables efficient storage and transmission. Our analysis shows that mocap data have some unique characteristics that distinguish themselves from images and videos. Therefore, directly borrowing image or video compression techniques, such as discrete cosine transform, does not work well. In this paper, we propose a novel mocap-tailored transform coding algorithm that takes advantage of these features. Our algorithm segments the input mocap sequences into clips, which are represented in 2D matrices. Then it computes a set of data-dependent orthogonal bases to transform the matrices to frequency domain, in which the transform coefficients have significantly less dependency. Finally, the compression is obtained by entropy coding of the quantized coefficients and the bases. Our method has low computational cost and can be easily extended to compress mocap databases. It also requires neither training nor complicated parameter setting. Experimental results demonstrate that the proposed scheme significantly outperforms state-of-the-art algorithms in terms of compression performance and speed.

Improvement of Secret Image Invisibility in Circulation Image with Dyadic Wavelet Based Data Hiding with Run-Length Coded Secret Images of Which Location of Codes are Determined with Random Number

OpenAIRE

Kohei Arai; Yuji Yamada

2011-01-01

An attempt is made for improvement of secret image invisibility in circulation images with dyadic wavelet based data hiding with run-length coded secret images of which location of codes are determined by random number. Through experiments, it is confirmed that secret images are almost invisible in circulation images. Also robustness of the proposed data hiding method against data compression of circulation images is discussed. Data hiding performance in terms of invisibility of secret images...

A CABAC codec of H.264AVC with secure arithmetic coding

Science.gov (United States)

Neji, Nihel; Jridi, Maher; Alfalou, Ayman; Masmoudi, Nouri

2013-02-01

This paper presents an optimized H.264/AVC coding system for HDTV displays based on a typical flow with high coding efficiency and statics adaptivity features. For high quality streaming, the codec uses a Binary Arithmetic Encoding/Decoding algorithm with high complexity and a JVCE (Joint Video compression and encryption) scheme. In fact, particular attention is given to simultaneous compression and encryption applications to gain security without compromising the speed of transactions [1]. The proposed design allows us to encrypt the information using a pseudo-random number generator (PRNG). Thus we achieved the two operations (compression and encryption) simultaneously and in a dependent manner which is a novelty in this kind of architecture. Moreover, we investigated the hardware implementation of CABAC (Context-based adaptive Binary Arithmetic Coding) codec. The proposed architecture is based on optimized binarizer/de-binarizer to handle significant pixel rates videos with low cost and high performance for most frequent SEs. This was checked using HD video frames. The obtained synthesis results using an FPGA (Xilinx's ISE) show that our design is relevant to code main profile video stream.

Data compression with applications to digital radiology

International Nuclear Information System (INIS)

Elnahas, S.E.

1985-01-01

The structure of arithmetic codes is defined in terms of source parsing trees. The theoretical derivations of algorithms for the construction of optimal and sub-optimal structures are presented. The software simulation results demonstrate how arithmetic coding out performs variable-length to variable-length coding. Linear predictive coding is presented for the compression of digital diagnostic images from several imaging modalities including computed tomography, nuclear medicine, ultrasound, and magnetic resonance imaging. The problem of designing optimal predictors is formulated and alternative solutions are discussed. The results indicate that noiseless compression factors between 1.7 and 7.4 can be achieved. With nonlinear predictive coding, noisy and noiseless compression techniques are combined in a novel way that may have a potential impact on picture archiving and communication systems in radiology. Adaptive fast discrete cosine transform coding systems are used as nonlinear block predictors, and optimal delta modulation systems are used as nonlinear sequential predictors. The off-line storage requirements for archiving diagnostic images are reasonably reduced by the nonlinear block predictive coding. The online performance, however, seems to be bounded by that of the linear systems. The subjective quality of image imperfect reproductions from the cosine transform coding is promising and prompts future research on the compression of diagnostic images by transform coding systems and the clinical evaluation of these systems

CCAN and TCAN - 1 1/2-D compressible-flow and time-dependent codes for conductor analysis

International Nuclear Information System (INIS)

Gierszewski, P.J.; Wan, A.S.; Yang, T.F.

1983-01-01

This report documents the computer programs CCAN (steady-state Compressible flow Conductor ANalysis) and TCAN (Time-dependent incompressible-flow Conductor ANalysis). These codes calculate temperature, pressure, power and other engineering quantities along the length of an actively-cooled electrical conductor. Present versions contain detailed property information for copper and aluminum conductors; and gaseous helium, liquid nitrogen and water coolants. CCAN and TCAN are available on the NMFECC CDC 7600

Reliability-Based Code Calibration

DEFF Research Database (Denmark)

Faber, M.H.; Sørensen, John Dalsgaard

2003-01-01

The present paper addresses fundamental concepts of reliability based code calibration. First basic principles of structural reliability theory are introduced and it is shown how the results of FORM based reliability analysis may be related to partial safety factors and characteristic values....... Thereafter the code calibration problem is presented in its principal decision theoretical form and it is discussed how acceptable levels of failure probability (or target reliabilities) may be established. Furthermore suggested values for acceptable annual failure probabilities are given for ultimate...... and serviceability limit states. Finally the paper describes the Joint Committee on Structural Safety (JCSS) recommended procedure - CodeCal - for the practical implementation of reliability based code calibration of LRFD based design codes....

n-Gram-Based Text Compression

Science.gov (United States)

Duong, Hieu N.; Snasel, Vaclav

2016-01-01

We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods. PMID:27965708

n-Gram-Based Text Compression

Directory of Open Access Journals (Sweden)

Vu H. Nguyen

2016-01-01

Full Text Available We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.

Modified Three-Step Search Block Matching Motion Estimation and Weighted Finite Automata based Fractal Video Compression

Directory of Open Access Journals (Sweden)

Shailesh Kamble

2017-08-01

Full Text Available The major challenge with fractal image/video coding technique is that, it requires more encoding time. Therefore, how to reduce the encoding time is the research component remains in the fractal coding. Block matching motion estimation algorithms are used, to reduce the computations performed in the process of encoding. The objective of the proposed work is to develop an approach for video coding using modified three step search (MTSS block matching algorithm and weighted finite automata (WFA coding with a specific focus on reducing the encoding time. The MTSS block matching algorithm are used for computing motion vectors between the two frames i.e. displacement of pixels and WFA is used for the coding as it behaves like the Fractal Coding (FC. WFA represents an image (frame or motion compensated prediction error based on the idea of fractal that the image has self-similarity in itself. The self-similarity is sought from the symmetry of an image, so the encoding algorithm divides an image into multi-levels of quad-tree segmentations and creates an automaton from the sub-images. The proposed MTSS block matching algorithm is based on the combination of rectangular and hexagonal search pattern and compared with the existing New Three-Step Search (NTSS, Three-Step Search (TSS, and Efficient Three-Step Search (ETSS block matching estimation algorithm. The performance of the proposed MTSS block matching algorithm is evaluated on the basis of performance evaluation parameters i.e. mean absolute difference (MAD and average search points required per frame. Mean of absolute difference (MAD distortion function is used as the block distortion measure (BDM. Finally, developed approaches namely, MTSS and WFA, MTSS and FC, and Plane FC (applied on every frame are compared with each other. The experimentations are carried out on the standard uncompressed video databases, namely, akiyo, bus, mobile, suzie, traffic, football, soccer, ice etc. Developed

3D Video Compression and Transmission

DEFF Research Database (Denmark)

Zamarin, Marco; Forchhammer, Søren

In this short paper we provide a brief introduction to 3D and multi-view video technologies - like three-dimensional television and free-viewpoint video - focusing on the aspects related to data compression and transmission. Geometric information represented by depth maps is introduced as well...... and a novel coding scheme for multi-view data able to exploit geometric information in order to improve compression performances is briefly described and compared against the classical solution based on multi-view motion estimation. Future research directions close the paper....

Characterization of coded random access with compressive sensing based multi user detection

DEFF Research Database (Denmark)

Ji, Yalei; Stefanovic, Cedomir; Bockelmann, Carsten

2014-01-01

The emergence of Machine-to-Machine (M2M) communication requires new Medium Access Control (MAC) schemes and physical (PHY) layer concepts to support a massive number of access requests. The concept of coded random access, introduced recently, greatly outperforms other random access methods...... coded random access with CS-MUD on the PHY layer and show very promising results for the resulting protocol....

Bit Plane Coding based Steganography Technique for JPEG2000 Images and Videos

Directory of Open Access Journals (Sweden)

Geeta Kasana

2016-02-01

Full Text Available In this paper, a Bit Plane Coding (BPC based steganography technique for JPEG2000 images and Motion JPEG2000 video is proposed. Embedding in this technique is performed in the lowest significant bit planes of the wavelet coefficients of a cover image. In JPEG2000 standard, the number of bit planes of wavelet coefficients to be used in encoding is dependent on the compression rate and are used in Tier-2 process of JPEG2000. In the proposed technique, Tier-1 and Tier-2 processes of JPEG2000 and Motion JPEG2000 are executed twice on the encoder side to collect the information about the lowest bit planes of all code blocks of a cover image, which is utilized in embedding and transmitted to the decoder. After embedding secret data, Optimal Pixel Adjustment Process (OPAP is applied on stego images to enhance its visual quality. Experimental results show that proposed technique provides large embedding capacity and better visual quality of stego images than existing steganography techniques for JPEG2000 compressed images and videos. Extracted secret image is similar to the original secret image.

High Bit-Depth Medical Image Compression With HEVC.

Science.gov (United States)

Parikh, Saurin S; Ruiz, Damian; Kalva, Hari; Fernandez-Escribano, Gerardo; Adzic, Velibor

2018-03-01

Efficient storing and retrieval of medical images has direct impact on reducing costs and improving access in cloud-based health care services. JPEG 2000 is currently the commonly used compression format for medical images shared using the DICOM standard. However, new formats such as high efficiency video coding (HEVC) can provide better compression efficiency compared to JPEG 2000. Furthermore, JPEG 2000 is not suitable for efficiently storing image series and 3-D imagery. Using HEVC, a single format can support all forms of medical images. This paper presents the use of HEVC for diagnostically acceptable medical image compression, focusing on compression efficiency compared to JPEG 2000. Diagnostically acceptable lossy compression and complexity of high bit-depth medical image compression are studied. Based on an established medically acceptable compression range for JPEG 2000, this paper establishes acceptable HEVC compression range for medical imaging applications. Experimental results show that using HEVC can increase the compression performance, compared to JPEG 2000, by over 54%. Along with this, a new method for reducing computational complexity of HEVC encoding for medical images is proposed. Results show that HEVC intra encoding complexity can be reduced by over 55% with negligible increase in file size.

Light-weight reference-based compression of FASTQ data.

Science.gov (United States)

Zhang, Yongpeng; Li, Linsen; Yang, Yanli; Yang, Xiao; He, Shan; Zhu, Zexuan

2015-06-09

The exponential growth of next generation sequencing (NGS) data has posed big challenges to data storage, management and archive. Data compression is one of the effective solutions, where reference-based compression strategies can typically achieve superior compression ratios compared to the ones not relying on any reference. This paper presents a lossless light-weight reference-based compression algorithm namely LW-FQZip to compress FASTQ data. The three components of any given input, i.e., metadata, short reads and quality score strings, are first parsed into three data streams in which the redundancy information are identified and eliminated independently. Particularly, well-designed incremental and run-length-limited encoding schemes are utilized to compress the metadata and quality score streams, respectively. To handle the short reads, LW-FQZip uses a novel light-weight mapping model to fast map them against external reference sequence(s) and produce concise alignment results for storage. The three processed data streams are then packed together with some general purpose compression algorithms like LZMA. LW-FQZip was evaluated on eight real-world NGS data sets and achieved compression ratios in the range of 0.111-0.201. This is comparable or superior to other state-of-the-art lossless NGS data compression algorithms. LW-FQZip is a program that enables efficient lossless FASTQ data compression. It contributes to the state of art applications for NGS data storage and transmission. LW-FQZip is freely available online at: http://csse.szu.edu.cn/staff/zhuzx/LWFQZip.

Content layer progressive coding of digital maps

DEFF Research Database (Denmark)

Forchhammer, Søren; Jensen, Ole Riis

2000-01-01

A new lossless context based method is presented for content progressive coding of limited bits/pixel images, such as maps, company logos, etc., common on the WWW. Progressive encoding is achieved by separating the image into content layers based on other predefined information. Information from...... already coded layers are used when coding subsequent layers. This approach is combined with efficient template based context bi-level coding, context collapsing methods for multi-level images and arithmetic coding. Relative pixel patterns are used to collapse contexts. The number of contexts are analyzed....... The new methods outperform existing coding schemes coding digital maps and in addition provide progressive coding. Compared to the state-of-the-art PWC coder, the compressed size is reduced to 60-70% on our layered test images....

The mathematical theory of signal processing and compression-designs

Science.gov (United States)

Feria, Erlan H.

2006-05-01

The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

A Psychoacoustic-Based Multiple Audio Object Coding Approach via Intra-Object Sparsity

Directory of Open Access Journals (Sweden)

Maoshen Jia

2017-12-01

Full Text Available Rendering spatial sound scenes via audio objects has become popular in recent years, since it can provide more flexibility for different auditory scenarios, such as 3D movies, spatial audio communication and virtual classrooms. To facilitate high-quality bitrate-efficient distribution for spatial audio objects, an encoding scheme based on intra-object sparsity (approximate k-sparsity of the audio object itself is proposed in this paper. The statistical analysis is presented to validate the notion that the audio object has a stronger sparseness in the Modified Discrete Cosine Transform (MDCT domain than in the Short Time Fourier Transform (STFT domain. By exploiting intra-object sparsity in the MDCT domain, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. To ensure a balanced perception quality of audio objects, a Psychoacoustic-based time-frequency instants sorting algorithm and an energy equalized Number of Preserved Time-Frequency Bins (NPTF allocation strategy are proposed, which are employed in the underlying compression framework. The downmix signal can be further encoded via Scalar Quantized Vector Huffman Coding (SQVH technique at a desirable bitrate, and the side information is transmitted in a lossless manner. Both objective and subjective evaluations show that the proposed encoding scheme outperforms the Sparsity Analysis (SPA approach and Spatial Audio Object Coding (SAOC in cases where eight objects were jointly encoded.

Image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing

Science.gov (United States)

Zhou, Nanrun; Pan, Shumin; Cheng, Shan; Zhou, Zhihong

2016-08-01

Most image encryption algorithms based on low-dimensional chaos systems bear security risks and suffer encryption data expansion when adopting nonlinear transformation directly. To overcome these weaknesses and reduce the possible transmission burden, an efficient image compression-encryption scheme based on hyper-chaotic system and 2D compressive sensing is proposed. The original image is measured by the measurement matrices in two directions to achieve compression and encryption simultaneously, and then the resulting image is re-encrypted by the cycle shift operation controlled by a hyper-chaotic system. Cycle shift operation can change the values of the pixels efficiently. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys distribution simultaneously as a nonlinear encryption system. Simulation results verify the validity and the reliability of the proposed algorithm with acceptable compression and security performance.

EPC: A Provably Secure Permutation Based Compression Function

DEFF Research Database (Denmark)

Bagheri, Nasour; Gauravaram, Praveen; Naderi, Majid

2010-01-01

The security of permutation-based hash functions in the ideal permutation model has been studied when the input-length of compression function is larger than the input-length of the permutation function. In this paper, we consider permutation based compression functions that have input lengths sh...

Techniques for data compression in experimental nuclear physics problems

International Nuclear Information System (INIS)

Byalko, A.A.; Volkov, N.G.; Tsupko-Sitnikov, V.M.

1984-01-01

Techniques and ways for data compression during physical experiments are estimated. Data compression algorithms are divided into three groups: the first one includes the algorithms based on coding and which posses only average indexes by data files, the second group includes algorithms with data processing elements, the third one - algorithms for converted data storage. The greatest promise for the techniques connected with data conversion is concluded. The techniques possess high indexes for compression efficiency and for fast response, permit to store information close to the source one

Optimal, Reliability-Based Code Calibration

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2002-01-01

Reliability based code calibration is considered in this paper. It is described how the results of FORM based reliability analysis may be related to the partial safety factors and characteristic values. The code calibration problem is presented in a decision theoretical form and it is discussed how...... of reliability based code calibration of LRFD based design codes....

Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

Science.gov (United States)

Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

2014-02-01

The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

Content Layer progressive Coding of Digital Maps

DEFF Research Database (Denmark)

Forchhammer, Søren; Jensen, Ole Riis

2002-01-01

A new lossless context based method is presented for content progressive coding of limited bits/pixel images, such as maps, company logos, etc., common on the World Wide Web. Progressive encoding is achieved by encoding the image in content layers based on color level or other predefined...... information. Information from already coded layers are used when coding subsequent layers. This approach is combined with efficient template based context bilevel coding, context collapsing methods for multilevel images and arithmetic coding. Relative pixel patterns are used to collapse contexts. Expressions...... for calculating the resulting number of contexts are given. The new methods outperform existing schemes coding digital maps and in addition provide progressive coding. Compared to the state-of-the-art PWC coder, the compressed size is reduced to 50-70% on our layered map test images....

Speech coding

Energy Technology Data Exchange (ETDEWEB)

Ravishankar, C., Hughes Network Systems, Germantown, MD

1998-05-08

Speech is the predominant means of communication between human beings and since the invention of the telephone by Alexander Graham Bell in 1876, speech services have remained to be the core service in almost all telecommunication systems. Original analog methods of telephony had the disadvantage of speech signal getting corrupted by noise, cross-talk and distortion Long haul transmissions which use repeaters to compensate for the loss in signal strength on transmission links also increase the associated noise and distortion. On the other hand digital transmission is relatively immune to noise, cross-talk and distortion primarily because of the capability to faithfully regenerate digital signal at each repeater purely based on a binary decision. Hence end-to-end performance of the digital link essentially becomes independent of the length and operating frequency bands of the link Hence from a transmission point of view digital transmission has been the preferred approach due to its higher immunity to noise. The need to carry digital speech became extremely important from a service provision point of view as well. Modem requirements have introduced the need for robust, flexible and secure services that can carry a multitude of signal types (such as voice, data and video) without a fundamental change in infrastructure. Such a requirement could not have been easily met without the advent of digital transmission systems, thereby requiring speech to be coded digitally. The term Speech Coding is often referred to techniques that represent or code speech signals either directly as a waveform or as a set of parameters by analyzing the speech signal. In either case, the codes are transmitted to the distant end where speech is reconstructed or synthesized using the received set of codes. A more generic term that is applicable to these techniques that is often interchangeably used with speech coding is the term voice coding. This term is more generic in the sense that the

Full-frame compression of discrete wavelet and cosine transforms

Science.gov (United States)

Lo, Shih-Chung B.; Li, Huai; Krasner, Brian; Freedman, Matthew T.; Mun, Seong K.

1995-04-01

At the foreground of computerized radiology and the filmless hospital are the possibilities for easy image retrieval, efficient storage, and rapid image communication. This paper represents the authors' continuous efforts in compression research on full-frame discrete wavelet (FFDWT) and full-frame discrete cosine transforms (FFDCT) for medical image compression. Prior to the coding, it is important to evaluate the global entropy in the decomposed space. It is because of the minimum entropy, that a maximum compression efficiency can be achieved. In this study, each image was split into the top three most significant bit (MSB) and the remaining remapped least significant bit (RLSB) images. The 3MSB image was compressed by an error-free contour coding and received an average of 0.1 bit/pixel. The RLSB image was either transformed to a multi-channel wavelet or the cosine transform domain for entropy evaluation. Ten x-ray chest radiographs and ten mammograms were randomly selected from our clinical database and were used for the study. Our results indicated that the coding scheme in the FFDCT domain performed better than in FFDWT domain for high-resolution digital chest radiographs and mammograms. From this study, we found that decomposition efficiency in the DCT domain for relatively smooth images is higher than that in the DWT. However, both schemes worked just as well for low resolution digital images. We also found that the image characteristics of the `Lena' image commonly used in the compression literature are very different from those of radiological images. The compression outcome of the radiological images can not be extrapolated from the compression result based on the `Lena.'

Layered compression for high-precision depth data.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

Directory of Open Access Journals (Sweden)

Thomas André

2007-03-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

JPEG2000-Compatible Scalable Scheme for Wavelet-Based Video Coding

Directory of Open Access Journals (Sweden)

André Thomas

2007-01-01

Full Text Available We present a simple yet efficient scalable scheme for wavelet-based video coders, able to provide on-demand spatial, temporal, and SNR scalability, and fully compatible with the still-image coding standard JPEG2000. Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves. Our study shows that scalably encoded sequences have the same or almost the same quality than nonscalably encoded ones, without a significant increase in complexity. A full compatibility with Motion JPEG2000, which tends to be a serious candidate for the compression of high-definition video sequences, is ensured.

Signal Recovery in Compressive Sensing via Multiple Sparsifying Bases

DEFF Research Database (Denmark)

Wijewardhana, U. L.; Belyaev, Evgeny; Codreanu, M.

2017-01-01

is sparse is the key assumption utilized by such algorithms. However, the basis in which the signal is the sparsest is unknown for many natural signals of interest. Instead there may exist multiple bases which lead to a compressible representation of the signal: e.g., an image is compressible in different...... wavelet transforms. We show that a significant performance improvement can be achieved by utilizing multiple estimates of the signal using sparsifying bases in the context of signal reconstruction from compressive samples. Further, we derive a customized interior-point method to jointly obtain multiple...... estimates of a 2-D signal (image) from compressive measurements utilizing multiple sparsifying bases as well as the fact that the images usually have a sparse gradient....

Fixed-Rate Compressed Floating-Point Arrays.

Science.gov (United States)

Lindstrom, Peter

2014-12-01

Current compression schemes for floating-point data commonly take fixed-precision values and compress them to a variable-length bit stream, complicating memory management and random access. We present a fixed-rate, near-lossless compression scheme that maps small blocks of 4(d) values in d dimensions to a fixed, user-specified number of bits per block, thereby allowing read and write random access to compressed floating-point data at block granularity. Our approach is inspired by fixed-rate texture compression methods widely adopted in graphics hardware, but has been tailored to the high dynamic range and precision demands of scientific applications. Our compressor is based on a new, lifted, orthogonal block transform and embedded coding, allowing each per-block bit stream to be truncated at any point if desired, thus facilitating bit rate selection using a single compression scheme. To avoid compression or decompression upon every data access, we employ a software write-back cache of uncompressed blocks. Our compressor has been designed with computational simplicity and speed in mind to allow for the possibility of a hardware implementation, and uses only a small number of fixed-point arithmetic operations per compressed value. We demonstrate the viability and benefits of lossy compression in several applications, including visualization, quantitative data analysis, and numerical simulation.

Double-compression method for biomedical images

Science.gov (United States)

Antonenko, Yevhenii A.; Mustetsov, Timofey N.; Hamdi, Rami R.; Małecka-Massalska, Teresa; Orshubekov, Nurbek; DzierŻak, RóŻa; Uvaysova, Svetlana

2017-08-01

This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.

Compression of seismic data: filter banks and extended transforms, synthesis and adaptation; Compression de donnees sismiques: bancs de filtres et transformees etendues, synthese et adaptation

Energy Technology Data Exchange (ETDEWEB)

Duval, L.

2000-11-01

Wavelet and wavelet packet transforms are the most commonly used algorithms for seismic data compression. Wavelet coefficients are generally quantized and encoded by classical entropy coding techniques. We first propose in this work a compression algorithm based on the wavelet transform. The wavelet transform is used together with a zero-tree type coding, with first use in seismic applications. Classical wavelet transforms nevertheless yield a quite rigid approach, since it is often desirable to adapt the transform stage to the properties of each type of signal. We thus propose a second algorithm using, instead of wavelets, a set of so called 'extended transforms'. These transforms, originating from the filter bank theory, are parameterized. Classical examples are Malvar's Lapped Orthogonal Transforms (LOT) or de Queiroz et al. Generalized Lapped Orthogonal Transforms (GenLOT). We propose several optimization criteria to build 'extended transforms' which are adapted the properties of seismic signals. We further show that these transforms can be used with the same zero-tree type coding technique as used with wavelets. Both proposed algorithms provide exact compression rate choice, block-wise compression (in the case of extended transforms) and partial decompression for quality control or visualization. Performances are tested on a set of actual seismic data. They are evaluated for several quality measures. We also compare them to other seismic compression algorithms. (author)

Recent advances in coding theory for near error-free communications

Science.gov (United States)

Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.

1991-01-01

Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.

Study of CSR longitudinal bunch compression cavity

International Nuclear Information System (INIS)

Yin Dayu; Li Peng; Liu Yong; Xie Qingchun

2009-01-01

The scheme of longitudinal bunch compression cavity for the Cooling Storage Ring (CSR)is an important issue. Plasma physics experiments require high density heavy ion beam and short pulsed bunch,which can be produced by non-adiabatic compression of bunch implemented by a fast compression with 90 degree rotation in the longitudinal phase space. The phase space rotation in fast compression is initiated by a fast jump of the RF-voltage amplitude. For this purpose, the CSR longitudinal bunch compression cavity, loaded with FINEMET-FT-1M is studied and simulated with MAFIA code. In this paper, the CSR longitudinal bunch compression cavity is simulated and the initial bunch length of 238 U 72+ with 250 MeV/u will be compressed from 200 ns to 50 ns.The construction and RF properties of the CSR longitudinal bunch compression cavity are simulated and calculated also with MAFIA code. The operation frequency of the cavity is 1.15 MHz with peak voltage of 80 kV, and the cavity can be used to compress heavy ions in the CSR. (authors)

Adaptive discrete cosine transform coding algorithm for digital mammography

Science.gov (United States)

Baskurt, Atilla M.; Magnin, Isabelle E.; Goutte, Robert

1992-09-01

The need for storage, transmission, and archiving of medical images has led researchers to develop adaptive and efficient data compression techniques. Among medical images, x-ray radiographs of the breast are especially difficult to process because of their particularly low contrast and very fine structures. A block adaptive coding algorithm based on the discrete cosine transform to compress digitized mammograms is described. A homogeneous repartition of the degradation in the decoded images is obtained using a spatially adaptive threshold. This threshold depends on the coding error associated with each block of the image. The proposed method is tested on a limited number of pathological mammograms including opacities and microcalcifications. A comparative visual analysis is performed between the original and the decoded images. Finally, it is shown that data compression with rather high compression rates (11 to 26) is possible in the mammography field.

Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

Directory of Open Access Journals (Sweden)

Xin Tian

2017-06-01

Full Text Available We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online. Clustering is introduced for dictionary learning. A set of dictionaries could be generated, and each dictionary is used for one cluster’s sparse coding. In this way, the signals in one cluster could be well represented by their corresponding dictionaries. A nonparametric Bayesian dictionary learning method is used to learn the dictionaries, which naturally infers an appropriate dictionary size for each cluster. A uniform quantizer and an adaptive arithmetic coding algorithm are adopted to code the sparse coefficients. With comparisons to other state-of-the art approaches, the effectiveness of the proposed method could be validated in the experiments.

Audiovisual focus of attention and its application to Ultra High Definition video compression

Science.gov (United States)

Rerabek, Martin; Nemoto, Hiromi; Lee, Jong-Seok; Ebrahimi, Touradj

2014-02-01

Using Focus of Attention (FoA) as a perceptual process in image and video compression belongs to well-known approaches to increase coding efficiency. It has been shown that foveated coding, when compression quality varies across the image according to region of interest, is more efficient than the alternative coding, when all region are compressed in a similar way. However, widespread use of such foveated compression has been prevented due to two main conflicting causes, namely, the complexity and the efficiency of algorithms for FoA detection. One way around these is to use as much information as possible from the scene. Since most video sequences have an associated audio, and moreover, in many cases there is a correlation between the audio and the visual content, audiovisual FoA can improve efficiency of the detection algorithm while remaining of low complexity. This paper discusses a simple yet efficient audiovisual FoA algorithm based on correlation of dynamics between audio and video signal components. Results of audiovisual FoA detection algorithm are subsequently taken into account for foveated coding and compression. This approach is implemented into H.265/HEVC encoder producing a bitstream which is fully compliant to any H.265/HEVC decoder. The influence of audiovisual FoA in the perceived quality of high and ultra-high definition audiovisual sequences is explored and the amount of gain in compression efficiency is analyzed.

Context based Coding of Binary Shapes by Object Boundary Straightness Analysis

DEFF Research Database (Denmark)

Aghito, Shankar Manuel; Forchhammer, Søren

2004-01-01

A new lossless compression scheme for bilevel images targeted at binary shapes of image and video objects is presented. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding....... Tested on individual images of binary shapes and binary layers of digital maps the algorithm outperforms PWC, JBIG and MPEG-4 CAE. On the binary shapes the code lengths are reduced by 21%, 25%, and 42%, respectively. On the maps the reductions are 34%, 32%, and 59%, respectively. The algorithm is also...

ESE a 2D compressible multiphase flow code developed for MFCI analysis - code validation

International Nuclear Information System (INIS)

Leskovar, M.; Mavko, B.

1998-01-01

ESE (Evaluation of Steam Explosions) is a general second order accurate two-dimensional compressible multiphase flow computer code. It has been developed to model the interaction of molten core debris with water during the first premixing stage of a steam explosion. A steam explosion is a physical event, which may occur during a severe reactor accident following core meltdown when the molten fuel comes into contact with the coolant water. Since the exchanges of mass, momentum and energy are regime dependent, different exchange laws have been incorporated in ESE for the major flow regimes. With ESE a number of premixing experiments performed at the Oxford University and at the QUEOS facility at Forschungszentrum Karlsruhe has been simulated. In these premixing experiments different jets of spheres were injected in a water poll. The ESE validation plan was carefully chosen, starting from very simple, well-defined problems, and gradually working up to more complicated ones. The results of ESE simulations, which were compared to experimental data and also to first order accurate calculations, are presented in form graphs. Most of the ESE results agree qualitatively as quantitatively reasonably well with experimental data and in general better than the results obtained with the first order accurate calculation.(author)

Edge-preserving Intra mode for efficient depth map coding based on H.264/AVC

DEFF Research Database (Denmark)

Zamarin, Marco; Forchhammer, Søren

2014-01-01

Depth-image-based-rendering (DIBR) algorithms for 3D video communication systems based on the “multi-view video plus depth” format are very sensitive to the accuracy of depth information. Specifically, edge regions in the depth data should be preserved in the coding/decoding process to ensure good...... view synthesis performance, which directly affects the overall system performance. This paper proposes a novel scheme for edge-aware Intra depth compression based on the H.264/AVC framework enabled on both Intra (I) and Inter (P) slices. The proposed scheme includes a new Intra mode specifically...

A New Approach for Fingerprint Image Compression

Energy Technology Data Exchange (ETDEWEB)

Mazieres, Bertrand

1997-12-01

The FBI has been collecting fingerprint cards since 1924 and now has over 200 million of them. Digitized with 8 bits of grayscale resolution at 500 dots per inch, it means 2000 terabytes of information. Also, without any compression, transmitting a 10 Mb card over a 9600 baud connection will need 3 hours. Hence we need a compression and a compression as close to lossless as possible: all fingerprint details must be kept. A lossless compression usually do not give a better compression ratio than 2:1, which is not sufficient. Compressing these images with the JPEG standard leads to artefacts which appear even at low compression rates. Therefore the FBI has chosen in 1993 a scheme of compression based on a wavelet transform, followed by a scalar quantization and an entropy coding : the so-called WSQ. This scheme allows to achieve compression ratios of 20:1 without any perceptible loss of quality. The publication of the FBI specifies a decoder, which means that many parameters can be changed in the encoding process: the type of analysis/reconstruction filters, the way the bit allocation is made, the number of Huffman tables used for the entropy coding. The first encoder used 9/7 filters for the wavelet transform and did the bit allocation using a high-rate bit assumption. Since the transform is made into 64 subbands, quite a lot of bands receive only a few bits even at an archival quality compression rate of 0.75 bit/pixel. Thus, after a brief overview of the standard, we will discuss a new approach for the bit-allocation that seems to make more sense where theory is concerned. Then we will talk about some implementation aspects, particularly for the new entropy coder and the features that allow other applications than fingerprint image compression. Finally, we will compare the performances of the new encoder to those of the first encoder.

Disk-based compression of data from genome sequencing.

Science.gov (United States)

Grabowski, Szymon; Deorowicz, Sebastian; Roguski, Łukasz

2015-05-01

High-coverage sequencing data have significant, yet hard to exploit, redundancy. Most FASTQ compressors cannot efficiently compress the DNA stream of large datasets, since the redundancy between overlapping reads cannot be easily captured in the (relatively small) main memory. More interesting solutions for this problem are disk based, where the better of these two, from Cox et al. (2012), is based on the Burrows-Wheeler transform (BWT) and achieves 0.518 bits per base for a 134.0 Gbp human genome sequencing collection with almost 45-fold coverage. We propose overlapping reads compression with minimizers, a compression algorithm dedicated to sequencing reads (DNA only). Our method makes use of a conceptually simple and easily parallelizable idea of minimizers, to obtain 0.317 bits per base as the compression ratio, allowing to fit the 134.0 Gbp dataset into only 5.31 GB of space. http://sun.aei.polsl.pl/orcom under a free license. sebastian.deorowicz@polsl.pl Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

HVS scheme for DICOM image compression: Design and comparative performance evaluation

Energy Technology Data Exchange (ETDEWEB)

Prabhakar, B. [Biomedical and Engineering Division, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu (India)]. E-mail: prabhakarb@iitm.ac.in; Reddy, M. Ramasubba [Biomedical and Engineering Division, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu (India)

2007-07-15

Advanced digital imaging technology in medical domain demands efficient and effective DICOM image compression for progressive image transmission and picture archival. Here a compression system, which incorporates sensitivities of HVS coded with SPIHT quantization, is discussed. The weighting factors derived from luminance CSF are used to transform the wavelet subband coefficients to reflect characteristics of HVS in best possible manner. Mannos et al. and Daly HVS models have been used and results are compared. To evaluate the performance, Eskicioglu chart metric is considered. Experiment is done on both Monochrome and Color Dicom images of MRI, CT, OT, and CR, natural and benchmark images. Reconstructed image through our technique showed improvement in visual quality and Eskicioglu chart metric at same compression ratios. Also the Daly HVS model based compression shows better performance perceptually and quantitatively when compared to Mannos et el. model. Further 'bior4.4' wavelet filter provides better results than 'db9' filter for this compression system. Results give strong evidence that under common boundary conditions; our technique achieves competitive visual quality, compression ratio and coding/decoding time, when compared with jpeg2000 (kakadu)

Fast Coding Unit Encoding Mechanism for Low Complexity Video Coding

OpenAIRE

Gao, Yuan; Liu, Pengyu; Wu, Yueying; Jia, Kebin; Gao, Guandong

2016-01-01

In high efficiency video coding (HEVC), coding tree contributes to excellent compression performance. However, coding tree brings extremely high computational complexity. Innovative works for improving coding tree to further reduce encoding time are stated in this paper. A novel low complexity coding tree mechanism is proposed for HEVC fast coding unit (CU) encoding. Firstly, this paper makes an in-depth study of the relationship among CU distribution, quantization parameter (QP) and content ...

Ultrasound imaging using coded signals

DEFF Research Database (Denmark)

Misaridis, Athanasios

Modulated (or coded) excitation signals can potentially improve the quality and increase the frame rate in medical ultrasound scanners. The aim of this dissertation is to investigate systematically the applicability of modulated signals in medical ultrasound imaging and to suggest appropriate...... methods for coded imaging, with the goal of making better anatomic and flow images and three-dimensional images. On the first stage, it investigates techniques for doing high-resolution coded imaging with improved signal-to-noise ratio compared to conventional imaging. Subsequently it investigates how...... coded excitation can be used for increasing the frame rate. The work includes both simulated results using Field II, and experimental results based on measurements on phantoms as well as clinical images. Initially a mathematical foundation of signal modulation is given. Pulse compression based...

Image and video compression for multimedia engineering fundamentals, algorithms, and standards

CERN Document Server

Shi, Yun Q

2008-01-01

Part I: Fundamentals Introduction Quantization Differential Coding Transform Coding Variable-Length Coding: Information Theory Results (II) Run-Length and Dictionary Coding: Information Theory Results (III) Part II: Still Image Compression Still Image Coding: Standard JPEG Wavelet Transform for Image Coding: JPEG2000 Nonstandard Still Image Coding Part III: Motion Estimation and Compensation Motion Analysis and Motion Compensation Block Matching Pel-Recursive Technique Optical Flow Further Discussion and Summary on 2-D Motion Estimation Part IV: Video Compression Fundam

A Unique Perspective on Data Coding and Decoding

Directory of Open Access Journals (Sweden)

Wen-Yan Wang

2010-12-01

Full Text Available The concept of a loss-less data compression coding method is proposed, and a detailed description of each of its steps follows. Using the Calgary Corpus and Wikipedia data as the experimental samples and compared with existing algorithms, like PAQ or PPMstr, the new coding method could not only compress the source data, but also further re-compress the data produced by the other compression algorithms. The final files are smaller, and by comparison with the original compression ratio, at least 1% redundancy could be eliminated. The new method is simple and easy to realize. Its theoretical foundation is currently under study. The corresponding Matlab source code is provided in  the Appendix.

Unified formulation for URANS and LES in DxUNSp code

Directory of Open Access Journals (Sweden)

Catalin NAE

2009-09-01

Full Text Available The aim of this work is to find a unified and efficient implementation of a LES turbulence model in an existing URANS CFD code, initially based on unsteady RANS equations with a k-ε turbulence model. This code has the capability to be developed for nonreacting/reacting multifluid flows in research applications. The paper intends to present mainly three aspects of this implementation for unstructured mesh based solvers, for high Reynolds compressible flows: the influence of the numerical reconstruction scheme on the results for compressible LES, the influence of the compressible SGS modeling and the efficient implementation of a wall-law based approach for complex geometry. The results will be presented for a test case (3D flow over a square cylinder at Reynolds = 22.000 [0] and compared with experimental data and other simulations. Some details for the computational efficiency and implementation on parallel computer cluster at INCAS will also be presented [0].

A novel chaotic encryption scheme based on arithmetic coding

International Nuclear Information System (INIS)

Mi Bo; Liao Xiaofeng; Chen Yong

2008-01-01

In this paper, under the combination of arithmetic coding and logistic map, a novel chaotic encryption scheme is presented. The plaintexts are encrypted and compressed by using an arithmetic coder whose mapping intervals are changed irregularly according to a keystream derived from chaotic map and plaintext. Performance and security of the scheme are also studied experimentally and theoretically in detail

Hyperspectral image compressing using wavelet-based method

Science.gov (United States)

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.

LiTrack A Fast longitudinal phase space tracking code with graphical user interface

CERN Document Server

Emma, Paul

2005-01-01

Many linear accelerators, such as linac-based light sources and linear colliders, apply longitudinal phase space manipulations in their design, including electron bunch compression and wakefield-induced energy spread control. Several computer codes handle such issues, but most require detailed information on the transverse focusing lattice. In fact, in most linear accelerators, the transverse distributions do not significantly affect the longitudinal, and can be ignored initially. This allows the use of a fast 2D code to study longitudinal aspects without time-consuming considerations of the transverse focusing. LiTrack is based on a 15-year old code (same name) originally written by one of us (KB), which is now a MATLAB-based code with additional features, such as a graphical user interface and output plotting. The single-bunch tracking includes RF acceleration, bunch compression to 3rd order, geometric and resistive wakefields, aperture limits, synchrotron radiation, and flexible output plotting. The code w...

Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation.

Science.gov (United States)

Lan, Cuiling; Shi, Guangming; Wu, Feng

2010-04-01

Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper proposes a novel coding scheme from the H.264 intraframe coding. In the scheme, two new intramodes are developed to better exploit spatial correlation in compound images. The first is the residual scalar quantization (RSQ) mode, where intrapredicted residues are directly quantized and coded without transform. The second is the base colors and index map (BCIM) mode that can be viewed as an adaptive color quantization. In this mode, an image block is represented by several representative colors, referred to as base colors, and an index map to compress. Every block selects its coding mode from two new modes and the previous intramodes in H.264 by rate-distortion optimization (RDO). Experimental results show that the proposed scheme improves the coding efficiency even more than 10 dB at most bit rates for compound images and keeps a comparable efficient performance to H.264 for natural images.

Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

Directory of Open Access Journals (Sweden)

Jianping Hua

2004-01-01

Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing

Directory of Open Access Journals (Sweden)

Zhouzhou Liu

2015-01-01

Full Text Available For wireless network microseismic monitoring and the problems of low compression ratio and high energy consumption of communication, this paper proposes a segmentation compression algorithm according to the characteristics of the microseismic signals and the compression perception theory (CS used in the transmission process. The algorithm will be collected as a number of nonzero elements of data segmented basis, by reducing the number of combinations of nonzero elements within the segment to improve the accuracy of signal reconstruction, while taking advantage of the characteristics of compressive sensing theory to achieve a high compression ratio of the signal. Experimental results show that, in the quantum chaos immune clone refactoring (Q-CSDR algorithm for reconstruction algorithm, under the condition of signal sparse degree higher than 40, to be more than 0.4 of the compression ratio to compress the signal, the mean square error is less than 0.01, prolonging the network life by 2 times.

Video Coding Technique using MPEG Compression Standards

African Journals Online (AJOL)

Akorede

The two dimensional discrete cosine transform (2-D DCT) is an integral part of video and image compression ... solution for the optimum trade-off by applying rate-distortion theory has been ..... Int. J. the computer, the internet and management,.

Parallel Algorithm for Wireless Data Compression and Encryption

Directory of Open Access Journals (Sweden)

Qin Jiancheng

2017-01-01

Full Text Available As the wireless network has limited bandwidth and insecure shared media, the data compression and encryption are very useful for the broadcasting transportation of big data in IoT (Internet of Things. However, the traditional techniques of compression and encryption are neither competent nor efficient. In order to solve this problem, this paper presents a combined parallel algorithm named “CZ algorithm” which can compress and encrypt the big data efficiently. CZ algorithm uses a parallel pipeline, mixes the coding of compression and encryption, and supports the data window up to 1 TB (or larger. Moreover, CZ algorithm can encrypt the big data as a chaotic cryptosystem which will not decrease the compression speed. Meanwhile, a shareware named “ComZip” is developed based on CZ algorithm. The experiment results show that ComZip in 64 b system can get better compression ratio than WinRAR and 7-zip, and it can be faster than 7-zip in the big data compression. In addition, ComZip encrypts the big data without extra consumption of computing resources.

Compressing DNA sequence databases with coil

Directory of Open Access Journals (Sweden)

Hendy Michael D

2008-05-01

Full Text Available Abstract Background Publicly available DNA sequence databases such as GenBank are large, and are growing at an exponential rate. The sheer volume of data being dealt with presents serious storage and data communications problems. Currently, sequence data is usually kept in large "flat files," which are then compressed using standard Lempel-Ziv (gzip compression – an approach which rarely achieves good compression ratios. While much research has been done on compressing individual DNA sequences, surprisingly little has focused on the compression of entire databases of such sequences. In this study we introduce the sequence database compression software coil. Results We have designed and implemented a portable software package, coil, for compressing and decompressing DNA sequence databases based on the idea of edit-tree coding. coil is geared towards achieving high compression ratios at the expense of execution time and memory usage during compression – the compression time represents a "one-off investment" whose cost is quickly amortised if the resulting compressed file is transmitted many times. Decompression requires little memory and is extremely fast. We demonstrate a 5% improvement in compression ratio over state-of-the-art general-purpose compression tools for a large GenBank database file containing Expressed Sequence Tag (EST data. Finally, coil can efficiently encode incremental additions to a sequence database. Conclusion coil presents a compelling alternative to conventional compression of flat files for the storage and distribution of DNA sequence databases having a narrow distribution of sequence lengths, such as EST data. Increasing compression levels for databases having a wide distribution of sequence lengths is a direction for future work.

Worst configurations (instantons) for compressed sensing over reals: a channel coding approach

International Nuclear Information System (INIS)

Chertkov, Michael; Chilappagari, Shashi K.; Vasic, Bane

2010-01-01

We consider Linear Programming (LP) solution of a Compressed Sensing (CS) problem over reals, also known as the Basis Pursuit (BasP) algorithm. The BasP allows interpretation as a channel-coding problem, and it guarantees the error-free reconstruction over reals for properly chosen measurement matrix and sufficiently sparse error vectors. In this manuscript, we examine how the BasP performs on a given measurement matrix and develop a technique to discover sparse vectors for which the BasP fails. The resulting algorithm is a generalization of our previous results on finding the most probable error-patterns, so called instantons, degrading performance of a finite size Low-Density Parity-Check (LDPC) code in the error-floor regime. The BasP fails when its output is different from the actual error-pattern. We design CS-Instanton Search Algorithm (ISA) generating a sparse vector, called CS-instanton, such that the BasP fails on the instanton, while its action on any modification of the CS-instanton decreasing a properly defined norm is successful. We also prove that, given a sufficiently dense random input for the error-vector, the CS-ISA converges to an instanton in a small finite number of steps. Performance of the CS-ISA is tested on example of a randomly generated 512 * 120 matrix, that outputs the shortest instanton (error vector) pattern of length 11.

Binaural model-based dynamic-range compression.

Science.gov (United States)

Ernst, Stephan M A; Kortlang, Steffen; Grimm, Giso; Bisitz, Thomas; Kollmeier, Birger; Ewert, Stephan D

2018-01-26

Binaural cues such as interaural level differences (ILDs) are used to organise auditory perception and to segregate sound sources in complex acoustical environments. In bilaterally fitted hearing aids, dynamic-range compression operating independently at each ear potentially alters these ILDs, thus distorting binaural perception and sound source segregation. A binaurally-linked model-based fast-acting dynamic compression algorithm designed to approximate the normal-hearing basilar membrane (BM) input-output function in hearing-impaired listeners is suggested. A multi-center evaluation in comparison with an alternative binaural and two bilateral fittings was performed to assess the effect of binaural synchronisation on (a) speech intelligibility and (b) perceived quality in realistic conditions. 30 and 12 hearing impaired (HI) listeners were aided individually with the algorithms for both experimental parts, respectively. A small preference towards the proposed model-based algorithm in the direct quality comparison was found. However, no benefit of binaural-synchronisation regarding speech intelligibility was found, suggesting a dominant role of the better ear in all experimental conditions. The suggested binaural synchronisation of compression algorithms showed a limited effect on the tested outcome measures, however, linking could be situationally beneficial to preserve a natural binaural perception of the acoustical environment.

Improved entropy encoding for high efficient video coding standard

Directory of Open Access Journals (Sweden)

B.S. Sunil Kumar

2018-03-01

Full Text Available The High Efficiency Video Coding (HEVC has better coding efficiency, but the encoding performance has to be improved to meet the growing multimedia applications. This paper improves the standard entropy encoding by introducing the optimized weighing parameters, so that higher rate of compression can be accomplished over the standard entropy encoding. The optimization is performed using the recently introduced firefly algorithm. The experimentation is carried out using eight benchmark video sequences and the PSNR for varying rate of data transmission is investigated. Comparative analysis based on the performance statistics is made with the standard entropy encoding. From the obtained results, it is clear that the originality of the decoded video sequence is preserved far better than the proposed method, though the compression rate is increased. Keywords: Entropy, Encoding, HEVC, PSNR, Compression

Blind compressed sensing image reconstruction based on alternating direction method

Science.gov (United States)

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.

Convolutional coding techniques for data protection

Science.gov (United States)

Massey, J. L.

1975-01-01

Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described.

Single exposure optically compressed imaging and visualization using random aperture coding

Energy Technology Data Exchange (ETDEWEB)

Stern, A [Electro Optical Unit, Ben Gurion University of the Negev, Beer-Sheva 84105 (Israel); Rivenson, Yair [Department of Electrical and Computer Engineering, Ben Gurion University of the Negev, Beer-Sheva 84105 (Israel); Javidi, Bahrain [Department of Electrical and Computer Engineering, University of Connecticut, Storrs, Connecticut 06269-1157 (United States)], E-mail: stern@bgu.ac.il

2008-11-01

The common approach in digital imaging follows the sample-then-compress framework. According to this approach, in the first step as many pixels as possible are captured and in the second step the captured image is compressed by digital means. The recently introduced theory of compressed sensing provides the mathematical foundation necessary to combine these two steps in a single one, that is, to compress the information optically before it is recorded. In this paper we overview and extend an optical implementation of compressed sensing theory that we have recently proposed. With this new imaging approach the compression is accomplished inherently in the optical acquisition step. The primary feature of this imaging approach is a randomly encoded aperture realized by means of a random phase screen. The randomly encoded aperture implements random projection of the object field in the image plane. Using a single exposure, a randomly encoded image is captured which can be decoded by proper decoding algorithm.

Lossless compression for 3D PET

International Nuclear Information System (INIS)

Macq, B.; Sibomana, M.; Coppens, A.; Bol, A.; Michel, C.

1994-01-01

A new adaptive scheme is proposed for the lossless compression of positron emission tomography (PET) sinogram data. The algorithm uses an adaptive differential pulse code modulator (ADPCM) followed by a universal variable length coder (UVLC). Contrasting with Lempel-Ziv (LZ), which operates on a whole sinogram, UVLC operates very efficiently on short data blocks. This is a major advantage for real-time implementation. The algorithm is adaptive and codes data after some on-line estimations of the statistics inside each block. Its efficiency is tested when coding dynamic and static scans from two PET scanners and reaches asymptotically the entropy limit for long frames. For very short 3D frames, the new algorithm is twice more efficient than LZ. Since an ASIC implementing a similar UVLC scheme is available today, a similar one should be able to sustain PET data lossless compression and decompression at a rate of 27 MBytes/sec. This algorithm is consequently a good candidate for the next generation of lossless compression engine

Lossless compression of multispectral images using spectral information

Science.gov (United States)

Ma, Long; Shi, Zelin; Tang, Xusheng

2009-10-01

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

An evaluation of the effect of JPEG, JPEG2000, and H.264/AVC on CQR codes decoding process

Science.gov (United States)

Vizcarra Melgar, Max E.; Farias, Mylène C. Q.; Zaghetto, Alexandre

2015-02-01

This paper presents a binarymatrix code based on QR Code (Quick Response Code), denoted as CQR Code (Colored Quick Response Code), and evaluates the effect of JPEG, JPEG2000 and H.264/AVC compression on the decoding process. The proposed CQR Code has three additional colors (red, green and blue), what enables twice as much storage capacity when compared to the traditional black and white QR Code. Using the Reed-Solomon error-correcting code, the CQR Code model has a theoretical correction capability of 38.41%. The goal of this paper is to evaluate the effect that degradations inserted by common image compression algorithms have on the decoding process. Results show that a successful decoding process can be achieved for compression rates up to 0.3877 bits/pixel, 0.1093 bits/pixel and 0.3808 bits/pixel for JPEG, JPEG2000 and H.264/AVC formats, respectively. The algorithm that presents the best performance is the H.264/AVC, followed by the JPEG2000, and JPEG.

