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 ...

Statistical conditional sampling for variable-resolution video compression.

Directory of Open Access Journals (Sweden)

Alexander Wong

Full Text Available In this study, we investigate a variable-resolution approach to video compression based on Conditional Random Field and statistical conditional sampling in order to further improve compression rate while maintaining high-quality video. In the proposed approach, representative key-frames within a video shot are identified and stored at full resolution. The remaining frames within the video shot are stored and compressed at a reduced resolution. At the decompression stage, a region-based dictionary is constructed from the key-frames and used