DNABIT Compress – Genome compression algorithm

OpenAIRE

Rajarajeswari, Pothuraju; Apparao, Allam

2011-01-01

Data compression is concerned with how information is organized in data. Efficient storage means removal of redundancy from the data being stored in the DNA molecule. Data compression algorithms remove redundancy and are used to understand biologically important molecules. We present a compression algorithm, “DNABIT Compress” for DNA sequences based on a novel algorithm of assigning binary bits for smaller segments of DNA bases to compress both repetitive and non repetitive DNA sequence. Our ...

Dynamic code block size for JPEG 2000

Science.gov (United States)

Tsai, Ping-Sing; LeCornec, Yann

2008-02-01

Since the standardization of the JPEG 2000, it has found its way into many different applications such as DICOM (digital imaging and communication in medicine), satellite photography, military surveillance, digital cinema initiative, professional video cameras, and so on. The unified framework of the JPEG 2000 architecture makes practical high quality real-time compression possible even in video mode, i.e. motion JPEG 2000. In this paper, we present a study of the compression impact using dynamic code block size instead of fixed code block size as specified in the JPEG 2000 standard. The simulation results show that there is no significant impact on compression if dynamic code block sizes are used. In this study, we also unveil the advantages of using dynamic code block sizes.

Compressing Data Cube in Parallel OLAP Systems

Directory of Open Access Journals (Sweden)

Frank Dehne

2007-03-01

Full Text Available This paper proposes an efficient algorithm to compress the cubes in the progress of the parallel data cube generation. This low overhead compression mechanism provides block-by-block and record-by-record compression by using tuple difference coding techniques, thereby maximizing the compression ratio and minimizing the decompression penalty at run-time. The experimental results demonstrate that the typical compression ratio is about 30:1 without sacrificing running time. This paper also demonstrates that the compression method is suitable for Hilbert Space Filling Curve, a mechanism widely used in multi-dimensional indexing.

DNA barcode goes two-dimensions: DNA QR code web server.

Science.gov (United States)

Liu, Chang; Shi, Linchun; Xu, Xiaolan; Li, Huan; Xing, Hang; Liang, Dong; Jiang, Kun; Pang, Xiaohui; Song, Jingyuan; Chen, Shilin

2012-01-01

The DNA barcoding technology uses a standard region of DNA sequence for species identification and discovery. At present, "DNA barcode" actually refers to DNA sequences, which are not amenable to information storage, recognition, and retrieval. Our aim is to identify the best symbology that can represent DNA barcode sequences in practical applications. A comprehensive set of sequences for five DNA barcode markers ITS2, rbcL, matK, psbA-trnH, and CO1 was used as the test data. Fifty-three different types of one-dimensional and ten two-dimensional barcode symbologies were compared based on different criteria, such as coding capacity, compression efficiency, and error detection ability. The quick response (QR) code was found to have the largest coding capacity and relatively high compression ratio. To facilitate the further usage of QR code-based DNA barcodes, a web server was developed and is accessible at http://qrfordna.dnsalias.org. The web server allows users to retrieve the QR code for a species of interests, convert a DNA sequence to and from a QR code, and perform species identification based on local and global sequence similarities. In summary, the first comprehensive evaluation of various barcode symbologies has been carried out. The QR code has been found to be the most appropriate symbology for DNA barcode sequences. A web server has also been constructed to allow biologists to utilize QR codes in practical DNA barcoding applications.

DNA barcode goes two-dimensions: DNA QR code web server.

Directory of Open Access Journals (Sweden)

Chang Liu

Full Text Available The DNA barcoding technology uses a standard region of DNA sequence for species identification and discovery. At present, "DNA barcode" actually refers to DNA sequences, which are not amenable to information storage, recognition, and retrieval. Our aim is to identify the best symbology that can represent DNA barcode sequences in practical applications. A comprehensive set of sequences for five DNA barcode markers ITS2, rbcL, matK, psbA-trnH, and CO1 was used as the test data. Fifty-three different types of one-dimensional and ten two-dimensional barcode symbologies were compared based on different criteria, such as coding capacity, compression efficiency, and error detection ability. The quick response (QR code was found to have the largest coding capacity and relatively high compression ratio. To facilitate the further usage of QR code-based DNA barcodes, a web server was developed and is accessible at http://qrfordna.dnsalias.org. The web server allows users to retrieve the QR code for a species of interests, convert a DNA sequence to and from a QR code, and perform species identification based on local and global sequence similarities. In summary, the first comprehensive evaluation of various barcode symbologies has been carried out. The QR code has been found to be the most appropriate symbology for DNA barcode sequences. A web server has also been constructed to allow biologists to utilize QR codes in practical DNA barcoding applications.

StirMark Benchmark: audio watermarking attacks based on lossy compression

Science.gov (United States)

Steinebach, Martin; Lang, Andreas; Dittmann, Jana

2002-04-01

StirMark Benchmark is a well-known evaluation tool for watermarking robustness. Additional attacks are added to it continuously. To enable application based evaluation, in our paper we address attacks against audio watermarks based on lossy audio compression algorithms to be included in the test environment. We discuss the effect of different lossy compression algorithms like MPEG-2 audio Layer 3, Ogg or VQF on a selection of audio test data. Our focus is on changes regarding the basic characteristics of the audio data like spectrum or average power and on removal of embedded watermarks. Furthermore we compare results of different watermarking algorithms and show that lossy compression is still a challenge for most of them. There are two strategies for adding evaluation of robustness against lossy compression to StirMark Benchmark: (a) use of existing free compression algorithms (b) implementation of a generic lossy compression simulation. We discuss how such a model can be implemented based on the results of our tests. This method is less complex, as no real psycho acoustic model has to be applied. Our model can be used for audio watermarking evaluation of numerous application fields. As an example, we describe its importance for e-commerce applications with watermarking security.

Curvelet-based compressive sensing for InSAR raw data

Science.gov (United States)

Costa, Marcello G.; da Silva Pinho, Marcelo; Fernandes, David

2015-10-01

The aim of this work is to evaluate the compression performance of SAR raw data for interferometry applications collected by airborne from BRADAR (Brazilian SAR System operating in X and P bands) using the new approach based on compressive sensing (CS) to achieve an effective recovery with a good phase preserving. For this framework is desirable a real-time capability, where the collected data can be compressed to reduce onboard storage and bandwidth required for transmission. In the CS theory, a sparse unknown signals can be recovered from a small number of random or pseudo-random measurements by sparsity-promoting nonlinear recovery algorithms. Therefore, the original signal can be significantly reduced. To achieve the sparse representation of SAR signal, was done a curvelet transform. The curvelets constitute a directional frame, which allows an optimal sparse representation of objects with discontinuities along smooth curves as observed in raw data and provides an advanced denoising optimization. For the tests were made available a scene of 8192 x 2048 samples in range and azimuth in X-band with 2 m of resolution. The sparse representation was compressed using low dimension measurements matrices in each curvelet subband. Thus, an iterative CS reconstruction method based on IST (iterative soft/shrinkage threshold) was adjusted to recover the curvelets coefficients and then the original signal. To evaluate the compression performance were computed the compression ratio (CR), signal to noise ratio (SNR), and because the interferometry applications require more reconstruction accuracy the phase parameters like the standard deviation of the phase (PSD) and the mean phase error (MPE) were also computed. Moreover, in the image domain, a single-look complex image was generated to evaluate the compression effects. All results were computed in terms of sparsity analysis to provides an efficient compression and quality recovering appropriated for inSAR applications

Signal Compression in Automatic Ultrasonic testing of Rails

Directory of Open Access Journals (Sweden)

Tomasz Ciszewski

2007-01-01

Full Text Available Full recording of the most important information carried by the ultrasonic signals allows realizing statistical analysis of measurement data. Statistical analysis of the results gathered during automatic ultrasonic tests gives data which lead, together with use of features of measuring method, differential lossy coding and traditional method of lossless data compression (Huffman’s coding, dictionary coding, to a comprehensive, efficient data compression algorithm. The subject of the article is to present the algorithm and the benefits got by using it in comparison to alternative compression methods. Storage of large amount  of data allows to create an electronic catalogue of ultrasonic defects. If it is created, the future qualification system training in the new solutions of the automat for test in rails will be possible.

Coding of Depth Images for 3DTV

DEFF Research Database (Denmark)

Zamarin, Marco; Forchhammer, Søren

In this short paper a brief overview of the topic of coding and compression of depth images for multi-view image and video coding is provided. Depth images represent a convenient way to describe distances in the 3D scene, useful for 3D video processing purposes. Standard approaches...... for the compression of depth images are described and compared against some recent specialized algorithms able to achieve higher compression performances. Future research directions close the paper....

QC-LDPC code-based cryptography

CERN Document Server

Baldi, Marco

2014-01-01

This book describes the fundamentals of cryptographic primitives based on quasi-cyclic low-density parity-check (QC-LDPC) codes, with a special focus on the use of these codes in public-key cryptosystems derived from the McEliece and Niederreiter schemes. In the first part of the book, the main characteristics of QC-LDPC codes are reviewed, and several techniques for their design are presented, while tools for assessing the error correction performance of these codes are also described. Some families of QC-LDPC codes that are best suited for use in cryptography are also presented. The second part of the book focuses on the McEliece and Niederreiter cryptosystems, both in their original forms and in some subsequent variants. The applicability of QC-LDPC codes in these frameworks is investigated by means of theoretical analyses and numerical tools, in order to assess their benefits and drawbacks in terms of system efficiency and security. Several examples of QC-LDPC code-based public key cryptosystems are prese...

Research of Block-Based Motion Estimation Methods for Video Compression

Directory of Open Access Journals (Sweden)

Tropchenko Andrey

2016-08-01

Full Text Available This work is a review of the block-based algorithms used for motion estimation in video compression. It researches different types of block-based algorithms that range from the simplest named Full Search to the fast adaptive algorithms like Hierarchical Search. The algorithms evaluated in this paper are widely accepted by the video compressing community and have been used in implementing various standards, such as MPEG-4 Visual and H.264. The work also presents a very brief introduction to the entire flow of video compression.

The possibilities of compressed sensing based migration

KAUST Repository

Aldawood, Ali

2013-09-22

Linearized waveform inversion or Least-square migration helps reduce migration artifacts caused by limited acquisition aperture, coarse sampling of sources and receivers, and low subsurface illumination. However, leastsquare migration, based on L2-norm minimization of the misfit function, tends to produce a smeared (smoothed) depiction of the true subsurface reflectivity. Assuming that the subsurface reflectivity distribution is a sparse signal, we use a compressed-sensing (Basis Pursuit) algorithm to retrieve this sparse distribution from a small number of linear measurements. We applied a compressed-sensing algorithm to image a synthetic fault model using dense and sparse acquisition geometries. Tests on synthetic data demonstrate the ability of compressed-sensing to produce highly resolved migrated images. We, also, studied the robustness of the Basis Pursuit algorithm in the presence of Gaussian random noise.

The possibilities of compressed sensing based migration

KAUST Repository

Aldawood, Ali; Hoteit, Ibrahim; Alkhalifah, Tariq Ali

2013-01-01

Linearized waveform inversion or Least-square migration helps reduce migration artifacts caused by limited acquisition aperture, coarse sampling of sources and receivers, and low subsurface illumination. However, leastsquare migration, based on L2-norm minimization of the misfit function, tends to produce a smeared (smoothed) depiction of the true subsurface reflectivity. Assuming that the subsurface reflectivity distribution is a sparse signal, we use a compressed-sensing (Basis Pursuit) algorithm to retrieve this sparse distribution from a small number of linear measurements. We applied a compressed-sensing algorithm to image a synthetic fault model using dense and sparse acquisition geometries. Tests on synthetic data demonstrate the ability of compressed-sensing to produce highly resolved migrated images. We, also, studied the robustness of the Basis Pursuit algorithm in the presence of Gaussian random noise.

Fast lossless compression via cascading Bloom filters.

Science.gov (United States)

Rozov, Roye; Shamir, Ron; Halperin, Eran

2014-01-01

Data from large Next Generation Sequencing (NGS) experiments present challenges both in terms of costs associated with storage and in time required for file transfer. It is sometimes possible to store only a summary relevant to particular applications, but generally it is desirable to keep all information needed to revisit experimental results in the future. Thus, the need for efficient lossless compression methods for NGS reads arises. It has been shown that NGS-specific compression schemes can improve results over generic compression methods, such as the Lempel-Ziv algorithm, Burrows-Wheeler transform, or Arithmetic Coding. When a reference genome is available, effective compression can be achieved by first aligning the reads to the reference genome, and then encoding each read using the alignment position combined with the differences in the read relative to the reference. These reference-based methods have been shown to compress better than reference-free schemes, but the alignment step they require demands several hours of CPU time on a typical dataset, whereas reference-free methods can usually compress in minutes. We present a new approach that achieves highly efficient compression by using a reference genome, but completely circumvents the need for alignment, affording a great reduction in the time needed to compress. In contrast to reference-based methods that first align reads to the genome, we hash all reads into Bloom filters to encode, and decode by querying the same Bloom filters using read-length subsequences of the reference genome. Further compression is achieved by using a cascade of such filters. Our method, called BARCODE, runs an order of magnitude faster than reference-based methods, while compressing an order of magnitude better than reference-free methods, over a broad range of sequencing coverage. In high coverage (50-100 fold), compared to the best tested compressors, BARCODE saves 80-90% of the running time while only increasing space

Compression-based inference on graph data

NARCIS (Netherlands)

Bloem, P.; van den Bosch, A.; Heskes, T.; van Leeuwen, D.

2013-01-01

We investigate the use of compression-based learning on graph data. General purpose compressors operate on bitstrings or other sequential representations. A single graph can be represented sequentially in many ways, which may in uence the performance of sequential compressors. Using Normalized

Lossless compression for 3D PET

International Nuclear Information System (INIS)

Macq, B.; Sibomana, M.; Coppens, A.; Bol, A.; Michel, C.; Baker, K.; Jones, B.

1994-01-01

A new adaptive scheme is proposed for the lossless compression of positron emission tomography (PET) sinogram data. The algorithm uses an adaptive differential pulse code modulator (ADPCM) followed by a universal variable length coder (UVLC). Contrasting with Lempel-Ziv (LZ), which operates on a whole sinogram, UVLC operates very efficiently on short data blocks. This is a major advantage for real-time implementation. The algorithms is adaptive and codes data after some on-line estimations of the statistics inside each block. Its efficiency is tested when coding dynamic and static scans from two PET scanners and reaches asymptotically the entropy limit for long frames. For very short 3D frames, the new algorithm is twice more efficient than LZ. Since an application specific integrated circuit (ASIC) implementing a similar UVLC scheme is available today, a similar one should be able to sustain PET data lossless compression and decompression at a rate of 27 MBytes/sec. This algorithm is consequently a good candidate for the next generation of lossless compression engine

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

Energy Technology Data Exchange (ETDEWEB)

Briles, S.

1996-04-01

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

Development of a Fast Breeder Reactor Fuel Bundle Deformation Analysis Code - BAMBOO: Development of a Pin Dispersion Model and Verification by the Out-of-Pile Compression Test

International Nuclear Information System (INIS)

Uwaba, Tomoyuki; Ito, Masahiro; Ukai, Shigeharu

2004-01-01

To analyze the wire-wrapped fast breeder reactor fuel pin bundle deformation under bundle/duct interaction conditions, the Japan Nuclear Cycle Development Institute has developed the BAMBOO computer code. This code uses the three-dimensional beam element to calculate fuel pin bowing and cladding oval distortion as the primary deformation mechanisms in a fuel pin bundle. The pin dispersion, which is disarrangement of pins in a bundle and would occur during irradiation, was modeled in this code to evaluate its effect on bundle deformation. By applying the contact analysis method commonly used in the finite element method, this model considers the contact conditions at various axial positions as well as the nodal points and can analyze the irregular arrangement of fuel pins with the deviation of the wire configuration.The dispersion model was introduced in the BAMBOO code and verified by using the results of the out-of-pile compression test of the bundle, where the dispersion was caused by the deviation of the wire position. And the effect of the dispersion on the bundle deformation was evaluated based on the analysis results of the code

Two-terminal video coding.

Science.gov (United States)

Yang, Yang; Stanković, Vladimir; Xiong, Zixiang; Zhao, Wei

2009-03-01

Following recent works on the rate region of the quadratic Gaussian two-terminal source coding problem and limit-approaching code designs, this paper examines multiterminal source coding of two correlated, i.e., stereo, video sequences to save the sum rate over independent coding of both sequences. Two multiterminal video coding schemes are proposed. In the first scheme, the left sequence of the stereo pair is coded by H.264/AVC and used at the joint decoder to facilitate Wyner-Ziv coding of the right video sequence. The first I-frame of the right sequence is successively coded by H.264/AVC Intracoding and Wyner-Ziv coding. An efficient stereo matching algorithm based on loopy belief propagation is then adopted at the decoder to produce pixel-level disparity maps between the corresponding frames of the two decoded video sequences on the fly. Based on the disparity maps, side information for both motion vectors and motion-compensated residual frames of the right sequence are generated at the decoder before Wyner-Ziv encoding. In the second scheme, source splitting is employed on top of classic and Wyner-Ziv coding for compression of both I-frames to allow flexible rate allocation between the two sequences. Experiments with both schemes on stereo video sequences using H.264/AVC, LDPC codes for Slepian-Wolf coding of the motion vectors, and scalar quantization in conjunction with LDPC codes for Wyner-Ziv coding of the residual coefficients give a slightly lower sum rate than separate H.264/AVC coding of both sequences at the same video quality.

Three-Dimensional Inverse Transport Solver Based on Compressive Sensing Technique

Science.gov (United States)

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.

Transform coding for hardware-accelerated volume rendering.

Science.gov (United States)

Fout, Nathaniel; Ma, Kwan-Liu

2007-01-01

Hardware-accelerated volume rendering using the GPU is now the standard approach for real-time volume rendering, although limited graphics memory can present a problem when rendering large volume data sets. Volumetric compression in which the decompression is coupled to rendering has been shown to be an effective solution to this problem; however, most existing techniques were developed in the context of software volume rendering, and all but the simplest approaches are prohibitive in a real-time hardware-accelerated volume rendering context. In this paper we present a novel block-based transform coding scheme designed specifically with real-time volume rendering in mind, such that the decompression is fast without sacrificing compression quality. This is made possible by consolidating the inverse transform with dequantization in such a way as to allow most of the reprojection to be precomputed. Furthermore, we take advantage of the freedom afforded by off-line compression in order to optimize the encoding as much as possible while hiding this complexity from the decoder. In this context we develop a new block classification scheme which allows us to preserve perceptually important features in the compression. The result of this work is an asymmetric transform coding scheme that allows very large volumes to be compressed and then decompressed in real-time while rendering on the GPU.

Drift compression and final focus systems for heavy ion inertial fusion

Energy Technology Data Exchange (ETDEWEB)

de Hoon, Michiel Jan Laurens [Univ. of California, Berkeley, CA (United States)

2001-01-01

Longitudinal compression of space-charge dominated beams can be achieved by imposing a head-to-tail velocity tilt on the beam. This tilt has to be carefully tailored, such that it is removed by the longitudinal space-charge repulsion by the time the beam reaches the end of the drift compression section. The transverse focusing lattice should be designed such that all parts of the beam stay approximately matched, while the beam smoothly expands transversely to the larger beam radius needed in the final focus system following drift compression. In this thesis, several drift compression systems were designed within these constraints, based on a given desired pulse shape at the end of drift compression systems were designed within these constraints, based on a given desired pulse shape at the end of drift compression. The occurrence of mismatches due to a rapidly increasing current was analyzed. In addition, the sensitivity of drift compression to errors in the initial velocity tilt and current profile was studied. These calculations were done using a new computer code that accurately calculates the longitudinal electric field in the space-charge dominated regime.

Blind Compressed Sensing Parameter Estimation of Non-cooperative Frequency Hopping Signal

Directory of Open Access Journals (Sweden)

Chen Ying

2016-10-01

Full Text Available To overcome the disadvantages of a non-cooperative frequency hopping communication system, such as a high sampling rate and inadequate prior information, parameter estimation based on Blind Compressed Sensing (BCS is proposed. The signal is precisely reconstructed by the alternating iteration of sparse coding and basis updating, and the hopping frequencies are directly estimated based on the results. Compared with conventional compressive sensing, blind compressed sensing does not require prior information of the frequency hopping signals; hence, it offers an effective solution to the inadequate prior information problem. In the proposed method, the signal is first modeled and then reconstructed by Orthonormal Block Diagonal Blind Compressed Sensing (OBD-BCS, and the hopping frequencies and hop period are finally estimated. The simulation results suggest that the proposed method can reconstruct and estimate the parameters of noncooperative frequency hopping signals with a low signal-to-noise ratio.

Clinical use and evaluation of coded excitation in B-mode images

DEFF Research Database (Denmark)

Misaridis, Athanasios; Pedersen, M. H.; Jensen, Jørgen Arendt

2000-01-01

on a predistorted FM excitation and a mismatched compression filter designed for medical ultrasonic applications. The attenuation effect, analyzed in this paper using the ambiguity function and simulations, dictated the choice of the coded waveform. In this study clinical images, images of wire phantoms......Use of long encoded waveforms can be advantageous in ultrasound imaging, as long as the pulse compression mechanism ensures low range sidelobes and preserves both axial resolution and contrast. A coded excitation/compression scheme was previously presented by our group, which is based...... was programmed to allow alternating excitation on every second frame. That offers the possibility of direct comparison of the same set of image pairs; one with pulsed and one with encoded excitation. Abdominal clinical images from healthy volunteers were acquired and statistically analyzed by means of the auto...

Edge-Based Image Compression with Homogeneous Diffusion

Science.gov (United States)

Mainberger, Markus; Weickert, Joachim

It is well-known that edges contain semantically important image information. In this paper we present a lossy compression method for cartoon-like images that exploits information at image edges. These edges are extracted with the Marr-Hildreth operator followed by hysteresis thresholding. Their locations are stored in a lossless way using JBIG. Moreover, we encode the grey or colour values at both sides of each edge by applying quantisation, subsampling and PAQ coding. In the decoding step, information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. Our experiments show that the suggested method outperforms the widely-used JPEG standard and can even beat the advanced JPEG2000 standard for cartoon-like images.

Verification of the FBR fuel bundle-duct interaction analysis code BAMBOO by the out-of-pile bundle compression test with large diameter pins

Science.gov (United States)

Uwaba, Tomoyuki; Ito, Masahiro; Nemoto, Junichi; Ichikawa, Shoichi; Katsuyama, Kozo

2014-09-01

The BAMBOO computer code was verified by results for the out-of-pile bundle compression test with large diameter pin bundle deformation under the bundle-duct interaction (BDI) condition. The pin diameters of the examined test bundles were 8.5 mm and 10.4 mm, which are targeted as preliminary fuel pin diameters for the upgraded core of the prototype fast breeder reactor (FBR) and for demonstration and commercial FBRs studied in the FaCT project. In the bundle compression test, bundle cross-sectional views were obtained from X-ray computer tomography (CT) images and local parameters of bundle deformation such as pin-to-duct and pin-to-pin clearances were measured by CT image analyses. In the verification, calculation results of bundle deformation obtained by the BAMBOO code analyses were compared with the experimental results from the CT image analyses. The comparison showed that the BAMBOO code reasonably predicts deformation of large diameter pin bundles under the BDI condition by assuming that pin bowing and cladding oval distortion are the major deformation mechanisms, the same as in the case of small diameter pin bundles. In addition, the BAMBOO analysis results confirmed that cladding oval distortion effectively suppresses BDI in large diameter pin bundles as well as in small diameter pin bundles.

Verification of the FBR fuel bundle–duct interaction analysis code BAMBOO by the out-of-pile bundle compression test with large diameter pins

Energy Technology Data Exchange (ETDEWEB)

Uwaba, Tomoyuki, E-mail: uwaba.tomoyuki@jaea.go.jp [Japan Atomic Energy Agency, 4002, Narita-cho, Oarai-machi, Ibaraki 311-1393 (Japan); Ito, Masahiro; Nemoto, Junichi [Japan Atomic Energy Agency, 4002, Narita-cho, Oarai-machi, Ibaraki 311-1393 (Japan); Ichikawa, Shoichi [Japan Atomic Energy Agency, 2-1, Shiraki, Tsuruga-shi, Fukui 919-1279 (Japan); Katsuyama, Kozo [Japan Atomic Energy Agency, 4002, Narita-cho, Oarai-machi, Ibaraki 311-1393 (Japan)

2014-09-15

The BAMBOO computer code was verified by results for the out-of-pile bundle compression test with large diameter pin bundle deformation under the bundle–duct interaction (BDI) condition. The pin diameters of the examined test bundles were 8.5 mm and 10.4 mm, which are targeted as preliminary fuel pin diameters for the upgraded core of the prototype fast breeder reactor (FBR) and for demonstration and commercial FBRs studied in the FaCT project. In the bundle compression test, bundle cross-sectional views were obtained from X-ray computer tomography (CT) images and local parameters of bundle deformation such as pin-to-duct and pin-to-pin clearances were measured by CT image analyses. In the verification, calculation results of bundle deformation obtained by the BAMBOO code analyses were compared with the experimental results from the CT image analyses. The comparison showed that the BAMBOO code reasonably predicts deformation of large diameter pin bundles under the BDI condition by assuming that pin bowing and cladding oval distortion are the major deformation mechanisms, the same as in the case of small diameter pin bundles. In addition, the BAMBOO analysis results confirmed that cladding oval distortion effectively suppresses BDI in large diameter pin bundles as well as in small diameter pin bundles.

LiTrack: A Fast Longitudinal Phase Space Tracking Code with Graphical User Interface

International Nuclear Information System (INIS)

Bane, K.L.F.

2005-01-01

Linac-based light sources and linear colliders typically apply longitudinal phase space manipulations in their design, including electron bunch compression and wakefield-induced energy spread control. Several computer codes handle such issues, but most also require detailed information on the transverse focusing lattice. In fact, in most linear accelerators, the transverse distributions do not significantly affect the longitudinal, and can be ignored initially. This allows the use of a fast 2D code to study longitudinal aspects without time-consuming considerations of the transverse focusing. LiTrack is based on a 15-year old code (same name) originally written by one of us (KB), which is now a Matlab [1] code with additional features, such as graphical user interface, prompt output plotting, and functional call within a script. This single-bunch tracking code includes RF acceleration, bunch compression to 3rd order, geometric and resistive short-range wakefields, aperture limits, synchrotron radiation, and flexible output plotting. The code was used to design both the LCLS [2] and the SPPS [3] projects at SLAC and typically runs 10 5 particles in < 1 minute. We describe the features, show some examples, and provide free access to the code

Compression of computer generated phase-shifting hologram sequence using AVC and HEVC

Science.gov (United States)

Xing, Yafei; Pesquet-Popescu, Béatrice; Dufaux, Frederic

2013-09-01

With the capability of achieving twice the compression ratio of Advanced Video Coding (AVC) with similar reconstruction quality, High Efficiency Video Coding (HEVC) is expected to become the newleading technique of video coding. In order to reduce the storage and transmission burden of digital holograms, in this paper we propose to use HEVC for compressing the phase-shifting digital hologram sequences (PSDHS). By simulating phase-shifting digital holography (PSDH) interferometry, interference patterns between illuminated three dimensional( 3D) virtual objects and the stepwise phase changed reference wave are generated as digital holograms. The hologram sequences are obtained by the movement of the virtual objects and compressed by AVC and HEVC. The experimental results show that AVC and HEVC are efficient to compress PSDHS, with HEVC giving better performance. Good compression rate and reconstruction quality can be obtained with bitrate above 15000kbps.

Tree Coding of Bilevel Images

DEFF Research Database (Denmark)

Martins, Bo; Forchhammer, Søren

1998-01-01

Presently, sequential tree coders are the best general purpose bilevel image coders and the best coders of halftoned images. The current ISO standard, Joint Bilevel Image Experts Group (JBIG), is a good example. A sequential tree coder encodes the data by feeding estimates of conditional...... is one order of magnitude slower than JBIG, obtains excellent and highly robust compression performance. A multipass free tree coding scheme produces superior compression results for all test images. A multipass free template coding scheme produces significantly better results than JBIG for difficult...... images such as halftones. By utilizing randomized subsampling in the template selection, the speed becomes acceptable for practical image coding...

Compression of magnetohydrodynamic simulation data using singular value decomposition

International Nuclear Information System (INIS)

Castillo Negrete, D. del; Hirshman, S.P.; Spong, D.A.; D'Azevedo, E.F.

2007-01-01

Numerical calculations of magnetic and flow fields in magnetohydrodynamic (MHD) simulations can result in extensive data sets. Particle-based calculations in these MHD fields, needed to provide closure relations for the MHD equations, will require communication of this data to multiple processors and rapid interpolation at numerous particle orbit positions. To facilitate this analysis it is advantageous to compress the data using singular value decomposition (SVD, or principal orthogonal decomposition, POD) methods. As an example of the compression technique, SVD is applied to magnetic field data arising from a dynamic nonlinear MHD code. The performance of the SVD compression algorithm is analyzed by calculating Poincare plots for electron orbits in a three-dimensional magnetic field and comparing the results with uncompressed data

Schwarz-based algorithms for compressible flows

Energy Technology Data Exchange (ETDEWEB)

Tidriri, M.D. [ICASE, Hampton, VA (United States)

1996-12-31

To compute steady compressible flows one often uses an implicit discretization approach which leads to a large sparse linear system that must be solved at each time step. In the derivation of this system one often uses a defect-correction procedure, in which the left-hand side of the system is discretized with a lower order approximation than that used for the right-hand side. This is due to storage considerations and computational complexity, and also to the fact that the resulting lower order matrix is better conditioned than the higher order matrix. The resulting schemes are only moderately implicit. In the case of structured, body-fitted grids, the linear system can easily be solved using approximate factorization (AF), which is among the most widely used methods for such grids. However, for unstructured grids, such techniques are no longer valid, and the system is solved using direct or iterative techniques. Because of the prohibitive computational costs and large memory requirements for the solution of compressible flows, iterative methods are preferred. In these defect-correction methods, which are implemented in most CFD computer codes, the mismatch in the right and left hand side operators, together with explicit treatment of the boundary conditions, lead to a severely limited CFL number, which results in a slow convergence to steady state aerodynamic solutions. Many authors have tried to replace explicit boundary conditions with implicit ones. Although they clearly demonstrate that high CFL numbers are possible, the reduction in CPU time is not clear cut.

Coding Local and Global Binary Visual Features Extracted From Video Sequences

Science.gov (United States)

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

Spectral Interpolation on 3 x 3 Stencils for Prediction and Compression

Energy Technology Data Exchange (ETDEWEB)

Ibarria, L; Lindstrom, P; Rossignac, J

2007-06-25

Many scientific, imaging, and geospatial applications produce large high-precision scalar fields sampled on a regular grid. Lossless compression of such data is commonly done using predictive coding, in which weighted combinations of previously coded samples known to both encoder and decoder are used to predict subsequent nearby samples. In hierarchical, incremental, or selective transmission, the spatial pattern of the known neighbors is often irregular and varies from one sample to the next, which precludes prediction based on a single stencil and fixed set of weights. To handle such situations and make the best use of available neighboring samples, we propose a local spectral predictor that offers optimal prediction by tailoring the weights to each configuration of known nearby samples. These weights may be precomputed and stored in a small lookup table. We show through several applications that predictive coding using our spectral predictor improves compression for various sources of high-precision data.

Content Adaptive Lagrange Multiplier Selection for Rate-Distortion Optimization in 3-D Wavelet-Based Scalable Video Coding

Directory of Open Access Journals (Sweden)

Ying Chen

2018-03-01

Full Text Available Rate-distortion optimization (RDO plays an essential role in substantially enhancing the coding efficiency. Currently, rate-distortion optimized mode decision is widely used in scalable video coding (SVC. Among all the possible coding modes, it aims to select the one which has the best trade-off between bitrate and compression distortion. Specifically, this tradeoff is tuned through the choice of the Lagrange multiplier. Despite the prevalence of conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to 3-D wavelet-based SVC where the explicit values of the quantization step are not available, with on consideration of the content features of input signal. In this paper, an efficient content adaptive Lagrange multiplier selection algorithm is proposed in the context of RDO for 3-D wavelet-based SVC targeting quality scalability. Our contributions are two-fold. First, we introduce a novel weighting method, which takes account of the mutual information, gradient per pixel, and texture homogeneity to measure the temporal subband characteristics after applying the motion-compensated temporal filtering (MCTF technique. Second, based on the proposed subband weighting factor model, we derive the optimal Lagrange multiplier. Experimental results demonstrate that the proposed algorithm enables more satisfactory video quality with negligible additional computational complexity.

Communicating pictures a course in image and video coding

CERN Document Server

Bull, David R

2014-01-01

Communicating Pictures starts with a unique historical perspective of the role of images in communications and then builds on this to explain the applications and requirements of a modern video coding system. It draws on the author's extensive academic and professional experience of signal processing and video coding to deliver a text that is algorithmically rigorous, yet accessible, relevant to modern standards, and practical. It offers a thorough grounding in visual perception, and demonstrates how modern image and video compression methods can be designed in order to meet the rate-quality performance levels demanded by today's applications, networks and users. With this book you will learn: Practical issues when implementing a codec, such as picture boundary extension and complexity reduction, with particular emphasis on efficient algorithms for transforms, motion estimators and error resilience Conflicts between conventional video compression, based on variable length coding and spatiotemporal prediction,...

Joint compression and encryption using chaotically mutated Huffman trees

Science.gov (United States)

Hermassi, Houcemeddine; Rhouma, Rhouma; Belghith, Safya

2010-10-01

This paper introduces a new scheme for joint compression and encryption using the Huffman codec. A basic tree is first generated for a given message and then based on a keystream generated from a chaotic map and depending from the input message, the basic tree is mutated without changing the statistical model. Hence a symbol can be coded by more than one codeword having the same length. The security of the scheme is tested against the known plaintext attack and the brute force attack. Performance analysis including encryption/decryption speed, additional computational complexity and compression ratio are given.

Efficient burst image compression using H.265/HEVC

Science.gov (United States)

Roodaki-Lavasani, Hoda; Lainema, Jani

2014-02-01

New imaging use cases are emerging as more powerful camera hardware is entering consumer markets. One family of such use cases is based on capturing multiple pictures instead of just one when taking a photograph. That kind of a camera operation allows e.g. selecting the most successful shot from a sequence of images, showing what happened right before or after the shot was taken or combining the shots by computational means to improve either visible characteristics of the picture (such as dynamic range or focus) or the artistic aspects of the photo (e.g. by superimposing pictures on top of each other). Considering that photographic images are typically of high resolution and quality and the fact that these kind of image bursts can consist of at least tens of individual pictures, an efficient compression algorithm is desired. However, traditional video coding approaches fail to provide the random access properties these use cases require to achieve near-instantaneous access to the pictures in the coded sequence. That feature is critical to allow users to browse the pictures in an arbitrary order or imaging algorithms to extract desired pictures from the sequence quickly. This paper proposes coding structures that provide such random access properties while achieving coding efficiency superior to existing image coders. The results indicate that using HEVC video codec with a single reference picture fixed for the whole sequence can achieve nearly as good compression as traditional IPPP coding structures. It is also shown that the selection of the reference frame can further improve the coding efficiency.

Multimedia signal coding and transmission

CERN Document Server

Ohm, Jens-Rainer

2015-01-01

This textbook covers the theoretical background of one- and multidimensional signal processing, statistical analysis and modelling, coding and information theory with regard to the principles and design of image, video and audio compression systems. The theoretical concepts are augmented by practical examples of algorithms for multimedia signal coding technology, and related transmission aspects. On this basis, principles behind multimedia coding standards, including most recent developments like High Efficiency Video Coding, can be well understood. Furthermore, potential advances in future development are pointed out. Numerous figures and examples help to illustrate the concepts covered. The book was developed on the basis of a graduate-level university course, and most chapters are supplemented by exercises. The book is also a self-contained introduction both for researchers and developers of multimedia compression systems in industry.

Lossless Compression of Classification-Map Data

Science.gov (United States)

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.

High-speed and high-ratio referential genome compression.

Science.gov (United States)

Liu, Yuansheng; Peng, Hui; Wong, Limsoon; Li, Jinyan

2017-11-01

The rapidly increasing number of genomes generated by high-throughput sequencing platforms and assembly algorithms is accompanied by problems in data storage, compression and communication. Traditional compression algorithms are unable to meet the demand of high compression ratio due to the intrinsic challenging features of DNA sequences such as small alphabet size, frequent repeats and palindromes. Reference-based lossless compression, by which only the differences between two similar genomes are stored, is a promising approach with high compression ratio. We present a high-performance referential genome compression algorithm named HiRGC. It is based on a 2-bit encoding scheme and an advanced greedy-matching search on a hash table. We compare the performance of HiRGC with four state-of-the-art compression methods on a benchmark dataset of eight human genomes. HiRGC takes compress about 21 gigabytes of each set of the seven target genomes into 96-260 megabytes, achieving compression ratios of 217 to 82 times. This performance is at least 1.9 times better than the best competing algorithm on its best case. Our compression speed is also at least 2.9 times faster. HiRGC is stable and robust to deal with different reference genomes. In contrast, the competing methods' performance varies widely on different reference genomes. More experiments on 100 human genomes from the 1000 Genome Project and on genomes of several other species again demonstrate that HiRGC's performance is consistently excellent. The C ++ and Java source codes of our algorithm are freely available for academic and non-commercial use. They can be downloaded from https://github.com/yuansliu/HiRGC. jinyan.li@uts.edu.au. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Compressing bitmap indexes for faster search operations

International Nuclear Information System (INIS)

Wu, Kesheng; Otoo, Ekow J.; Shoshani, Arie

2002-01-01

In this paper, we study the effects of compression on bitmap indexes. The main operations on the bitmaps during query processing are bitwise logical operations such as AND, OR, NOT, etc. Using the general purpose compression schemes, such as gzip, the logical operations on the compressed bitmaps are much slower than on the uncompressed bitmaps. Specialized compression schemes, like the byte-aligned bitmap code(BBC), are usually faster in performing logical operations than the general purpose schemes, but in many cases they are still orders of magnitude slower than the uncompressed scheme. To make the compressed bitmap indexes operate more efficiently, we designed a CPU-friendly scheme which we refer to as the word-aligned hybrid code (WAH). Tests on both synthetic and real application data show that the new scheme significantly outperforms well-known compression schemes at a modest increase in storage space. Compared to BBC, a scheme well-known for its operational efficiency, WAH performs logical operations about 12 times faster and uses only 60 percent more space. Compared to the uncompressed scheme, in most test cases WAH is faster while still using less space. We further verified with additional tests that the improvement in logical operation speed translates to similar improvement in query processing speed

Compressing bitmap indexes for faster search operations

Energy Technology Data Exchange (ETDEWEB)

Wu, Kesheng; Otoo, Ekow J.; Shoshani, Arie

2002-04-25

In this paper, we study the effects of compression on bitmap indexes. The main operations on the bitmaps during query processing are bitwise logical operations such as AND, OR, NOT, etc. Using the general purpose compression schemes, such as gzip, the logical operations on the compressed bitmaps are much slower than on the uncompressed bitmaps. Specialized compression schemes, like the byte-aligned bitmap code(BBC), are usually faster in performing logical operations than the general purpose schemes, but in many cases they are still orders of magnitude slower than the uncompressed scheme. To make the compressed bitmap indexes operate more efficiently, we designed a CPU-friendly scheme which we refer to as the word-aligned hybrid code (WAH). Tests on both synthetic and real application data show that the new scheme significantly outperforms well-known compression schemes at a modest increase in storage space. Compared to BBC, a scheme well-known for its operational efficiency, WAH performs logical operations about 12 times faster and uses only 60 percent more space. Compared to the uncompressed scheme, in most test cases WAH is faster while still using less space. We further verified with additional tests that the improvement in logical operation speed translates to similar improvement in query processing speed.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

Science.gov (United States)

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant sensor networks.

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

DEFF Research Database (Denmark)

Misaridis, Thanasis; Jensen, Jørgen Arendt

1999-01-01

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

Evaluation of mammogram compression efficiency

International Nuclear Information System (INIS)

Przelaskowski, A.; Surowski, P.; Kukula, A.

2005-01-01

Lossy image coding significantly improves performance over lossless methods, but a reliable control of diagnostic accuracy regarding compressed images is necessary. The acceptable range of compression ratios must be safe with respect to as many objective criteria as possible. This study evaluates the compression efficiency of digital mammograms in both numerically lossless (reversible) and lossy (irreversible) manner. Effective compression methods and concepts were examined to increase archiving and telediagnosis performance. Lossless compression as a primary applicable tool for medical applications was verified on a set 131 mammograms. Moreover, nine radiologists participated in the evaluation of lossy compression of mammograms. Subjective rating of diagnostically important features brought a set of mean rates given for each test image. The lesion detection test resulted in binary decision data analyzed statistically. The radiologists rated and interpreted malignant and benign lesions, representative pathology symptoms, and other structures susceptible to compression distortions contained in 22 original and 62 reconstructed mammograms. Test mammograms were collected in two radiology centers for three years and then selected according to diagnostic content suitable for an evaluation of compression effects. Lossless compression efficiency of the tested coders varied, but CALIC, JPEG-LS, and SPIHT performed the best. The evaluation of lossy compression effects affecting detection ability was based on ROC-like analysis. Assuming a two-sided significance level of p=0.05, the null hypothesis that lower bit rate reconstructions are as useful for diagnosis as the originals was false in sensitivity tests with 0.04 bpp mammograms. However, verification of the same hypothesis with 0.1 bpp reconstructions suggested their acceptance. Moreover, the 1 bpp reconstructions were rated very similarly to the original mammograms in the diagnostic quality evaluation test, but the

Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

Science.gov (United States)

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.

REMOTELY SENSEDC IMAGE COMPRESSION BASED ON WAVELET TRANSFORM

Directory of Open Access Journals (Sweden)

Heung K. Lee

1996-06-01

Full Text Available In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR and classification capability.

Novel 3D Compression Methods for Geometry, Connectivity and Texture

Science.gov (United States)

Siddeq, M. M.; Rodrigues, M. A.

2016-06-01

A large number of applications in medical visualization, games, engineering design, entertainment, heritage, e-commerce and so on require the transmission of 3D models over the Internet or over local networks. 3D data compression is an important requirement for fast data storage, access and transmission within bandwidth limitations. The Wavefront OBJ (object) file format is commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces, normals, texture coordinates and other parameters) describing the mesh surface. In this paper we introduce a new method to compress geometry, connectivity and texture coordinates by a novel Geometry Minimization Algorithm (GM-Algorithm) in connection with arithmetic coding. First, each vertex ( x, y, z) coordinates are encoded to a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, which are compressed by arithmetic coding together with texture coordinates. We demonstrate the method on large data sets achieving compression ratios between 87 and 99 % without reduction in the number of reconstructed vertices and triangle faces. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as VRML, OpenCTM and STL highlighting the performance and effectiveness of the proposed method.

Compressive sensing based ptychography image encryption

Science.gov (United States)

Rawat, Nitin

2015-09-01

A compressive sensing (CS) based ptychography combined with an optical image encryption is proposed. The diffraction pattern is recorded through ptychography technique further compressed by non-uniform sampling via CS framework. The system requires much less encrypted data and provides high security. The diffraction pattern as well as the lesser measurements of the encrypted samples serves as a secret key which make the intruder attacks more difficult. Furthermore, CS shows that the linearly projected few random samples have adequate information for decryption with a dramatic volume reduction. Experimental results validate the feasibility and effectiveness of our proposed technique compared with the existing techniques. The retrieved images do not reveal any information with the original information. In addition, the proposed system can be robust even with partial encryption and under brute-force attacks.

Design of a Biorthogonal Wavelet Transform Based R-Peak Detection and Data Compression Scheme for Implantable Cardiac Pacemaker Systems.

Science.gov (United States)

Kumar, Ashish; Kumar, Manjeet; Komaragiri, Rama

2018-04-19

Bradycardia can be modulated using the cardiac pacemaker, an implantable medical device which sets and balances the patient's cardiac health. The device has been widely used to detect and monitor the patient's heart rate. The data collected hence has the highest authenticity assurance and is convenient for further electric stimulation. In the pacemaker, ECG detector is one of the most important element. The device is available in its new digital form, which is more efficient and accurate in performance with the added advantage of economical power consumption platform. In this work, a joint algorithm based on biorthogonal wavelet transform and run-length encoding (RLE) is proposed for QRS complex detection of the ECG signal and compressing the detected ECG data. Biorthogonal wavelet transform of the input ECG signal is first calculated using a modified demand based filter bank architecture which consists of a series combination of three lowpass filters with a highpass filter. Lowpass and highpass filters are realized using a linear phase structure which reduces the hardware cost of the proposed design approximately by 50%. Then, the location of the R-peak is found by comparing the denoised ECG signal with the threshold value. The proposed R-peak detector achieves the highest sensitivity and positive predictivity of 99.75 and 99.98 respectively with the MIT-BIH arrhythmia database. Also, the proposed R-peak detector achieves a comparatively low data error rate (DER) of 0.002. The use of RLE for the compression of detected ECG data achieves a higher compression ratio (CR) of 17.1. To justify the effectiveness of the proposed algorithm, the results have been compared with the existing methods, like Huffman coding/simple predictor, Huffman coding/adaptive, and slope predictor/fixed length packaging.

Coronary angiogram video compression for remote browsing and archiving applications.

Science.gov (United States)

Ouled Zaid, Azza; Fradj, Bilel Ben

2010-12-01

In this paper, we propose a H.264/AVC based compression technique adapted to coronary angiograms. H.264/AVC coder has proven to use the most advanced and accurate motion compensation process, but, at the cost of high computational complexity. On the other hand, analysis of coronary X-ray images reveals large areas containing no diagnostically important information. Our contribution is to exploit the energy characteristics in slice equal size regions to determine the regions with relevant information content, to be encoded using the H.264 coding paradigm. The others regions, are compressed using fixed block motion compensation and conventional hard-decision quantization. Experiments have shown that at the same bitrate, this procedure reduces the H.264 coder computing time of about 25% while attaining the same visual quality. A subjective assessment, based on the consensus approach leads to a compression ratio of 30:1 which insures both a diagnostic adequacy and a sufficient compression in regards to storage and transmission requirements. Copyright © 2010 Elsevier Ltd. All rights reserved.

Coding Local and Global Binary Visual Features Extracted From Video Sequences.

Science.gov (United States)

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

The Statistical Analysis of Relation between Compressive and Tensile/Flexural Strength of High Performance Concrete

Directory of Open Access Journals (Sweden)

Kępniak M.

2016-12-01

Full Text Available This paper addresses the tensile and flexural strength of HPC (high performance concrete. The aim of the paper is to analyse the efficiency of models proposed in different codes. In particular, three design procedures from: the ACI 318 [1], Eurocode 2 [2] and the Model Code 2010 [3] are considered. The associations between design tensile strength of concrete obtained from these three codes and compressive strength are compared with experimental results of tensile strength and flexural strength by statistical tools. Experimental results of tensile strength were obtained in the splitting test. Based on this comparison, conclusions are drawn according to the fit between the design methods and the test data. The comparison shows that tensile strength and flexural strength of HPC depend on more influential factors and not only compressive strength.

Compression of Short Text on Embedded Systems

DEFF Research Database (Denmark)

Rein, S.; Gühmann, C.; Fitzek, Frank

2006-01-01

The paper details a scheme for lossless compression of a short data series larger than 50 bytes. The method uses arithmetic coding and context modelling with a low-complexity data model. A data model that takes 32 kBytes of RAM already cuts the data size in half. The compression scheme just takes...

A new hyperspectral image compression paradigm based on fusion

Science.gov (United States)

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.

Energy-efficient sensing in wireless sensor networks using compressed sensing.

Science.gov (United States)

Razzaque, Mohammad Abdur; Dobson, Simon

2014-02-12

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.

An efficient fractal image coding algorithm using unified feature and DCT

International Nuclear Information System (INIS)

Zhou Yiming; Zhang Chao; Zhang Zengke

2009-01-01

Fractal image compression is a promising technique to improve the efficiency of image storage and image transmission with high compression ratio, however, the huge time consumption for the fractal image coding is a great obstacle to the practical applications. In order to improve the fractal image coding, efficient fractal image coding algorithms using a special unified feature and a DCT coder are proposed in this paper. Firstly, based on a necessary condition to the best matching search rule during fractal image coding, the fast algorithm using a special unified feature (UFC) is addressed, and it can reduce the search space obviously and exclude most inappropriate matching subblocks before the best matching search. Secondly, on the basis of UFC algorithm, in order to improve the quality of the reconstructed image, a DCT coder is combined to construct a hybrid fractal image algorithm (DUFC). Experimental results show that the proposed algorithms can obtain good quality of the reconstructed images and need much less time than the baseline fractal coding algorithm.

LSP Simulations of the Neutralized Drift Compression Experiment

CERN Document Server

Thoma, Carsten H; Gilson, Erik P; Henestroza, Enrique; Roy, Prabir K; Welch, Dale; Yu, Simon

2005-01-01

The Neutralized Drift Compression Experiment (NDCX) at Lawrence Berkeley National Laboratory involves the longitudinal compression of a singly-stripped K ion beam with a mean energy of 250 keV in a meter long plasma. We present simulation results of compression of the NDCX beam using the PIC code LSP. The NDCX beam encounters an acceleration gap with a time-dependent voltage that decelerates the front and accelerates the tail of a 500 ns pulse which is to be compressed 110 cm downstream. The simulations model both ideal and experimental voltage waveforms. Results show good longitudinal compression without significant emittance growth.

Coding with partially hidden Markov models

DEFF Research Database (Denmark)

Forchhammer, Søren; Rissanen, J.

1995-01-01

Partially hidden Markov models (PHMM) are introduced. They are a variation of the hidden Markov models (HMM) combining the power of explicit conditioning on past observations and the power of using hidden states. (P)HMM may be combined with arithmetic coding for lossless data compression. A general...... 2-part coding scheme for given model order but unknown parameters based on PHMM is presented. A forward-backward reestimation of parameters with a redefined backward variable is given for these models and used for estimating the unknown parameters. Proof of convergence of this reestimation is given....... The PHMM structure and the conditions of the convergence proof allows for application of the PHMM to image coding. Relations between the PHMM and hidden Markov models (HMM) are treated. Results of coding bi-level images with the PHMM coding scheme is given. The results indicate that the PHMM can adapt...

Fast modeling of flux trapping cascaded explosively driven magnetic flux compression generators.

Science.gov (United States)

Wang, Yuwei; Zhang, Jiande; Chen, Dongqun; Cao, Shengguang; Li, Da; Liu, Chebo

2013-01-01

To predict the performance of flux trapping cascaded flux compression generators, a calculation model based on an equivalent circuit is investigated. The system circuit is analyzed according to its operation characteristics in different steps. Flux conservation coefficients are added to the driving terms of circuit differential equations to account for intrinsic flux losses. To calculate the currents in the circuit by solving the circuit equations, a simple zero-dimensional model is used to calculate the time-varying inductance and dc resistance of the generator. Then a fast computer code is programmed based on this calculation model. As an example, a two-staged flux trapping generator is simulated by using this computer code. Good agreements are achieved by comparing the simulation results with the measurements. Furthermore, it is obvious that this fast calculation model can be easily applied to predict performances of other flux trapping cascaded flux compression generators with complex structures such as conical stator or conical armature sections and so on for design purpose.

Wireless Sensor Networks Data Processing Summary Based on Compressive Sensing

Directory of Open Access Journals (Sweden)

Caiyun Huang

2014-07-01

Full Text Available As a newly proposed theory, compressive sensing (CS is commonly used in signal processing area. This paper investigates the applications of compressed sensing (CS in wireless sensor networks (WSNs. First, the development and research status of compressed sensing technology and wireless sensor networks are described, then a detailed investigation of WSNs research based on CS are conducted from aspects of data fusion, signal acquisition, signal routing transmission, and signal reconstruction. At the end of the paper, we conclude our survey and point out the possible future research directions.

Use of the algebraic coding theory in nuclear electronics

International Nuclear Information System (INIS)

Nikityuk, N.M.

1990-01-01

New results of studies of the development and use of the syndrome coding method in nuclear electronics are described. Two aspects of using the syndrome coding method are considered for sequential coding devices and for the creation of fast parallel data compression devices. Specific examples of the creation of time-to-digital converters based on circular counters are described. Several time intervals can be coded very fast and with a high resolution by means of these converters. The effective coding matrix which can be used for light signal coding. The rule of constructing such coding matrices for arbitrary number of channels and multiplicity n is given. The methods for solving ambiguities in silicon detectors and for creating the special-purpose processors for high-energy spectrometers are given. 21 refs.; 9 figs.; 3 tabs

A new approach of objective quality evaluation on JPEG2000 lossy-compressed lung cancer CT images

Science.gov (United States)

Cai, Weihua; Tan, Yongqiang; Zhang, Jianguo

2007-03-01

Image compression has been used to increase the communication efficiency and storage capacity. JPEG 2000 compression, based on the wavelet transformation, has its advantages comparing to other compression methods, such as ROI coding, error resilience, adaptive binary arithmetic coding and embedded bit-stream. However it is still difficult to find an objective method to evaluate the image quality of lossy-compressed medical images so far. In this paper, we present an approach to evaluate the image quality by using a computer aided diagnosis (CAD) system. We selected 77 cases of CT images, bearing benign and malignant lung nodules with confirmed pathology, from our clinical Picture Archiving and Communication System (PACS). We have developed a prototype of CAD system to classify these images into benign ones and malignant ones, the performance of which was evaluated by the receiver operator characteristics (ROC) curves. We first used JPEG 2000 to compress these cases of images with different compression ratio from lossless to lossy, and used the CAD system to classify the cases with different compressed ratio, then compared the ROC curves from the CAD classification results. Support vector machine (SVM) and neural networks (NN) were used to classify the malignancy of input nodules. In each approach, we found that the area under ROC (AUC) decreases with the increment of compression ratio with small fluctuations.

Compression of TPC data in the ALICE experiment

International Nuclear Information System (INIS)

Nicolaucig, A.; Mattavelli, M.; Carrato, S.

2002-01-01

In this paper two algorithms for the compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN are described. The first algorithm is based on a lossless source code modeling technique, i.e. the original TPC signal information can be reconstructed without errors at the decompression stage. The source model exploits the temporal correlation that is present in the TPC data to reduce the entropy of the source. The second algorithm is based on a source model which is lossy if samples of the TPC signal are considered one by one. Conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse. Obviously entropy coding is applied to the set of events defined by the two source models to reduce the bit rate to the corresponding source entropy. Using TPC simulated data according to the expected ALICE TPC performance, the lossless and the lossy compression algorithms achieve a data reduction, respectively, to 49.2% and in the range of 34.2% down to 23.7% of the original data rate. The number of operations per input symbol required to implement the compression stage for both algorithms is relatively low, so that a real-time implementation embedded in the TPC data acquisition chain using low-cost integrated electronics is a realistic option to effectively reduce the data storing cost of ALICE experiment

Compression of fingerprint data using the wavelet vector quantization image compression algorithm. 1992 progress report

Energy Technology Data Exchange (ETDEWEB)

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

1992-04-11

This report describes the development of a Wavelet Vector Quantization (WVQ) image compression algorithm for fingerprint raster files. The pertinent work was performed at Los Alamos National Laboratory for the Federal Bureau of Investigation. This document describes a previously-sent package of C-language source code, referred to as LAFPC, that performs the WVQ fingerprint compression and decompression tasks. The particulars of the WVQ algorithm and the associated design procedure are detailed elsewhere; the purpose of this document is to report the results of the design algorithm for the fingerprint application and to delineate the implementation issues that are incorporated in LAFPC. Special attention is paid to the computation of the wavelet transform, the fast search algorithm used for the VQ encoding, and the entropy coding procedure used in the transmission of the source symbols.

System Based Code: Principal Concept

International Nuclear Information System (INIS)

Yasuhide Asada; Masanori Tashimo; Masahiro Ueta

2002-01-01

This paper introduces a concept of the 'System Based Code' which has initially been proposed by the authors intending to give nuclear industry a leap of progress in the system reliability, performance improvement, and cost reduction. The concept of the System Based Code intends to give a theoretical procedure to optimize the reliability of the system by administrating every related engineering requirement throughout the life of the system from design to decommissioning. (authors)

Memory hierarchy using row-based compression

Science.gov (United States)

Loh, Gabriel H.; O'Connor, James M.

2016-10-25

A system includes a first memory and a device coupleable to the first memory. The device includes a second memory to cache data from the first memory. The second memory includes a plurality of rows, each row including a corresponding set of compressed data blocks of non-uniform sizes and a corresponding set of tag blocks. Each tag block represents a corresponding compressed data block of the row. The device further includes decompression logic to decompress data blocks accessed from the second memory. The device further includes compression logic to compress data blocks to be stored in the second memory.

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

Science.gov (United States)

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

Highly compressible and all-solid-state supercapacitors based on nanostructured composite sponge.

Science.gov (United States)

Niu, Zhiqiang; Zhou, Weiya; Chen, Xiaodong; Chen, Jun; Xie, Sishen

2015-10-21

Based on polyaniline-single-walled carbon nanotubes -sponge electrodes, highly compressible all-solid-state supercapacitors are prepared with an integrated configuration using a poly(vinyl alcohol) (PVA)/H2 SO4 gel as the electrolyte. The unique configuration enables the resultant supercapacitors to be compressed as an integrated unit arbitrarily during 60% compressible strain. Furthermore, the performance of the resultant supercapacitors is nearly unchanged even under 60% compressible strain. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A review of lossless audio compression standards and algorithms

Science.gov (United States)

Muin, Fathiah Abdul; Gunawan, Teddy Surya; Kartiwi, Mira; Elsheikh, Elsheikh M. A.

2017-09-01

Over the years, lossless audio compression has gained popularity as researchers and businesses has become more aware of the need for better quality and higher storage demand. This paper will analyse various lossless audio coding algorithm and standards that are used and available in the market focusing on Linear Predictive Coding (LPC) specifically due to its popularity and robustness in audio compression, nevertheless other prediction methods are compared to verify this. Advanced representation of LPC such as LSP decomposition techniques are also discussed within this paper.

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

Science.gov (United States)

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.

Non-binary unitary error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E.

1996-06-01

Error operator bases for systems of any dimension are defined and natural generalizations of the bit-flip/ sign-change error basis for qubits are given. These bases allow generalizing the construction of quantum codes based on eigenspaces of Abelian groups. As a consequence, quantum codes can be constructed form linear codes over {ital Z}{sub {ital n}} for any {ital n}. The generalization of the punctured code construction leads to many codes which permit transversal (i.e. fault tolerant) implementations of certain operations compatible with the error basis.

Contributions in compression of 3D medical images and 2D images; Contributions en compression d'images medicales 3D et d'images naturelles 2D

Energy Technology Data Exchange (ETDEWEB)

Gaudeau, Y

2006-12-15

The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

Natrium: Use of FPGA embedded processors for real-time data compression

Energy Technology Data Exchange (ETDEWEB)

Ammendola, R; Salamon, A; Salina, G [INFN Sezione di Roma Tor Vergata, Rome (Italy); Biagioni, A; Frezza, O; Cicero, F Lo; Lonardo, A; Rossetti, D; Simula, F; Tosoratto, L; Vicini, P [INFN Sezione di Roma, Rome (Italy)

2011-12-15

We present test results and characterization of a data compression system for the readout of the NA62 liquid krypton calorimeter trigger processor. The Level-0 electromagnetic calorimeter trigger processor of the NA62 experiment at CERN receives digitized data from the calorimeter main readout board. These data are stored on an on-board DDR2 RAM memory and read out upon reception of a Level-0 accept signal. The maximum raw data throughput from the trigger front-end cards is 2.6 Gbps. To readout these data over two Gbit Ethernet interfaces we investigated different implementations of a data compression system based on the Rice-Golomb coding: one is implemented in the FPGA as a custom block and one is implemented on the FPGA embedded processor running a C code. The two implementations are tested on a set of sample events and compared with respect to achievable readout bandwidth.

Natrium: Use of FPGA embedded processors for real-time data compression

International Nuclear Information System (INIS)

Ammendola, R; Salamon, A; Salina, G; Biagioni, A; Frezza, O; Cicero, F Lo; Lonardo, A; Rossetti, D; Simula, F; Tosoratto, L; Vicini, P

2011-01-01

We present test results and characterization of a data compression system for the readout of the NA62 liquid krypton calorimeter trigger processor. The Level-0 electromagnetic calorimeter trigger processor of the NA62 experiment at CERN receives digitized data from the calorimeter main readout board. These data are stored on an on-board DDR2 RAM memory and read out upon reception of a Level-0 accept signal. The maximum raw data throughput from the trigger front-end cards is 2.6 Gbps. To readout these data over two Gbit Ethernet interfaces we investigated different implementations of a data compression system based on the Rice-Golomb coding: one is implemented in the FPGA as a custom block and one is implemented on the FPGA embedded processor running a C code. The two implementations are tested on a set of sample events and compared with respect to achievable readout bandwidth.

Sub-band/transform compression of video sequences

Science.gov (United States)

Sauer, Ken; Bauer, Peter

1992-01-01

The progress on compression of video sequences is discussed. The overall goal of the research was the development of data compression algorithms for high-definition television (HDTV) sequences, but most of our research is general enough to be applicable to much more general problems. We have concentrated on coding algorithms based on both sub-band and transform approaches. Two very fundamental issues arise in designing a sub-band coder. First, the form of the signal decomposition must be chosen to yield band-pass images with characteristics favorable to efficient coding. A second basic consideration, whether coding is to be done in two or three dimensions, is the form of the coders to be applied to each sub-band. Computational simplicity is of essence. We review the first portion of the year, during which we improved and extended some of the previous grant period's results. The pyramid nonrectangular sub-band coder limited to intra-frame application is discussed. Perhaps the most critical component of the sub-band structure is the design of bandsplitting filters. We apply very simple recursive filters, which operate at alternating levels on rectangularly sampled, and quincunx sampled images. We will also cover the techniques we have studied for the coding of the resulting bandpass signals. We discuss adaptive three-dimensional coding which takes advantage of the detection algorithm developed last year. To this point, all the work on this project has been done without the benefit of motion compensation (MC). Motion compensation is included in many proposed codecs, but adds significant computational burden and hardware expense. We have sought to find a lower-cost alternative featuring a simple adaptation to motion in the form of the codec. In sequences of high spatial detail and zooming or panning, it appears that MC will likely be necessary for the proposed quality and bit rates.

A GPU-accelerated implicit meshless method for compressible flows

Science.gov (United States)

Zhang, Jia-Le; Ma, Zhi-Hua; Chen, Hong-Quan; Cao, Cheng

2018-05-01

This paper develops a recently proposed GPU based two-dimensional explicit meshless method (Ma et al., 2014) by devising and implementing an efficient parallel LU-SGS implicit algorithm to further improve the computational efficiency. The capability of the original 2D meshless code is extended to deal with 3D complex compressible flow problems. To resolve the inherent data dependency of the standard LU-SGS method, which causes thread-racing conditions destabilizing numerical computation, a generic rainbow coloring method is presented and applied to organize the computational points into different groups by painting neighboring points with different colors. The original LU-SGS method is modified and parallelized accordingly to perform calculations in a color-by-color manner. The CUDA Fortran programming model is employed to develop the key kernel functions to apply boundary conditions, calculate time steps, evaluate residuals as well as advance and update the solution in the temporal space. A series of two- and three-dimensional test cases including compressible flows over single- and multi-element airfoils and a M6 wing are carried out to verify the developed code. The obtained solutions agree well with experimental data and other computational results reported in the literature. Detailed analysis on the performance of the developed code reveals that the developed CPU based implicit meshless method is at least four to eight times faster than its explicit counterpart. The computational efficiency of the implicit method could be further improved by ten to fifteen times on the GPU.

Future trends in image coding

Science.gov (United States)

Habibi, Ali

1993-01-01

The objective of this article is to present a discussion on the future of image data compression in the next two decades. It is virtually impossible to predict with any degree of certainty the breakthroughs in theory and developments, the milestones in advancement of technology and the success of the upcoming commercial products in the market place which will be the main factors in establishing the future stage to image coding. What we propose to do, instead, is look back at the progress in image coding during the last two decades and assess the state of the art in image coding today. Then, by observing the trends in developments of theory, software, and hardware coupled with the future needs for use and dissemination of imagery data and the constraints on the bandwidth and capacity of various networks, predict the future state of image coding. What seems to be certain today is the growing need for bandwidth compression. The television is using a technology which is half a century old and is ready to be replaced by high definition television with an extremely high digital bandwidth. Smart telephones coupled with personal computers and TV monitors accommodating both printed and video data will be common in homes and businesses within the next decade. Efficient and compact digital processing modules using developing technologies will make bandwidth compressed imagery the cheap and preferred alternative in satellite and on-board applications. In view of the above needs, we expect increased activities in development of theory, software, special purpose chips and hardware for image bandwidth compression in the next two decades. The following sections summarize the future trends in these areas.

Multiband CCD Image Compression for Space Camera with Large Field of View

Directory of Open Access Journals (Sweden)

Jin Li

2014-01-01

Full Text Available Space multiband CCD camera compression encoder requires low-complexity, high-robustness, and high-performance because of its captured images information being very precious and also because it is usually working on the satellite where the resources, such as power, memory, and processing capacity, are limited. However, the traditional compression approaches, such as JPEG2000, 3D transforms, and PCA, have the high-complexity. The Consultative Committee for Space Data Systems-Image Data Compression (CCSDS-IDC algorithm decreases the average PSNR by 2 dB compared with JPEG2000. In this paper, we proposed a low-complexity compression algorithm based on deep coupling algorithm among posttransform in wavelet domain, compressive sensing, and distributed source coding. In our algorithm, we integrate three low-complexity and high-performance approaches in a deeply coupled manner to remove the spatial redundant, spectral redundant, and bit information redundancy. Experimental results on multiband CCD images show that the proposed algorithm significantly outperforms the traditional approaches.

On-board image compression for the RAE lunar mission

Science.gov (United States)

Miller, W. H.; Lynch, T. J.

1976-01-01

The requirements, design, implementation, and flight performance of an on-board image compression system for the lunar orbiting Radio Astronomy Explorer-2 (RAE-2) spacecraft are described. The image to be compressed is a panoramic camera view of the long radio astronomy antenna booms used for gravity-gradient stabilization of the spacecraft. A compression ratio of 32 to 1 is obtained by a combination of scan line skipping and adaptive run-length coding. The compressed imagery data are convolutionally encoded for error protection. This image compression system occupies about 1000 cu cm and consumes 0.4 W.

Group representations, error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E

1996-01-01

This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

EP-based wavelet coefficient quantization for linear distortion ECG data compression.

Science.gov (United States)

Hung, King-Chu; Wu, Tsung-Ching; Lee, Hsieh-Wei; Liu, Tung-Kuan

2014-07-01

Reconstruction quality maintenance is of the essence for ECG data compression due to the desire for diagnosis use. Quantization schemes with non-linear distortion characteristics usually result in time-consuming quality control that blocks real-time application. In this paper, a new wavelet coefficient quantization scheme based on an evolution program (EP) is proposed for wavelet-based ECG data compression. The EP search can create a stationary relationship among the quantization scales of multi-resolution levels. The stationary property implies that multi-level quantization scales can be controlled with a single variable. This hypothesis can lead to a simple design of linear distortion control with 3-D curve fitting technology. In addition, a competitive strategy is applied for alleviating data dependency effect. By using the ECG signals saved in MIT and PTB databases, many experiments were undertaken for the evaluation of compression performance, quality control efficiency, data dependency influence. The experimental results show that the new EP-based quantization scheme can obtain high compression performance and keep linear distortion behavior efficiency. This characteristic guarantees fast quality control even for the prediction model mismatching practical distortion curve. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Lossy compression of TPC data and trajectory tracking efficiency for the ALICE experiment

International Nuclear Information System (INIS)

Nicolaucig, A.; Ivanov, M.; Mattavelli, M.

2003-01-01

In this paper a quasi-lossless algorithm for the on-line compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN is described. The algorithm is based on a lossy source code modeling technique, i.e. it is based on a source model which is lossy if samples of the TPC signal are considered one by one; conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse, representing the pulse charge and the time localization of the pulse. So as to evaluate the consequences of the error introduced by the lossy compression process, the results of the trajectory tracking algorithms that process data off-line after the experiment are analyzed, in particular, versus their sensibility to the noise introduced by the compression. Two different versions of these off-line algorithms are described, performing cluster finding and particle tracking. The results on how these algorithms are affected by the lossy compression are reported. Entropy coding can be applied to the set of events defined by the source model to reduce the bit rate to the corresponding source entropy. Using TPC simulated data according to the expected ALICE TPC performance, the compression algorithm achieves a data reduction in the range of 34.2% down to 23.7% of the original data rate depending on the desired precision on the pulse center of mass. The number of operations per input symbol required to implement the algorithm is relatively low, so that a real-time implementation of the compression process embedded in the TPC data acquisition chain using low-cost integrated electronics is a realistic option to effectively reduce the data storing cost of ALICE experiment

Adiabatic compression of elongated field-reversed configurations

International Nuclear Information System (INIS)

Spencer, R.L.; Tuszewski, M.; Linford, R.K.

1983-01-01

The adiabatic compression of an elongated field-reversed configuration (FRC) is computed by using a one-dimensional approximation. The one-dimensional results are checked against a two-dimensional equilibrium code. For ratios of FRC separatrix length to separatrix radius greater than about ten, the one-dimensional results are accurate within 10%. To this accuracy, the adiabatic compression of FRC's can be described by simple analytic formulas

State of art in FE-based fuel performance codes

International Nuclear Information System (INIS)

Kim, Hyo Chan; Yang, Yong Sik; Kim, Dae Ho; Bang, Je Geon; Kim, Sun Ki; Koo, Yang Hyun

2013-01-01

Fuel performance codes approximate this complex behavior using an axisymmetric, axially-stacked, one-dimensional radial representation to save computation cost. However, the need for improved modeling of PCMI and, particularly, the importance of multidimensional capability for accurate fuel performance simulation has been identified as safety margin decreases. Finite element (FE) method that is reliable and proven solution in mechanical field has been introduced into fuel performance codes for multidimensional analysis. The present state of the art in numerical simulation of FE-based fuel performance predominantly involves 2-D axisymmetric model and 3-D volumetric model. The FRAPCON and FRAPTRAN own 1.5-D and 2-D FE model to simulate PCMI and cladding ballooning. In 2-D simulation, the FALCON code, developed by EPRI, is a 2-D (R-Z and R-θ) fully thermal-mechanically coupled steady-state and transient FE-based fuel behavior code. The French codes TOUTATIS and ALCYONE which are 3-D, and typically used to investigate localized behavior. In 2008, the Idaho National Laboratory (INL) has been developing multidimensional (2-D and 3-D) nuclear fuel performance code called BISON. In this paper, the current state of FE-based fuel performance code and their models are presented. Based on investigation into the codes, requirements and direction of development for new FE-based fuel performance code can be discussed. Based on comparison of models in FE-based fuel performance code, status of art in the codes can be discussed. A new FE-based fuel performance code should include typical pellet and cladding models which all codes own. In particular, specified pellet and cladding model such as gaseous swelling and high burnup structure (HBS) model should be developed to improve accuracy of code as well as consider AC condition. To reduce computation cost, the approximated gap and the optimized contact model should be also developed

Lossless, Near-Lossless, and Refinement Coding of Bi-level Images

DEFF Research Database (Denmark)

Martins, Bo; Forchhammer, Søren Otto

1997-01-01

We present general and unified algorithms for lossy/lossless codingof bi-level images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template.For better compression, the more general....... Introducing only a small amount of loss in halftoned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG......-2, an emerging international standard for lossless/lossy compression of bi-level images....

An efficient compression scheme for bitmap indices

Energy Technology Data Exchange (ETDEWEB)

Wu, Kesheng; Otoo, Ekow J.; Shoshani, Arie

2004-04-13

When using an out-of-core indexing method to answer a query, it is generally assumed that the I/O cost dominates the overall query response time. Because of this, most research on indexing methods concentrate on reducing the sizes of indices. For bitmap indices, compression has been used for this purpose. However, in most cases, operations on these compressed bitmaps, mostly bitwise logical operations such as AND, OR, and NOT, spend more time in CPU than in I/O. To speedup these operations, a number of specialized bitmap compression schemes have been developed; the best known of which is the byte-aligned bitmap code (BBC). They are usually faster in performing logical operations than the general purpose compression schemes, but, the time spent in CPU still dominates the total query response time. To reduce the query response time, we designed a CPU-friendly scheme named the word-aligned hybrid (WAH) code. In this paper, we prove that the sizes of WAH compressed bitmap indices are about two words per row for large range of attributes. This size is smaller than typical sizes of commonly used indices, such as a B-tree. Therefore, WAH compressed indices are not only appropriate for low cardinality attributes but also for high cardinality attributes.In the worst case, the time to operate on compressed bitmaps is proportional to the total size of the bitmaps involved. The total size of the bitmaps required to answer a query on one attribute is proportional to the number of hits. These indicate that WAH compressed bitmap indices are optimal. To verify their effectiveness, we generated bitmap indices for four different datasets and measured the response time of many range queries. Tests confirm that sizes of compressed bitmap indices are indeed smaller than B-tree indices, and query processing with WAH compressed indices is much faster than with BBC compressed indices, projection indices and B-tree indices. In addition, we also verified that the average query response time

Block-Based Compressed Sensing for Neutron Radiation Image Using WDFB

Directory of Open Access Journals (Sweden)

Wei Jin

2015-01-01

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

Data compression systems for home-use digital video recording

NARCIS (Netherlands)

With, de P.H.N.; Breeuwer, M.; van Grinsven, P.A.M.

1992-01-01

The authors focus on image data compression techniques for digital recording. Image coding for storage equipment covers a large variety of systems because the applications differ considerably in nature. Video coding systems suitable for digital TV and HDTV recording and digital electronic still

Contributions in compression of 3D medical images and 2D images; Contributions en compression d'images medicales 3D et d'images naturelles 2D

Energy Technology Data Exchange (ETDEWEB)

Gaudeau, Y

2006-12-15

The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding

Directory of Open Access Journals (Sweden)

Dai Qionghai

2010-01-01

Full Text Available We propose a Stereoscopic Visual Attention- (SVA- based regional bit allocation optimization for Multiview Video Coding (MVC by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over % bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by  dB at the cost of insensitive image quality degradation of the background image.

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

Science.gov (United States)

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.

ROI-based DICOM image compression for telemedicine

Indian Academy of Sciences (India)

ground and reconstruct the image portions losslessly. The compressed image can ... If the image is compressed by 8:1 compression without any perceptual distortion, the ... Figure 2. Cross-sectional view of medical image (statistical representation). ... The Integer Wavelet Transform (IWT) is used to have lossless processing.

Adiabatic compression of elongated field-reversed configurations

Energy Technology Data Exchange (ETDEWEB)

Spencer, R.L.; Tuszewski, M.; Linford, R.K.

1983-06-01

The adiabatic compression of an elongated field-reversed configuration (FRC) is computed by using a one-dimensional approximation. The one-dimensional results are checked against a two-dimensional equilibrium code. For ratios of FRC separatrix length to separatrix radius greater than about ten, the one-dimensional results are accurate within 10%. To this accuracy, the adiabatic compression of FRC's can be described by simple analytic formulas.

SPECTRUM analysis of multispectral imagery in conjunction with wavelet/KLT data compression

Energy Technology Data Exchange (ETDEWEB)

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

1993-12-01

The data analysis program, SPECTRUM, is used for fusion, visualization, and classification of multi-spectral imagery. The raw data used in this study is Landsat Thematic Mapper (TM) 7-channel imagery, with 8 bits of dynamic range per channel. To facilitate data transmission and storage, a compression algorithm is proposed based on spatial wavelet transform coding and KLT decomposition of interchannel spectral vectors, followed by adaptive optimal multiband scalar quantization. The performance of SPECTRUM clustering and visualization is evaluated on compressed multispectral data. 8-bit visualizations of 56-bit data show little visible distortion at 50:1 compression and graceful degradation at higher compression ratios. Two TM images were processed in this experiment: a 1024 x 1024-pixel scene of the region surrounding the Chernobyl power plant, taken a few months before the reactor malfunction, and a 2048 x 2048 image of Moscow and surrounding countryside.

Modeling of video traffic in packet networks, low rate video compression, and the development of a lossy+lossless image compression algorithm

Science.gov (United States)

Sayood, K.; Chen, Y. C.; Wang, X.

1992-01-01

During this reporting period we have worked on three somewhat different problems. These are modeling of video traffic in packet networks, low rate video compression, and the development of a lossy + lossless image compression algorithm, which might have some application in browsing algorithms. The lossy + lossless scheme is an extension of work previously done under this grant. It provides a simple technique for incorporating browsing capability. The low rate coding scheme is also a simple variation on the standard discrete cosine transform (DCT) coding approach. In spite of its simplicity, the approach provides surprisingly high quality reconstructions. The modeling approach is borrowed from the speech recognition literature, and seems to be promising in that it provides a simple way of obtaining an idea about the second order behavior of a particular coding scheme. Details about these are presented.

An efficient chaotic source coding scheme with variable-length blocks

International Nuclear Information System (INIS)

Lin Qiu-Zhen; Wong Kwok-Wo; Chen Jian-Yong

2011-01-01

An efficient chaotic source coding scheme operating on variable-length blocks is proposed. With the source message represented by a trajectory in the state space of a chaotic system, data compression is achieved when the dynamical system is adapted to the probability distribution of the source symbols. For infinite-precision computation, the theoretical compression performance of this chaotic coding approach attains that of optimal entropy coding. In finite-precision implementation, it can be realized by encoding variable-length blocks using a piecewise linear chaotic map within the precision of register length. In the decoding process, the bit shift in the register can track the synchronization of the initial value and the corresponding block. Therefore, all the variable-length blocks are decoded correctly. Simulation results show that the proposed scheme performs well with high efficiency and minor compression loss when compared with traditional entropy coding. (general)

Multiple Description Coding Based on Optimized Redundancy Removal for 3D Depth Map

Directory of Open Access Journals (Sweden)

Sen Han

2016-06-01

Full Text Available Multiple description (MD coding is a promising alternative for the robust transmission of information over error-prone channels. In 3D image technology, the depth map represents the distance between the camera and objects in the scene. Using the depth map combined with the existing multiview image, it can be efficient to synthesize images of any virtual viewpoint position, which can display more realistic 3D scenes. Differently from the conventional 2D texture image, the depth map contains a lot of spatial redundancy information, which is not necessary for view synthesis, but may result in the waste of compressed bits, especially when using MD coding for robust transmission. In this paper, we focus on the redundancy removal of MD coding based on the DCT (discrete cosine transform domain. In view of the characteristics of DCT coefficients, at the encoder, a Lagrange optimization approach is designed to determine the amounts of high frequency coefficients in the DCT domain to be removed. It is noted considering the low computing complexity that the entropy is adopted to estimate the bit rate in the optimization. Furthermore, at the decoder, adaptive zero-padding is applied to reconstruct the depth map when some information is lost. The experimental results have shown that compared to the corresponding scheme, the proposed method demonstrates better rate central and side distortion performance.

FLUST-2D - A computer code for the calculation of the two-dimensional flow of a compressible medium in coupled retangular areas

International Nuclear Information System (INIS)

Enderle, G.

1979-01-01

The computer-code FLUST-2D is able to calculate the two-dimensional flow of a compressible fluid in arbitrary coupled rectangular areas. In a finite-difference scheme the program computes pressure, density, internal energy and velocity. Starting with a basic set of equations, the difference equations in a rectangular grid are developed. The computational cycle for coupled fluid areas is described. Results of test calculations are compared to analytical solutions and the influence of time step and mesh size are investigated. The program was used to precalculate the blowdown experiments of the HDR experimental program. Downcomer, plena, internal vessel region, blowdown pipe and a containment area have been modelled two-dimensionally. The major results of the precalculations are presented. This report also contains a description of the code structure and user information. (orig.) [de

Airship Sparse Array Antenna Radar Real Aperture Imaging Based on Compressed Sensing and Sparsity in Transform Domain

Directory of Open Access Journals (Sweden)

Li Liechen

2016-02-01

Full Text Available A conformal sparse array based on combined Barker code is designed for airship platform. The performance of the designed array such as signal-to-noise ratio is analyzed. Using the hovering characteristics of the airship, interferometry operation can be applied on the real aperture imaging results of two pulses, which can eliminate the random backscatter phase and make the image sparse in the transform domain. Building the relationship between echo and transform coefficients, the Compressed Sensing (CS theory can be introduced to solve the formula and achieving imaging. The image quality of the proposed method can reach the image formed by the full array imaging. The simulation results show the effectiveness of the proposed method.

Contributions in compression of 3D medical images and 2D images

International Nuclear Information System (INIS)

Gaudeau, Y.

2006-12-01

The huge amounts of volumetric data generated by current medical imaging techniques in the context of an increasing demand for long term archiving solutions, as well as the rapid development of distant radiology make the use of compression inevitable. Indeed, if the medical community has sided until now with compression without losses, most of applications suffer from compression ratios which are too low with this kind of compression. In this context, compression with acceptable losses could be the most appropriate answer. So, we propose a new loss coding scheme based on 3D (3 dimensional) Wavelet Transform and Dead Zone Lattice Vector Quantization 3D (DZLVQ) for medical images. Our algorithm has been evaluated on several computerized tomography (CT) and magnetic resonance image volumes. The main contribution of this work is the design of a multidimensional dead zone which enables to take into account correlations between neighbouring elementary volumes. At high compression ratios, we show that it can out-perform visually and numerically the best existing methods. These promising results are confirmed on head CT by two medical patricians. The second contribution of this document assesses the effect with-loss image compression on CAD (Computer-Aided Decision) detection performance of solid lung nodules. This work on 120 significant lungs images shows that detection did not suffer until 48:1 compression and still was robust at 96:1. The last contribution consists in the complexity reduction of our compression scheme. The first allocation dedicated to 2D DZLVQ uses an exponential of the rate-distortion (R-D) functions. The second allocation for 2D and 3D medical images is based on block statistical model to estimate the R-D curves. These R-D models are based on the joint distribution of wavelet vectors using a multidimensional mixture of generalized Gaussian (MMGG) densities. (author)

Subsampling-based compression and flow visualization

Energy Technology Data Exchange (ETDEWEB)

Agranovsky, Alexy; Camp, David; Joy, I; Childs, Hank

2016-01-19

As computational capabilities increasingly outpace disk speeds on leading supercomputers, scientists will, in turn, be increasingly unable to save their simulation data at its native resolution. One solution to this problem is to compress these data sets as they are generated and visualize the compressed results afterwards. We explore this approach, specifically subsampling velocity data and the resulting errors for particle advection-based flow visualization. We compare three techniques: random selection of subsamples, selection at regular locations corresponding to multi-resolution reduction, and introduce a novel technique for informed selection of subsamples. Furthermore, we explore an adaptive system which exchanges the subsampling budget over parallel tasks, to ensure that subsampling occurs at the highest rate in the areas that need it most. We perform supercomputing runs to measure the effectiveness of the selection and adaptation techniques. Overall, we find that adaptation is very effective, and, among selection techniques, our informed selection provides the most accurate results, followed by the multi-resolution selection, and with the worst accuracy coming from random subsamples.

Motion-adaptive intraframe transform coding of video signals

NARCIS (Netherlands)

With, de P.H.N.

1989-01-01

Spatial transform coding has been widely applied for image compression because of its high coding efficiency. However, in many intraframe systems, in which every TV frame is independently processed, coding of moving objects in the case of interlaced input signals is not addressed. In this paper, we

Development of authentication code for multi-access optical code division multiplexing based quantum key distribution

Science.gov (United States)

Taiwo, Ambali; Alnassar, Ghusoon; Bakar, M. H. Abu; Khir, M. F. Abdul; Mahdi, Mohd Adzir; Mokhtar, M.

2018-05-01

One-weight authentication code for multi-user quantum key distribution (QKD) is proposed. The code is developed for Optical Code Division Multiplexing (OCDMA) based QKD network. A unique address assigned to individual user, coupled with degrading probability of predicting the source of the qubit transmitted in the channel offer excellent secure mechanism against any form of channel attack on OCDMA based QKD network. Flexibility in design as well as ease of modifying the number of users are equally exceptional quality presented by the code in contrast to Optical Orthogonal Code (OOC) earlier implemented for the same purpose. The code was successfully applied to eight simultaneous users at effective key rate of 32 bps over 27 km transmission distance.

An Image Compression Scheme in Wireless Multimedia Sensor Networks Based on NMF

Directory of Open Access Journals (Sweden)

Shikang Kong

2017-02-01

Full Text Available With the goal of addressing the issue of image compression in wireless multimedia sensor networks with high recovered quality and low energy consumption, an image compression and transmission scheme based on non-negative matrix factorization (NMF is proposed in this paper. First, the NMF algorithm theory is studied. Then, a collaborative mechanism of image capture, block, compression and transmission is completed. Camera nodes capture images and send them to ordinary nodes which use an NMF algorithm for image compression. Compressed images are transmitted to the station by the cluster head node and received from ordinary nodes. The station takes on the image restoration. Simulation results show that, compared with the JPEG2000 and singular value decomposition (SVD compression schemes, the proposed scheme has a higher quality of recovered images and lower total node energy consumption. It is beneficial to reduce the burden of energy consumption and prolong the life of the whole network system, which has great significance for practical applications of WMSNs.

Analysis of tractable distortion metrics for EEG compression applications

International Nuclear Information System (INIS)

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando; Cárdenas-Barrera, Julián

2012-01-01

Coding distortion in lossy electroencephalographic (EEG) signal compression methods is evaluated through tractable objective criteria. The percentage root-mean-square difference, which is a global and relative indicator of the quality held by reconstructed waveforms, is the most widely used criterion. However, this parameter does not ensure compliance with clinical standard guidelines that specify limits to allowable noise in EEG recordings. As a result, expert clinicians may have difficulties interpreting the resulting distortion of the EEG for a given value of this parameter. Conversely, the root-mean-square error is an alternative criterion that quantifies distortion in understandable units. In this paper, we demonstrate that the root-mean-square error is better suited to control and to assess the distortion introduced by compression methods. The experiments conducted in this paper show that the use of the root-mean-square error as target parameter in EEG compression allows both clinicians and scientists to infer whether coding error is clinically acceptable or not at no cost for the compression ratio. (paper)

L’Application des Codes de Costas et des Codes a Congruences Quadratiques a la Compression d’Impulsion Numerique (The Application of Cost, Codes and Quadratic Congruence Codes to the Compression of Numeric Impulsion)

Science.gov (United States)

1991-12-01

de produire des diagrammes d’ambigult& en forme de punaise avec de faibles lobes...particularit& de produire des diagrammes d’ambiguiLt6 en forme de punaise tout en ayant de faibles lobes secondaires. Ce rapport traite des diff6rentes m6thodes...les codes de Costas, les r~sultats obtenus mantrent que les codes de Golomb of frent de mains bonnes possibi- lit ~s que les codes de Welch pour

Real-time lossless data compression techniques for long-pulse operation

International Nuclear Information System (INIS)

Jesus Vega, J.; Sanchez, E.; Portas, A.; Pereira, A.; Ruiz, M.

2006-01-01

Data logging and data distribution will be two main tasks connected with data handling in ITER. Data logging refers to the recovery and ultimate storage of all data, independent on the data source. Control data and physics data distribution is related, on the one hand, to the on-line data broadcasting for immediate data availability for both data analysis and data visualization. On the other hand, delayed analyses require off-line data access. Due to the large data volume expected, data compression will be mandatory in order to save storage and bandwidth. On-line data distribution in a long pulse environment requires the use of a deterministic approach to be able to ensure a proper response time for data availability. However, an essential feature for all the above purposes is to apply compression techniques that ensure the recovery of the initial signals without spectral distortion when compacted data are expanded (lossless techniques). Delta compression methods are independent on the analogue characteristics of waveforms and there exist a variety of implementations that have been applied to the databases of several fusion devices such as Alcator, JET and TJ-II among others. Delta compression techniques are carried out in a two step algorithm. The first step consists of a delta calculation, i.e. the computation of the differences between the digital codes of adjacent signal samples. The resultant deltas are then encoded according to constant- or variable-length bit allocation. Several encoding forms can be considered for the second step and they have to satisfy a prefix code property. However, and in order to meet the requirement of on-line data distribution, the encoding forms have to be defined prior to data capture. This article reviews different lossless data compression techniques based on delta compression. In addition, the concept of cyclic delta transformation is introduced. Furthermore, comparative results concerning compression rates on different

Compact torus compression of microwaves

International Nuclear Information System (INIS)

Hewett, D.W.; Langdon, A.B.

1985-01-01

The possibility that a compact torus (CT) might be accelerated to large velocities has been suggested by Hartman and Hammer. If this is feasible one application of these moving CTs might be to compress microwaves. The proposed mechanism is that a coaxial vacuum region in front of a CT is prefilled with a number of normal electromagnetic modes on which the CT impinges. A crucial assumption of this proposal is that the CT excludes the microwaves and therefore compresses them. Should the microwaves penetrate the CT, compression efficiency is diminished and significant CT heating results. MFE applications in the same parameters regime have found electromagnetic radiation capable of penetrating, heating, and driving currents. We report here a cursory investigation of rf penetration using a 1-D version of a direct implicit PIC code

Compressive properties of sandwiches with functionally graded ...

Indian Academy of Sciences (India)

319–328. c Indian Academy of Sciences. Compressive properties ... †Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India .... spheres) which might aid in building FG composites is not explored ... Sample code.

Optimal context quantization in lossless compression of image data sequences

DEFF Research Database (Denmark)

Forchhammer, Søren; Wu, X.; Andersen, Jakob Dahl

2004-01-01

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due...... to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context C/sub t/=(X/sub t-t1/,X/sub t-t2/,...,X/sub t-tK/) of a source symbol X/sub t/ into one of a set of conditioning states. The optimality of context...... quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet...

Facial expression coding in children and adolescents with autism: Reduced adaptability but intact norm-based coding.

Science.gov (United States)

Rhodes, Gillian; Burton, Nichola; Jeffery, Linda; Read, Ainsley; Taylor, Libby; Ewing, Louise

2018-05-01

Individuals with autism spectrum disorder (ASD) can have difficulty recognizing emotional expressions. Here, we asked whether the underlying perceptual coding of expression is disrupted. Typical individuals code expression relative to a perceptual (average) norm that is continuously updated by experience. This adaptability of face-coding mechanisms has been linked to performance on various face tasks. We used an adaptation aftereffect paradigm to characterize expression coding in children and adolescents with autism. We asked whether face expression coding is less adaptable in autism and whether there is any fundamental disruption of norm-based coding. If expression coding is norm-based, then the face aftereffects should increase with adaptor expression strength (distance from the average expression). We observed this pattern in both autistic and typically developing participants, suggesting that norm-based coding is fundamentally intact in autism. Critically, however, expression aftereffects were reduced in the autism group, indicating that expression-coding mechanisms are less readily tuned by experience. Reduced adaptability has also been reported for coding of face identity and gaze direction. Thus, there appears to be a pervasive lack of adaptability in face-coding mechanisms in autism, which could contribute to face processing and broader social difficulties in the disorder. © 2017 The British Psychological Society.

On mathematical modelling and numerical simulation of transient compressible flow across open boundaries

Energy Technology Data Exchange (ETDEWEB)

Rian, Kjell Erik

2003-07-01

In numerical simulations of turbulent reacting compressible flows, artificial boundaries are needed to obtain a finite computational domain when an unbounded physical domain is given. Artificial boundaries which fluids are free to cross are called open boundaries. When calculating such flows, non-physical reflections at the open boundaries may occur. These reflections can pollute the solution severely, leading to inaccurate results, and the generation of spurious fluctuations may even cause the numerical simulation to diverge. Thus, a proper treatment of the open boundaries in numerical simulations of turbulent reacting compressible flows is required to obtain a reliable solution for realistic conditions. A local quasi-one-dimensional characteristic-based open-boundary treatment for the Favre-averaged governing equations for time-dependent three-dimensional multi-component turbulent reacting compressible flow is presented. A k-{epsilon} model for turbulent compressible flow and Magnussen's EDC model for turbulent combustion is included in the analysis. The notion of physical boundary conditions is incorporated in the method, and the conservation equations themselves are applied on the boundaries to complement the set of physical boundary conditions. A two-dimensional finite-difference-based computational fluid dynamics code featuring high-order accurate numerical schemes was developed for the numerical simulations. Transient numerical simulations of the well-known, one-dimensional shock-tube problem, a two-dimensional pressure-tower problem in a decaying turbulence field, and a two-dimensional turbulent reacting compressible flow problem have been performed. Flow- and combustion-generated pressure waves seem to be well treated by the non-reflecting subsonic open-boundary conditions. Limitations of the present open-boundary treatment are demonstrated and discussed. The simple and solid physical basis of the method makes it both favourable and relatively easy to

Segmentation-driven compound document coding based on H.264/AVC-INTRA.

Science.gov (United States)

Zaghetto, Alexandre; de Queiroz, Ricardo L

2007-07-01

In this paper, we explore H.264/AVC operating in intraframe mode to compress a mixed image, i.e., composed of text, graphics, and pictures. Even though mixed contents (compound) documents usually require the use of multiple compressors, we apply a single compressor for both text and pictures. For that, distortion is taken into account differently between text and picture regions. Our approach is to use a segmentation-driven adaptation strategy to change the H.264/AVC quantization parameter on a macroblock by macroblock basis, i.e., we deviate bits from pictorial regions to text in order to keep text edges sharp. We show results of a segmentation driven quantizer adaptation method applied to compress documents. Our reconstructed images have better text sharpness compared to straight unadapted coding, at negligible visual losses on pictorial regions. Our results also highlight the fact that H.264/AVC-INTRA outperforms coders such as JPEG-2000 as a single coder for compound images.

Mining compressing sequential problems

NARCIS (Netherlands)

Hoang, T.L.; Mörchen, F.; Fradkin, D.; Calders, T.G.K.

2012-01-01

Compression based pattern mining has been successfully applied to many data mining tasks. We propose an approach based on the minimum description length principle to extract sequential patterns that compress a database of sequences well. We show that mining compressing patterns is NP-Hard and

Radiologic image compression -- A review

International Nuclear Information System (INIS)

Wong, S.; Huang, H.K.; Zaremba, L.; Gooden, D.

1995-01-01

The objective of radiologic image compression is to reduce the data volume of and to achieve a lot bit rate in the digital representation of radiologic images without perceived loss of image quality. However, the demand for transmission bandwidth and storage space in the digital radiology environment, especially picture archiving and communication systems (PACS) and teleradiology, and the proliferating use of various imaging modalities, such as magnetic resonance imaging, computed tomography, ultrasonography, nuclear medicine, computed radiography, and digital subtraction angiography, continue to outstrip the capabilities of existing technologies. The availability of lossy coding techniques for clinical diagnoses further implicates many complex legal and regulatory issues. This paper reviews the recent progress of lossless and lossy radiologic image compression and presents the legal challenges of using lossy compression of medical records. To do so, the authors first describe the fundamental concepts of radiologic imaging and digitization. Then, the authors examine current compression technology in the field of medical imaging and discuss important regulatory policies and legal questions facing the use of compression in this field. The authors conclude with a summary of future challenges and research directions. 170 refs

State of art in FE-based fuel performance codes

International Nuclear Information System (INIS)

Kim, Hyo Chan; Yang, Yong Sik; Kim, Dae Ho; Bang, Je Geon; Kim, Sun Ki; Koo, Yang Hyun

2013-01-01

Finite element (FE) method that is reliable and proven solution in mechanical field has been introduced into fuel performance codes for multidimensional analysis. The present state of the art in numerical simulation of FE-based fuel performance predominantly involves 2-D axisymmetric model and 3-D volumetric model. The FRAPCON and FRAPTRAN own 1.5-D and 2-D FE model to simulate PCMI and cladding ballooning. In 2-D simulation, the FALCON code, developed by EPRI, is a 2-D (R-Z and R-θ) fully thermal-mechanically coupled steady-state and transient FE-based fuel behavior code. The French codes TOUTATIS and ALCYONE which are 3-D, and typically used to investigate localized behavior. In 2008, the Idaho National Laboratory (INL) has been developing multidimensional (2-D and 3-D) nuclear fuel performance code called BISON. In this paper, the current state of FE-based fuel performance code and their models are presented. Based on investigation into the codes, requirements and direction of development for new FE-based fuel performance code can be discussed. Based on comparison of models in FE-based fuel performance code, status of art in the codes can be discussed. A new FE-based fuel performance code should include typical pellet and cladding models which all codes own. In particular, specified pellet and cladding model such as gaseous swelling and high burnup structure (HBS) model should be developed to improve accuracy of code as well as consider AC condition. To reduce computation cost, the approximated gap and the optimized contact model should be also developed. Nuclear fuel operates in an extreme environment that induces complex multiphysics phenomena, occurring over distances ranging from inter-atomic spacing to meters, and times scales ranging from microseconds to years. This multiphysics behavior is often tightly coupled, a well known example being the thermomechanical behavior. Adding to this complexity, important aspects of fuel behavior are inherently

Incorporating Code-Based Software in an Introductory Statistics Course

Science.gov (United States)

Doehler, Kirsten; Taylor, Laura

2015-01-01

This article is based on the experiences of two statistics professors who have taught students to write and effectively utilize code-based software in a college-level introductory statistics course. Advantages of using software and code-based software in this context are discussed. Suggestions are made on how to ease students into using code with…

Characteristic compression strength of a brickwork masonry starting from the strength of its components. Experimental verification of analitycal equations of european codes

Directory of Open Access Journals (Sweden)

Rolando, A.

2006-09-01

Full Text Available In this paper the compression strength of a clay brickwork masonry bound with cement mortar is analyzed. The target is to obtain the characteristic compression strength of unreinforced brickwork masonry. This research try to test the validity of the analytical equations in European codes, comparing the experimental strength with the analytically obtained from the strength of its components (clay brick and cement mortar.En este artículo se analiza la resistencia a compresión de una fábrica de ladrillo cerámico, asentado con mortero de cemento.El objetivo es obtener la resistencia característica a compresión de la fábrica sin armar.La investigación comprueba la fiabilidad de las expresiones analíticas existentes en la normativa europea, comparando la resistencia obtenida experimentalmente con la obtenida analíticamente, a partir de la resistencia de sus componentes (ladrillo cerámico y mortero de cemento.

Compressible flow modelling in unstructured mesh topologies using numerical methods developed for incompressible flows

International Nuclear Information System (INIS)

Caruso, A.; Mechitoua, N.; Duplex, J.

1995-01-01

The R and D thermal hydraulic codes, notably the finite difference codes Melodie (2D) and ESTET (3D) or the 2D and 3D versions of the finite element code N3S were initially developed for incompressible, possibly dilatable, turbulent flows, i.e. those where density is not pressure-dependent. Subsequent minor modifications to these finite difference code algorithms enabled extension of their scope to subsonic compressible flows. The first applications in both single-phase and two flow contexts have now been completed. This paper presents the techniques used to adapt these algorithms for the processing of compressible flows in an N3S type finite element code, whereby complex geometries normally difficult to model in finite difference meshes could be successfully dealt with. The development of version 3.0 of he N3S code led to dilatable flow calculations at lower cost. On this basis, a 2-D prototype version of N3S was programmed, tested and validated, drawing maximum benefit from Cray vectorization possibilities and from physical, numerical or data processing experience with other fluid dynamics codes, such as Melodie, ESTET or TELEMAC. The algorithms are the same as those used in finite difference codes, but their formulation is variational. The first part of the paper deals with the fundamental equations involved, expressed in basic form, together with the associated digital method. The modifications to the k-epsilon turbulence model extended to compressible flows are also described. THe second part presents the algorithm used, indicating the additional terms required by the extension. The third part presents the equations in integral form and the associated matrix systems. The solutions adopted for calculation of the compressibility related terms are indicated. Finally, a few representative applications and test cases are discussed. These include subsonic, but also transsonic and supersonic cases, showing the shock responses of the digital method. The application of

Implementation of LT codes based on chaos

International Nuclear Information System (INIS)

Zhou Qian; Li Liang; Chen Zengqiang; Zhao Jiaxiang

2008-01-01

Fountain codes provide an efficient way to transfer information over erasure channels like the Internet. LT codes are the first codes fully realizing the digital fountain concept. They are asymptotically optimal rateless erasure codes with highly efficient encoding and decoding algorithms. In theory, for each encoding symbol of LT codes, its degree is randomly chosen according to a predetermined degree distribution, and its neighbours used to generate that encoding symbol are chosen uniformly at random. Practical implementation of LT codes usually realizes the randomness through pseudo-randomness number generator like linear congruential method. This paper applies the pseudo-randomness of chaotic sequence in the implementation of LT codes. Two Kent chaotic maps are used to determine the degree and neighbour(s) of each encoding symbol. It is shown that the implemented LT codes based on chaos perform better than the LT codes implemented by the traditional pseudo-randomness number generator. (general)

Loss less real-time data compression based on LZO for steady-state Tokamak DAS

International Nuclear Information System (INIS)

Pujara, H.D.; Sharma, Manika

2008-01-01

The evolution of data acquisition system (DAS) for steady-state operation of Tokamak has been technology driven. Steady-state Tokamak demands a data acquisition system which is capable enough to acquire data losslessly from diagnostics. The needs of loss less continuous acquisition have a significant effect on data storage and takes up a greater portion of any data acquisition systems. Another basic need of steady state of nature of operation demands online viewing of data which loads the LAN significantly. So there is strong demand for something that would control the expansion of both these portion by a way of employing compression technique in real time. This paper presents a data acquisition systems employing real-time data compression technique based on LZO. It is a data compression library which is suitable for data compression and decompression in real time. The algorithm used favours speed over compression ratio. The system has been rigged up based on PXI bus and dual buffer mode architecture is implemented for loss less acquisition. The acquired buffer is compressed in real time and streamed to network and hard disk for storage. Observed performance of measure on various data type like binary, integer float, types of different type of wave form as well as compression timing overheads has been presented in the paper. Various software modules for real-time acquiring, online viewing of data on network nodes have been developed in LabWindows/CVI based on client server architecture

Beam steering performance of compressed Luneburg lens based on transformation optics

Science.gov (United States)

Gao, Ju; Wang, Cong; Zhang, Kuang; Hao, Yang; Wu, Qun

2018-06-01

In this paper, two types of compressed Luneburg lenses based on transformation optics are investigated and simulated using two different sources, namely, waveguides and dipoles, which represent plane and spherical wave sources, respectively. We determined that the largest beam steering angle and the related feed point are intrinsic characteristics of a certain type of compressed Luneburg lens, and that the optimized distance between the feed and lens, gain enhancement, and side-lobe suppression are related to the type of source. Based on our results, we anticipate that these lenses will prove useful in various future antenna applications.

Lossless Compression of Broadcast Video

DEFF Research Database (Denmark)

Martins, Bo; Eriksen, N.; Faber, E.

1998-01-01

We investigate several techniques for lossless and near-lossless compression of broadcast video.The emphasis is placed on the emerging international standard for compression of continous-tone still images, JPEG-LS, due to its excellent compression performance and moderatecomplexity. Except for one...... cannot be expected to code losslessly at a rate of 125 Mbit/s. We investigate the rate and quality effects of quantization using standard JPEG-LS quantization and two new techniques: visual quantization and trellis quantization. Visual quantization is not part of baseline JPEG-LS, but is applicable...... in the framework of JPEG-LS. Visual tests show that this quantization technique gives much better quality than standard JPEG-LS quantization. Trellis quantization is a process by which the original image is altered in such a way as to make lossless JPEG-LS encoding more effective. For JPEG-LS and visual...

Compressive strength and microstructural analysis of fly ash/palm oil fuel ash based geopolymer mortar

International Nuclear Information System (INIS)

Ranjbar, Navid; Mehrali, Mehdi; Behnia, Arash; Alengaram, U. Johnson; Jumaat, Mohd Zamin

2014-01-01

Highlights: • Results show POFA is adaptable as replacement in FA based geopolymer mortar. • The increase in POFA/FA ratio delay of the compressive development of geopolymer. • The density of POFA based geoploymer is lower than FA based geopolymer mortar. - Abstract: This paper presents the effects and adaptability of palm oil fuel ash (POFA) as a replacement material in fly ash (FA) based geopolymer mortar from the aspect of microstructural and compressive strength. The geopolymers developed were synthesized with a combination of sodium hydroxide and sodium silicate as activator and POFA and FA as high silica–alumina resources. The development of compressive strength of POFA/FA based geopolymers was investigated using X-ray florescence (XRF), X-ray diffraction (XRD), Fourier transform infrared (FTIR), and field emission scanning electron microscopy (FESEM). It was observed that the particle shapes and surface area of POFA and FA as well as chemical composition affects the density and compressive strength of the mortars. The increment in the percentages of POFA increased the silica/alumina (SiO 2 /Al 2 O 3 ) ratio and that resulted in reduction of the early compressive strength of the geopolymer and delayed the geopolymerization process

SSWL and BWL: finite element models of compressed magnetic field current generators

Energy Technology Data Exchange (ETDEWEB)

Tucker, T.J.; Leeman, J.E.

1976-01-01

Documentation is presented for two new computer codes modeling the behavior of compressed magnetic field current generators. Code output results for the typical generator configurations are presented and compared to experimental results. (auth)

Toward topology-based characterization of small-scale mixing in compressible turbulence

Science.gov (United States)

Suman, Sawan; Girimaji, Sharath

2011-11-01

Turbulent mixing rate at small scales of motion (molecular mixing) is governed by the steepness of the scalar-gradient field which in turn is dependent upon the prevailing velocity gradients. Thus motivated, we propose a velocity-gradient topology-based approach for characterizing small-scale mixing in compressible turbulence. We define a mixing efficiency metric that is dependent upon the topology of the solenoidal and dilatational deformation rates of a fluid element. The mixing characteristics of solenoidal and dilatational velocity fluctuations are clearly delineated. We validate this new approach by employing mixing data from direct numerical simulations (DNS) of compressible decaying turbulence with passive scalar. For each velocity-gradient topology, we compare the mixing efficiency predicted by the topology-based model with the corresponding conditional scalar variance obtained from DNS. The new mixing metric accurately distinguishes good and poor mixing topologies and indeed reasonably captures the numerical values. The results clearly demonstrate the viability of the proposed approach for characterizing and predicting mixing in compressible flows.

Lossless compression of waveform data for efficient storage and transmission

International Nuclear Information System (INIS)

Stearns, S.D.; Tan, Li Zhe; Magotra, Neeraj

1993-01-01

Compression of waveform data is significant in many engineering and research areas since it can be used to alleviate data storage and transmission bandwidth. For example, seismic data are widely recorded and transmitted so that analysis can be performed on large amounts of data for numerous applications such as petroleum exploration, determination of the earth's core structure, seismic event detection and discrimination of underground nuclear explosions, etc. This paper describes a technique for lossless wave form data compression. The technique consists of two stages. The first stage is a modified form of linear prediction with discrete coefficients and the second stage is bi-level sequence coding. The linear predictor generates an error or residue sequence in a way such that exact reconstruction of the original data sequence can be accomplished with a simple algorithm. The residue sequence is essentially white Gaussian with seismic or other similar waveform data. Bi-level sequence coding, in which two sample sizes are chosen and the residue sequence is encoded into subsequences that alternate from one level to the other, further compresses the residue sequence. The principal feature of the two-stage data compression algorithm is that it is lossless, that is, it allows exact, bit-for-bit recovery of the original data sequence. The performance of the lossless compression algorithm at each stage is analyzed. The advantages of using bi-level sequence coding in the second stage are its simplicity of implementation, its effectiveness on data with large amplitude variations, and its near-optimal performance in encoding Gaussian sequences. Applications of the two-stage technique to typical seismic data indicates that an average number of compressed bits per sample close to the lower bound is achievable in practical situations

smallWig: parallel compression of RNA-seq WIG files.

Science.gov (United States)

Wang, Zhiying; Weissman, Tsachy; Milenkovic, Olgica

2016-01-15

We developed a new lossless compression method for WIG data, named smallWig, offering the best known compression rates for RNA-seq data and featuring random access functionalities that enable visualization, summary statistics analysis and fast queries from the compressed files. Our approach results in order of magnitude improvements compared with bigWig and ensures compression rates only a fraction of those produced by cWig. The key features of the smallWig algorithm are statistical data analysis and a combination of source coding methods that ensure high flexibility and make the algorithm suitable for different applications. Furthermore, for general-purpose file compression, the compression rate of smallWig approaches the empirical entropy of the tested WIG data. For compression with random query features, smallWig uses a simple block-based compression scheme that introduces only a minor overhead in the compression rate. For archival or storage space-sensitive applications, the method relies on context mixing techniques that lead to further improvements of the compression rate. Implementations of smallWig can be executed in parallel on different sets of chromosomes using multiple processors, thereby enabling desirable scaling for future transcriptome Big Data platforms. The development of next-generation sequencing technologies has led to a dramatic decrease in the cost of DNA/RNA sequencing and expression profiling. RNA-seq has emerged as an important and inexpensive technology that provides information about whole transcriptomes of various species and organisms, as well as different organs and cellular communities. The vast volume of data generated by RNA-seq experiments has significantly increased data storage costs and communication bandwidth requirements. Current compression tools for RNA-seq data such as bigWig and cWig either use general-purpose compressors (gzip) or suboptimal compression schemes that leave significant room for improvement. To substantiate

Non-Binary Protograph-Based LDPC Codes: Analysis,Enumerators and Designs

OpenAIRE

Sun, Yizeng

2013-01-01

Non-binary LDPC codes can outperform binary LDPC codes using sum-product algorithm with higher computation complexity. Non-binary LDPC codes based on protographs have the advantage of simple hardware architecture. In the first part of this thesis, we will use EXIT chart analysis to compute the thresholds of different protographs over GF(q). Based on threshold computation, some non-binary protograph-based LDPC codes are designed and their frame error rates are compared with binary LDPC codes. ...

Fundamentals of information theory and coding design

CERN Document Server

Togneri, Roberto

2003-01-01

In a clear, concise, and modular format, this book introduces the fundamental concepts and mathematics of information and coding theory. The authors emphasize how a code is designed and discuss the main properties and characteristics of different coding algorithms along with strategies for selecting the appropriate codes to meet specific requirements. They provide comprehensive coverage of source and channel coding, address arithmetic, BCH, and Reed-Solomon codes and explore some more advanced topics such as PPM compression and turbo codes. Worked examples and sets of basic and advanced exercises in each chapter reinforce the text's clear explanations of all concepts and methodologies.

A design approach for systems based on magnetic pulse compression

International Nuclear Information System (INIS)

Praveen Kumar, D. Durga; Mitra, S.; Senthil, K.; Sharma, D. K.; Rajan, Rehim N.; Sharma, Archana; Nagesh, K. V.; Chakravarthy, D. P.

2008-01-01

A design approach giving the optimum number of stages in a magnetic pulse compression circuit and gain per stage is given. The limitation on the maximum gain per stage is discussed. The total system volume minimization is done by considering the energy storage capacitor volume and magnetic core volume at each stage. At the end of this paper, the design of a magnetic pulse compression based linear induction accelerator of 200 kV, 5 kA, and 100 ns with a repetition rate of 100 Hz is discussed with its experimental results

Four year-olds use norm-based coding for face identity.

Science.gov (United States)

Jeffery, Linda; Read, Ainsley; Rhodes, Gillian

2013-05-01

Norm-based coding, in which faces are coded as deviations from an average face, is an efficient way of coding visual patterns that share a common structure and must be distinguished by subtle variations that define individuals. Adults and school-aged children use norm-based coding for face identity but it is not yet known if pre-school aged children also use norm-based coding. We reasoned that the transition to school could be critical in developing a norm-based system because school places new demands on children's face identification skills and substantially increases experience with faces. Consistent with this view, face identification performance improves steeply between ages 4 and 7. We used face identity aftereffects to test whether norm-based coding emerges between these ages. We found that 4 year-old children, like adults, showed larger face identity aftereffects for adaptors far from the average than for adaptors closer to the average, consistent with use of norm-based coding. We conclude that experience prior to age 4 is sufficient to develop a norm-based face-space and that failure to use norm-based coding cannot explain 4 year-old children's poor face identification skills. Copyright © 2013 Elsevier B.V. All rights reserved.

AN ENCODING METHOD FOR COMPRESSING GEOGRAPHICAL COORDINATES IN 3D SPACE

Directory of Open Access Journals (Sweden)

C. Qian

2017-09-01

Full Text Available This paper proposed an encoding method for compressing geographical coordinates in 3D space. By the way of reducing the length of geographical coordinates, it helps to lessen the storage size of geometry information. In addition, the encoding algorithm subdivides the whole space according to octree rules, which enables progressive transmission and loading. Three main steps are included in this method: (1 subdividing the whole 3D geographic space based on octree structure, (2 resampling all the vertices in 3D models, (3 encoding the coordinates of vertices with a combination of Cube Index Code (CIC and Geometry Code. A series of geographical 3D models were applied to evaluate the encoding method. The results showed that this method reduced the storage size of most test data by 90 % or even more under the condition of a speed of encoding and decoding. In conclusion, this method achieved a remarkable compression rate in vertex bit size with a steerable precision loss. It shall be of positive meaning to the web 3d map storing and transmission.

Radiological Image Compression

Science.gov (United States)

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.

A multi-GPU implementation of a D2Q37 lattice Boltzmann code

NARCIS (Netherlands)

Biferale, L.; Mantovani, F.; Pivanti, M.; Pozzati, F.; Sbragaglia, M.; Scagliarini, Andrea; Schifano, S.F.; Toschi, F.; Tripiccione, R.; Wyrzykowski, R.; Dongarra, J.; Karczewski, K.; Wasniewski, J.

2012-01-01

We describe a parallel implementation of a compressible Lattice Boltzmann code on a multi-GPU cluster based on Nvidia Fermi processors. We analyze how to optimize the algorithm for GP-GPU architectures, describe the implementation choices that we have adopted and compare our performance results with

Inelastic response of silicon to shock compression.

Science.gov (United States)

Higginbotham, A; Stubley, P G; Comley, A J; Eggert, J H; Foster, J M; Kalantar, D H; McGonegle, D; Patel, S; Peacock, L J; Rothman, S D; Smith, R F; Suggit, M J; Wark, J S

2016-04-13

The elastic and inelastic response of [001] oriented silicon to laser compression has been a topic of considerable discussion for well over a decade, yet there has been little progress in understanding the basic behaviour of this apparently simple material. We present experimental x-ray diffraction data showing complex elastic strain profiles in laser compressed samples on nanosecond timescales. We also present molecular dynamics and elasticity code modelling which suggests that a pressure induced phase transition is the cause of the previously reported 'anomalous' elastic waves. Moreover, this interpretation allows for measurement of the kinetic timescales for transition. This model is also discussed in the wider context of reported deformation of silicon to rapid compression in the literature.

Acceleration of beam ions during major radius compression in TFTR

International Nuclear Information System (INIS)

Wong, K.L.; Bitter, M.; Hammett, G.W.

1985-09-01

Tangentially co-injected deuterium beam ions were accelerated from 82 keV up to 150 keV during a major radius compression experiment in TFTR. The ion energy spectra and the variation in fusion yield were in good agreement with Fokker-Planck code simulations. In addition, the plasma rotation velocity was observed to rise during compression

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

Energy Technology Data Exchange (ETDEWEB)

Shih, Tzu-Ching [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, 40402, Taiwan (China); Chen, Jeon-Hor; Nie Ke; Lin Muqing; Chang, Daniel; Nalcioglu, Orhan; Su, Min-Ying [Tu and Yuen Center for Functional Onco-Imaging and Radiological Sciences, University of California, Irvine, CA 92697 (United States); Liu Dongxu; Sun Lizhi, E-mail: shih@mail.cmu.edu.t [Department of Civil and Environmental Engineering, University of California, Irvine, CA 92697 (United States)

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 (registered) 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 (registered) 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

A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression

Directory of Open Access Journals (Sweden)

J. Soraghan

2007-01-01

Full Text Available Lattice vector quantization (LVQ reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by “blowing out” the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.

A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression

Directory of Open Access Journals (Sweden)

Salleh MFM

2007-01-01

Full Text Available Lattice vector quantization (LVQ reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.

Experimental Investigation of Compression with Fixed-length Code Quantization for Convergent Access-Mobile Networks

OpenAIRE

L. Anet Neto; P. Chanclou; Z. Tayq; B. C. Zabada; F. Saliou; G. Simon

2016-01-01

We experimentally assess compression with scalar and vector quantization for fixed-mobile convergent networks. We show that four-dimensional vector quantization allows 73% compression compliant with 3GPP EVM recommendations for transmissions over 25 km SSMF with 1:16 split ratio.

Modeling Drift Compression in an Integrated Beam Experiment for Heavy-Ion-Fusion

Science.gov (United States)

Sharp, W. M.; Barnard, J. J.; Friedman, A.; Grote, D. P.; Celata, C. M.; Yu, S. S.

2003-10-01

The Integrated Beam Experiment (IBX) is an induction accelerator being designed to further develop the science base for heavy-ion fusion. The experiment is being developed jointly by Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, and Princeton Plasma Physics Laboratory. One conceptual approach would first accelerate a 0.5-1 A beam of singly charged potassium ions to 5 MeV, impose a head-to-tail velocity tilt to compress the beam longitudinally, and finally focus the beam radiallly using a series of quadrupole lenses. The lengthwise compression is a critical step because the radial size must be controlled as the current increases, and the beam emittance must be kept minimal. The work reported here first uses the moment-based model HERMES to design the drift-compression beam line and to assess the sensitivity of the final beam profile to beam and lattice errors. The particle-in-cell code WARP is then used to validate the physics design, study the phase-space evolution, and quantify the emittance growth.

Generalized wall function and its application to compressible turbulent boundary layer over a flat plate

Science.gov (United States)

Liu, J.; Wu, S. P.

2017-04-01

Wall function boundary conditions including the effects of compressibility and heat transfer are improved for compressible turbulent boundary flows. Generalized wall function formulation at zero-pressure gradient is proposed based on coupled velocity and temperature profiles in the entire near-wall region. The parameters in the generalized wall function are well revised. The proposed boundary conditions are integrated into Navier-Stokes computational fluid dynamics code that includes the shear stress transport turbulence model. Numerical results are presented for a compressible boundary layer over a flat plate at zero-pressure gradient. Compared with experimental data, the computational results show that the generalized wall function reduces the first grid spacing in the directed normal to the wall and proves the feasibility and effectivity of the generalized wall function method.

Benchmarking the Multidimensional Stellar Implicit Code MUSIC

Science.gov (United States)

Goffrey, T.; Pratt, J.; Viallet, M.; Baraffe, I.; Popov, M. V.; Walder, R.; Folini, D.; Geroux, C.; Constantino, T.

2017-04-01

We present the results of a numerical benchmark study for the MUltidimensional Stellar Implicit Code (MUSIC) based on widely applicable two- and three-dimensional compressible hydrodynamics problems relevant to stellar interiors. MUSIC is an implicit large eddy simulation code that uses implicit time integration, implemented as a Jacobian-free Newton Krylov method. A physics based preconditioning technique which can be adjusted to target varying physics is used to improve the performance of the solver. The problems used for this benchmark study include the Rayleigh-Taylor and Kelvin-Helmholtz instabilities, and the decay of the Taylor-Green vortex. Additionally we show a test of hydrostatic equilibrium, in a stellar environment which is dominated by radiative effects. In this setting the flexibility of the preconditioning technique is demonstrated. This work aims to bridge the gap between the hydrodynamic test problems typically used during development of numerical methods and the complex flows of stellar interiors. A series of multidimensional tests were performed and analysed. Each of these test cases was analysed with a simple, scalar diagnostic, with the aim of enabling direct code comparisons. As the tests performed do not have analytic solutions, we verify MUSIC by comparing it to established codes including ATHENA and the PENCIL code. MUSIC is able to both reproduce behaviour from established and widely-used codes as well as results expected from theoretical predictions. This benchmarking study concludes a series of papers describing the development of the MUSIC code and provides confidence in future applications.

Development of information preserving data compression algorithm for CT images

International Nuclear Information System (INIS)

Kobayashi, Yoshio

1989-01-01

Although digital imaging techniques in radiology develop rapidly, problems arise in archival storage and communication of image data. This paper reports on a new information preserving data compression algorithm for computed tomographic (CT) images. This algorithm consists of the following five processes: 1. Pixels surrounding the human body showing CT values smaller than -900 H.U. are eliminated. 2. Each pixel is encoded by its numerical difference from its neighboring pixel along a matrix line. 3. Difference values are encoded by a newly designed code rather than the natural binary code. 4. Image data, obtained with the above process, are decomposed into bit planes. 5. The bit state transitions in each bit plane are encoded by run length coding. Using this new algorithm, the compression ratios of brain, chest, and abdomen CT images are 4.49, 4.34. and 4.40 respectively. (author)

A Multiresolution Image Completion Algorithm for Compressing Digital Color Images

Directory of Open Access Journals (Sweden)

R. Gomathi

2014-01-01

Full Text Available This paper introduces a new framework for image coding that uses image inpainting method. In the proposed algorithm, the input image is subjected to image analysis to remove some of the portions purposefully. At the same time, edges are extracted from the input image and they are passed to the decoder in the compressed manner. The edges which are transmitted to decoder act as assistant information and they help inpainting process fill the missing regions at the decoder. Textural synthesis and a new shearlet inpainting scheme based on the theory of p-Laplacian operator are proposed for image restoration at the decoder. Shearlets have been mathematically proven to represent distributed discontinuities such as edges better than traditional wavelets and are a suitable tool for edge characterization. This novel shearlet p-Laplacian inpainting model can effectively reduce the staircase effect in Total Variation (TV inpainting model whereas it can still keep edges as well as TV model. In the proposed scheme, neural network is employed to enhance the value of compression ratio for image coding. Test results are compared with JPEG 2000 and H.264 Intracoding algorithms. The results show that the proposed algorithm works well.

Cartesian anisotropic mesh adaptation for compressible flow

International Nuclear Information System (INIS)

Keats, W.A.; Lien, F.-S.

2004-01-01

Simulating transient compressible flows involving shock waves presents challenges to the CFD practitioner in terms of the mesh quality required to resolve discontinuities and prevent smearing. This paper discusses a novel two-dimensional Cartesian anisotropic mesh adaptation technique implemented for compressible flow. This technique, developed for laminar flow by Ham, Lien and Strong, is efficient because it refines and coarsens cells using criteria that consider the solution in each of the cardinal directions separately. In this paper the method will be applied to compressible flow. The procedure shows promise in its ability to deliver good quality solutions while achieving computational savings. The convection scheme used is the Advective Upstream Splitting Method (Plus), and the refinement/ coarsening criteria are based on work done by Ham et al. Transient shock wave diffraction over a backward step and shock reflection over a forward step are considered as test cases because they demonstrate that the quality of the solution can be maintained as the mesh is refined and coarsened in time. The data structure is explained in relation to the computational mesh, and the object-oriented design and implementation of the code is presented. Refinement and coarsening algorithms are outlined. Computational savings over uniform and isotropic mesh approaches are shown to be significant. (author)

OTDM-WDM Conversion Based on Time-Domain Optical Fourier Transformation with Spectral Compression

DEFF Research Database (Denmark)

Mulvad, Hans Christian Hansen; Palushani, Evarist; Galili, Michael

2011-01-01

We propose a scheme enabling direct serial-to-parallel conversion of OTDM data tributaries onto a WDM grid, based on optical Fourier transformation with spectral compression. Demonstrations on 320 Gbit/s and 640 Gbit/s OTDM data are shown.......We propose a scheme enabling direct serial-to-parallel conversion of OTDM data tributaries onto a WDM grid, based on optical Fourier transformation with spectral compression. Demonstrations on 320 Gbit/s and 640 Gbit/s OTDM data are shown....

Filtering, Coding, and Compression with Malvar Wavelets

Science.gov (United States)

1993-12-01

speech coding techniques being investigated by the military (38). Imagery: Space imagery often requires adaptive restoration to deblur out-of-focus...and blurred image, find an estimate of the ideal image using a priori information about the blur, noise , and the ideal image" (12). The research for...recording can be described as the original signal convolved with impulses , which appear as echoes in the seismic event. The term deconvolution indicates

Four Year-Olds Use Norm-Based Coding for Face Identity

Science.gov (United States)

Jeffery, Linda; Read, Ainsley; Rhodes, Gillian

2013-01-01

Norm-based coding, in which faces are coded as deviations from an average face, is an efficient way of coding visual patterns that share a common structure and must be distinguished by subtle variations that define individuals. Adults and school-aged children use norm-based coding for face identity but it is not yet known if pre-school aged…

NASA Lewis Steady-State Heat Pipe Code Architecture

Science.gov (United States)

Mi, Ye; Tower, Leonard K.

2013-01-01

NASA Glenn Research Center (GRC) has developed the LERCHP code. The PC-based LERCHP code can be used to predict the steady-state performance of heat pipes, including the determination of operating temperature and operating limits which might be encountered under specified conditions. The code contains a vapor flow algorithm which incorporates vapor compressibility and axially varying heat input. For the liquid flow in the wick, Darcy s formula is employed. Thermal boundary conditions and geometric structures can be defined through an interactive input interface. A variety of fluid and material options as well as user defined options can be chosen for the working fluid, wick, and pipe materials. This report documents the current effort at GRC to update the LERCHP code for operating in a Microsoft Windows (Microsoft Corporation) environment. A detailed analysis of the model is presented. The programming architecture for the numerical calculations is explained and flowcharts of the key subroutines are given

Contributions to HEVC Prediction for Medical Image Compression

OpenAIRE

Guarda, André Filipe Rodrigues

2016-01-01

Medical imaging technology and applications are continuously evolving, dealing with images of increasing spatial and temporal resolutions, which allow easier and more accurate medical diagnosis. However, this increase in resolution demands a growing amount of data to be stored and transmitted. Despite the high coding efficiency achieved by the most recent image and video coding standards in lossy compression, they are not well suited for quality-critical medical image compressi...

Harmonic analysis in integrated energy system based on compressed sensing

International Nuclear Information System (INIS)

Yang, Ting; Pen, Haibo; Wang, Dan; Wang, Zhaoxia

2016-01-01

Highlights: • We propose a harmonic/inter-harmonic analysis scheme with compressed sensing theory. • Property of sparseness of harmonic signal in electrical power system is proved. • The ratio formula of fundamental and harmonic components sparsity is presented. • Spectral Projected Gradient-Fundamental Filter reconstruction algorithm is proposed. • SPG-FF enhances the precision of harmonic detection and signal reconstruction. - Abstract: The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In the proposed scheme, the sparsity of the harmonic signals in the base of the Discrete Fourier Transform (DFT) is numerically calculated first. This is followed by providing a proof of the matching satisfaction of the necessary conditions for compressed sensing. The binary sparse measurement is then leveraged to reduce the storage space in the sampling unit in the proposed scheme. In the recovery process, the scheme proposed a novel reconstruction algorithm called the Spectral Projected Gradient with Fundamental Filter (SPG-FF) algorithm to enhance the reconstruction precision. One of the actual microgrid systems is used as simulation example. The results of the experiment shows that the proposed scheme effectively enhances the precision of harmonic and inter-harmonic detection with low computing complexity, and has good

Image compression with Iris-C

Science.gov (United States)

Gains, David

2009-05-01

Iris-C is an image codec designed for streaming video applications that demand low bit rate, low latency, lossless image compression. To achieve compression and low latency the codec features the discrete wavelet transform, Exp-Golomb coding, and online processes that construct dynamic models of the input video. Like H.264 and Dirac, the Iris-C codec accepts input video from both the YUV and YCOCG colour spaces, but the system can also operate on Bayer RAW data read directly from an image sensor. Testing shows that the Iris-C codec is competitive with the Dirac low delay syntax codec which is typically regarded as the state-of-the-art low latency, lossless video compressor.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

OpenAIRE

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 vari...

Analog system for computing sparse codes

Science.gov (United States)

Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell

2010-08-24

A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.

Lossless Compression of Digital Images

DEFF Research Database (Denmark)

Martins, Bo

Presently, tree coders are the best bi-level image coders. The currentISO standard, JBIG, is a good example.By organising code length calculations properly a vast number of possible models (trees) can be investigated within reasonable time prior to generating code.A number of general-purpose coders...... version that is substantially faster than its precursorsand brings it close to the multi-pass coders in compression performance.Handprinted characters are of unequal complexity; recent work by Singer and Tishby demonstrates that utilizing the physiological process of writing one can synthesize cursive.......The feature vector of a bitmap initially constitutes a lossy representation of the contour(s) of the bitmap. The initial feature space is usually too large but can be reduced automatically by use ofa predictive code length or predictive error criterion....

Mammographic compression in Asian women.

Science.gov (United States)

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 (pAsian 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.

Multispectral code excited linear prediction coding and its application in magnetic resonance images.

Science.gov (United States)

Hu, J H; Wang, Y; Cahill, P T

1997-01-01

This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.

Hot-compress: A new postdeposition treatment for ZnO-based flexible dye-sensitized solar cells

Energy Technology Data Exchange (ETDEWEB)

Haque Choudhury, Mohammad Shamimul, E-mail: shamimul129@gmail.com [Department of Frontier Material, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555 (Japan); Department of Electrical and Electronic Engineering, International Islamic University Chittagong, b154/a, College Road, Chittagong 4203 (Bangladesh); Kishi, Naoki; Soga, Tetsuo [Department of Frontier Material, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555 (Japan)

2016-08-15

Highlights: • A new postdeposition treatment named hot-compress is introduced. • Hot-compression gives homogeneous compact layer ZnO photoanode. • I-V and EIS analysis data confirms the efficacy of this method. • Charge transport resistance was reduced by the application of hot-compression. - Abstract: This article introduces a new postdeposition treatment named hot-compress for flexible zinc oxide–base dye-sensitized solar cells. This postdeposition treatment includes the application of compression pressure at an elevated temperature. The optimum compression pressure of 130 Ma at an optimum compression temperature of 70 °C heating gives better photovoltaic performance compared to the conventional cells. The aptness of this method was confirmed by investigating scanning electron microscopy image, X-ray diffraction, current-voltage and electrochemical impedance spectroscopy analysis of the prepared cells. Proper heating during compression lowers the charge transport resistance, longer the electron lifetime of the device. As a result, the overall power conversion efficiency of the device was improved about 45% compared to the conventional room temperature compressed cell.

Effect of feedback on delaying deterioration in quality of compressions during 2 minutes of continuous chest compressions

DEFF Research Database (Denmark)

Lyngeraa, Tobias S; Hjortrup, Peter Buhl; Wulff, Nille B

2012-01-01

delays deterioration of quality of compressions. METHODS: Participants attending a national one-day conference on cardiac arrest and CPR in Denmark were randomized to perform single-rescuer BLS with (n = 26) or without verbal and visual feedback (n = 28) on a manikin using a ZOLL AED plus. Data were...... analyzed using Rescuenet Code Review. Blinding of participants was not possible, but allocation concealment was performed. Primary outcome was the proportion of delivered compressions within target depth compared over a 2-minute period within the groups and between the groups. Secondary outcome...... was the proportion of delivered compressions within target rate compared over a 2-minute period within the groups and between the groups. Performance variables for 30-second intervals were analyzed and compared. RESULTS: 24 (92%) and 23 (82%) had CPR experience in the group with and without feedback respectively. 14...

Empirical and Statistical Evaluation of the Effectiveness of Four Lossless Data Compression Algorithms

Directory of Open Access Journals (Sweden)

N. A. Azeez

2017-04-01

Full Text Available Data compression is the process of reducing the size of a file to effectively reduce storage space and communication cost. The evolvement in technology and digital age has led to an unparalleled usage of digital files in this current decade. The usage of data has resulted to an increase in the amount of data being transmitted via various channels of data communication which has prompted the need to look into the current lossless data compression algorithms to check for their level of effectiveness so as to maximally reduce the bandwidth requirement in communication and transfer of data. Four lossless data compression algorithm: Lempel-Ziv Welch algorithm, Shannon-Fano algorithm, Adaptive Huffman algorithm and Run-Length encoding have been selected for implementation. The choice of these algorithms was based on their similarities, particularly in application areas. Their level of efficiency and effectiveness were evaluated using some set of predefined performance evaluation metrics namely compression ratio, compression factor, compression time, saving percentage, entropy and code efficiency. The algorithms implementation was done in the NetBeans Integrated Development Environment using Java as the programming language. Through the statistical analysis performed using Boxplot and ANOVA and comparison made on the four algo

Lossy compression of TPC data and trajectory tracking efficiency for the ALICE experiment

CERN Document Server

Nicolaucig, A; Mattavelli, M

2003-01-01

In this paper a quasi-lossless algorithm for the on-line compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN is described. The algorithm is based on a lossy source code modeling technique, i.e. it is based on a source model which is lossy if samples of the TPC signal are considered one by one; conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse, representing the pulse charge and the time localization of the pulse. So as to evaluate the consequences of the error introduced by the lossy compression process, the results of the trajectory tracking algorithms that process data off-line after the experiment are analyzed, in particular, versus their sensibility to the noise introduced by the compression. Two different versions of these off- line algorithms are described,...

GAP--a PIC-type fluid code

International Nuclear Information System (INIS)

Marder, B.M.

1975-01-01

GAP, a PIC-type fluid code for computing compressible flows, is described and demonstrated. While retaining some features of PIC, it is felt that the GAP approach is conceptually and operationally simpler. 9 figures

Two-fluid and parallel compressibility effects in tokamak plasmas

International Nuclear Information System (INIS)

Sugiyama, L.E.; Park, W.

1998-01-01

The MHD, or single fluid, model for a plasma has long been known to provide a surprisingly good description of much of the observed nonlinear dynamics of confined plasmas, considering its simple nature compared to the complexity of the real system. On the other hand, some of the supposed agreement arises from the lack of the detailed measurements that are needed to distinguish MHD from more sophisticated models that incorporate slower time scale processes. At present, a number of factors combine to make models beyond MHD of practical interest. Computational considerations still favor fluid rather than particle models for description of the full plasma, and suggest an approach that starts from a set of fluid-like equations that extends MHD to slower time scales and more accurate parallel dynamics. This paper summarizes a set of two-fluid equations for toroidal (tokamak) geometry that has been developed and tested as the MH3D-T code [1] and some results from the model. The electrons and ions are described as separate fluids. The code and its original MHD version, MH3D [2], are the first numerical, initial value models in toroidal geometry that include the full 3D (fluid) compressibility and electromagnetic effects. Previous nonlinear MHD codes for toroidal geometry have, in practice, neglected the plasma density evolution, on the grounds that MHD plasmas are only weakly compressible and that the background density variation is weaker than the temperature variation. Analytically, the common use of toroidal plasma models based on aspect ratio expansion, such as reduced MHD, has reinforced this impression, since this ordering reduces plasma compressibility effects. For two-fluid plasmas, the density evolution cannot be neglected in principle, since it provides the basic driving energy for the diamagnetic drifts of the electrons and ions perpendicular to the magnetic field. It also strongly influences the parallel dynamics, in combination with the parallel thermal

Lossless medical image compression with a hybrid coder

Science.gov (United States)

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.

CEPRAM: Compression for Endurance in PCM RAM

OpenAIRE

González Alberquilla, Rodrigo; Castro Rodríguez, Fernando; Piñuel Moreno, Luis; Tirado Fernández, Francisco

2017-01-01

We deal with the endurance problem of Phase Change Memories (PCM) by proposing Compression for Endurance in PCM RAM (CEPRAM), a technique to elongate the lifespan of PCM-based main memory through compression. We introduce a total of three compression schemes based on already existent schemes, but targeting compression for PCM-based systems. We do a two-level evaluation. First, we quantify the performance of the compression, in terms of compressed size, bit-flips and how they are affected by e...

Influence of chest compression artefact on capnogram-based ventilation detection during out-of-hospital cardiopulmonary resuscitation.

Science.gov (United States)

Leturiondo, Mikel; Ruiz de Gauna, Sofía; Ruiz, Jesus M; Julio Gutiérrez, J; Leturiondo, Luis A; González-Otero, Digna M; Russell, James K; Zive, Dana; Daya, Mohamud

2018-03-01

Capnography has been proposed as a method for monitoring the ventilation rate during cardiopulmonary resuscitation (CPR). A high incidence (above 70%) of capnograms distorted by chest compression induced oscillations has been previously reported in out-of-hospital (OOH) CPR. The aim of the study was to better characterize the chest compression artefact and to evaluate its influence on the performance of a capnogram-based ventilation detector during OOH CPR. Data from the MRx monitor-defibrillator were extracted from OOH cardiac arrest episodes. For each episode, presence of chest compression artefact was annotated in the capnogram. Concurrent compression depth and transthoracic impedance signals were used to identify chest compressions and to annotate ventilations, respectively. We designed a capnogram-based ventilation detection algorithm and tested its performance with clean and distorted episodes. Data were collected from 232 episodes comprising 52 654 ventilations, with a mean (±SD) of 227 (±118) per episode. Overall, 42% of the capnograms were distorted. Presence of chest compression artefact degraded algorithm performance in terms of ventilation detection, estimation of ventilation rate, and the ability to detect hyperventilation. Capnogram-based ventilation detection during CPR using our algorithm was compromised by the presence of chest compression artefact. In particular, artefact spanning from the plateau to the baseline strongly degraded ventilation detection, and caused a high number of false hyperventilation alarms. Further research is needed to reduce the impact of chest compression artefact on capnographic ventilation monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Guessing and compression subject to distortion

OpenAIRE

Hanawal, Manjesh Kumar; Sundaresan, Rajesh

2010-01-01

The problem of guessing a random string is revisited. The relation-ship between guessing without distortion and compression is extended to the case when source alphabet size is countably in¯nite. Further, similar relationship is established for the case when distortion allowed by establishing a tight relationship between rate distortion codes and guessing strategies.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

Science.gov (United States)

Lin, Shu

1998-01-01

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and

Image splitting and remapping method for radiological image compression

Science.gov (United States)

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.

A blended pressure/density based method for the computation of incompressible and compressible flows

International Nuclear Information System (INIS)

Rossow, C.-C.

2003-01-01

An alternative method to low speed preconditioning for the computation of nearly incompressible flows with compressible methods is developed. For this approach the leading terms of the flux difference splitting (FDS) approximate Riemann solver are analyzed in the incompressible limit. In combination with the requirement of the velocity field to be divergence-free, an elliptic equation to solve for a pressure correction to enforce the divergence-free velocity field on the discrete level is derived. The pressure correction equation established is shown to be equivalent to classical methods for incompressible flows. In order to allow the computation of flows at all speeds, a blending technique for the transition from the incompressible, pressure based formulation to the compressible, density based formulation is established. It is found necessary to use preconditioning with this blending technique to account for a remaining 'compressible' contribution in the incompressible limit, and a suitable matrix directly applicable to conservative residuals is derived. Thus, a coherent framework is established to cover the discretization of both incompressible and compressible flows. Compared with standard preconditioning techniques, the blended pressure/density based approach showed improved robustness for high lift flows close to separation

Geothermally Coupled Well-Based Compressed Air Energy Storage

Energy Technology Data Exchange (ETDEWEB)

Davidson, C L [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bearden, Mark D [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Horner, Jacob A [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Appriou, Delphine [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McGrail, B Peter [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-12-01

. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

Geothermally Coupled Well-Based Compressed Air Energy Storage

Energy Technology Data Exchange (ETDEWEB)

Davidson, Casie L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bearden, Mark D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Horner, Jacob A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Cabe, James E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Appriou, Delphine [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); McGrail, B. Peter [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-12-20

. This project assessed the technical and economic feasibility of implementing geothermally coupled well-based CAES for grid-scale energy storage. Based on an evaluation of design specifications for a range of casing grades common in U.S. oil and gas fields, a 5-MW CAES project could be supported by twenty to twenty-five 5,000-foot, 7-inch wells using lower-grade casing, and as few as eight such wells for higher-end casing grades. Using this information, along with data on geothermal resources, well density, and potential future markets for energy storage systems, The Geysers geothermal field was selected to parameterize a case study to evaluate the potential match between the proven geothermal resource present at The Geysers and the field’s existing well infrastructure. Based on calculated wellbore compressed air mass, the study shows that a single average geothermal production well could provide enough geothermal energy to support a 15.4-MW (gross) power generation facility using 34 to 35 geothermal wells repurposed for compressed air storage, resulting in a simplified levelized cost of electricity (sLCOE) estimated at 11.2 ¢/kWh (Table S.1). Accounting for the power loss to the geothermal power project associated with diverting geothermal resources for air heating results in a net 2-MW decrease in generation capacity, increasing the CAES project’s sLCOE by 1.8 ¢/kWh.

Chloride transport under compressive load in bacteria-based self-healing concrete

NARCIS (Netherlands)

Binti Md Yunus, B.; Schlangen, E.; Jonkers, H.M.

2015-01-01

An experiment was carried out in this study to investigate the effect of compressive load on chloride penetration in self-healing concrete containing bacterial-based healing agent. Bacteria-based healing agent with the fraction of 2 mm – 4 mm of particles sizes were used in this contribution. ESEM

Compressive strength of different brands of cement (OPC) in province of Sindh

International Nuclear Information System (INIS)

Khaskheli, G.B.; Kumar, A.; Sheikh, A.

2009-01-01

OPC (Ordinary Portland Cement) is the most common type of cement used in construction industry. Three major brands of OPC are normal OPC, SRC (Sulphate Resisting Cement) and SC (Slag Cement). It is seen that the variation in constituents of cement may cause serious effects on the quality of cement. Thus the motivation of this research is to study the basic properties (consistency, setting time, and fineness), compressive strength (cement mortar and concrete cubes) and modulus of elasticity of all the OPC brands (OPC, SRC and SC) manufactured in Sindh. In total 10 cement factories, altogether 21 different brands of cement, were studied in the light of BS and ASTM Code specifications. In total 126 mortar cubes (1:3), 252 concrete cubes (126 for 3000 psi mix design and remaining for 5000 psi) and 126 concrete cylinders (6 for the each brand of cement pertaining to 3000 psi and 5000 psi mix design) were manufactured and tested. Experimental results demonstrated that all the cement brands fulfilled the BS and ASTM Code requirements for (i) basic properties (ii) compressive strength of mortar cubes at 3 and 28 days curing age (iii) compressive strength of concrete cubes at 28 days curing age, and (iv) modulus of elasticity. Some of the cements did not fulfill the BS and ASTM Code requirements for compressive strength of concrete cubes at 7 days curing age. (author)

Mesh-based parallel code coupling interface

Energy Technology Data Exchange (ETDEWEB)

Wolf, K.; Steckel, B. (eds.) [GMD - Forschungszentrum Informationstechnik GmbH, St. Augustin (DE). Inst. fuer Algorithmen und Wissenschaftliches Rechnen (SCAI)

2001-04-01

MpCCI (mesh-based parallel code coupling interface) is an interface for multidisciplinary simulations. It provides industrial end-users as well as commercial code-owners with the facility to combine different simulation tools in one environment. Thereby new solutions for multidisciplinary problems will be created. This opens new application dimensions for existent simulation tools. This Book of Abstracts gives a short overview about ongoing activities in industry and research - all presented at the 2{sup nd} MpCCI User Forum in February 2001 at GMD Sankt Augustin. (orig.) [German] MpCCI (mesh-based parallel code coupling interface) definiert eine Schnittstelle fuer multidisziplinaere Simulationsanwendungen. Sowohl industriellen Anwender als auch kommerziellen Softwarehersteller wird mit MpCCI die Moeglichkeit gegeben, Simulationswerkzeuge unterschiedlicher Disziplinen miteinander zu koppeln. Dadurch entstehen neue Loesungen fuer multidisziplinaere Problemstellungen und fuer etablierte Simulationswerkzeuge ergeben sich neue Anwendungsfelder. Dieses Book of Abstracts bietet einen Ueberblick ueber zur Zeit laufende Arbeiten in der Industrie und in der Forschung, praesentiert auf dem 2{sup nd} MpCCI User Forum im Februar 2001 an der GMD Sankt Augustin. (orig.)

Information preserving coding for multispectral data

Science.gov (United States)

Duan, J. R.; Wintz, P. A.

1973-01-01

A general formulation of the data compression system is presented. A method of instantaneous expansion of quantization levels by reserving two codewords in the codebook to perform a folding over in quantization is implemented for error free coding of data with incomplete knowledge of the probability density function. Results for simple DPCM with folding and an adaptive transform coding technique followed by a DPCM technique are compared using ERTS-1 data.

A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map

International Nuclear Information System (INIS)

Xiao Di; Cai Hong-Kun; Zheng Hong-Ying

2015-01-01

In this paper, a compressive sensing (CS) and chaotic map-based joint image encryption and watermarking algorithm is proposed. The transform domain coefficients of the original image are scrambled by Arnold map firstly. Then the watermark is adhered to the scrambled data. By compressive sensing, a set of watermarked measurements is obtained as the watermarked cipher image. In this algorithm, watermark embedding and data compression can be performed without knowing the original image; similarly, watermark extraction will not interfere with decryption. Due to the characteristics of CS, this algorithm features compressible cipher image size, flexible watermark capacity, and lossless watermark extraction from the compressed cipher image as well as robustness against packet loss. Simulation results and analyses show that the algorithm achieves good performance in the sense of security, watermark capacity, extraction accuracy, reconstruction, robustness, etc. (paper)

Hardware-efficient bosonic quantum error-correcting codes based on symmetry operators

Science.gov (United States)

Niu, Murphy Yuezhen; Chuang, Isaac L.; Shapiro, Jeffrey H.

2018-03-01

We establish a symmetry-operator framework for designing quantum error-correcting (QEC) codes based on fundamental properties of the underlying system dynamics. Based on this framework, we propose three hardware-efficient bosonic QEC codes that are suitable for χ(2 )-interaction based quantum computation in multimode Fock bases: the χ(2 ) parity-check code, the χ(2 ) embedded error-correcting code, and the χ(2 ) binomial code. All of these QEC codes detect photon-loss or photon-gain errors by means of photon-number parity measurements, and then correct them via χ(2 ) Hamiltonian evolutions and linear-optics transformations. Our symmetry-operator framework provides a systematic procedure for finding QEC codes that are not stabilizer codes, and it enables convenient extension of a given encoding to higher-dimensional qudit bases. The χ(2 ) binomial code is of special interest because, with m ≤N identified from channel monitoring, it can correct m -photon-loss errors, or m -photon-gain errors, or (m -1 )th -order dephasing errors using logical qudits that are encoded in O (N ) photons. In comparison, other bosonic QEC codes require O (N2) photons to correct the same degree of bosonic errors. Such improved photon efficiency underscores the additional error-correction power that can be provided by channel monitoring. We develop quantum Hamming bounds for photon-loss errors in the code subspaces associated with the χ(2 ) parity-check code and the χ(2 ) embedded error-correcting code, and we prove that these codes saturate their respective bounds. Our χ(2 ) QEC codes exhibit hardware efficiency in that they address the principal error mechanisms and exploit the available physical interactions of the underlying hardware, thus reducing the physical resources required for implementing their encoding, decoding, and error-correction operations, and their universal encoded-basis gate sets.

Edge-based compression of cartoon-like images with homogeneous diffusion

DEFF Research Database (Denmark)

Mainberger, Markus; Bruhn, Andrés; Weickert, Joachim

2011-01-01

Edges provide semantically important image features. In this paper a lossy compression method for cartoon-like images is presented, which is based on edge information. Edges together with some adjacent grey/colour values are extracted and encoded using a classical edge detector, binary compressio...

Development of System Based Code: Case Study of Life-Cycle Margin Evaluation

International Nuclear Information System (INIS)

Tai Asayama; Masaki Morishita; Masanori Tashimo

2006-01-01

For a leap of progress in structural deign of nuclear plant components, The late Professor Emeritus Yasuhide Asada proposed the System Based Code. The key concepts of the System Based Code are; (1) life-cycle margin optimization, (2) expansion of technical options as well as combinations of technical options beyond the current codes and standards, and (3) designing to clearly defined target reliabilities. Those concepts are very new to most of the nuclear power plant designers who are naturally obliged to design to current codes and standards; the application of the concepts of the System Based Code to design will lead to entire change of practices that designers have long been accustomed to. On the other hand, experienced designers are supposed to have expertise that can support and accelerate the development of the System Based Code. Therefore, interfacing with experienced designers is of crucial importance for the development of the System Based Code. The authors conducted a survey on the acceptability of the System Based Code concept. The results were analyzed from the possibility of improving structural design both in terms of reliability and cost effectiveness by the introduction of the System Based Code concept. It was concluded that the System Based Code is beneficial for those purposes. Also described is the expertise elicited from the results of the survey that can be reflected to the development of the System Based Code. (authors)

COSINE software development based on code generation technology

International Nuclear Information System (INIS)

Ren Hao; Mo Wentao; Liu Shuo; Zhao Guang

2013-01-01

The code generation technology can significantly improve the quality and productivity of software development and reduce software development risk. At present, the code generator is usually based on UML model-driven technology, which can not satisfy the development demand of nuclear power calculation software. The feature of scientific computing program was analyzed and the FORTRAN code generator (FCG) based on C# was developed in this paper. FCG can generate module variable definition FORTRAN code automatically according to input metadata. FCG also can generate memory allocation interface for dynamic variables as well as data access interface. FCG was applied to the core and system integrated engine for design and analysis (COSINE) software development. The result shows that FCG can greatly improve the development efficiency of nuclear power calculation software, and reduce the defect rate of software development. (authors)

[Symbol: see text]2 Optimized predictive image coding with [Symbol: see text]∞ bound.

Science.gov (United States)

Chuah, Sceuchin; Dumitrescu, Sorina; Wu, Xiaolin

2013-12-01

In many scientific, medical, and defense applications of image/video compression, an [Symbol: see text]∞ error bound is required. However, pure[Symbol: see text]∞-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, most of the previous [Symbol: see text]∞-based image coding methods suffer from poor rate control. In contrast, the [Symbol: see text]2 error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the ∞ error metric and it offers fine granularity in rate control, but pure [Symbol: see text]2-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as the [Symbol: see text]∞-based methods can. This paper presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics. A common approach of near-lossless image coding is to embed into a DPCM prediction loop a uniform scalar quantizer of residual errors. The said uniform scalar quantizer is replaced, in the proposed new approach, by a set of context-based [Symbol: see text]2-optimized quantizers. The optimization criterion is to minimize a weighted sum of the [Symbol: see text]2 distortion and the entropy while maintaining a strict [Symbol: see text]∞ error bound. The resulting method obtains good rate-distortion performance in both [Symbol: see text]2 and [Symbol: see text]∞ metrics and also increases the rate granularity. Compared with JPEG 2000, the new method not only guarantees lower [Symbol: see text]∞ error for all bit rates, but also it achieves higher PSNR for relatively high bit rates.

Validations and applications of the FEAST code

Energy Technology Data Exchange (ETDEWEB)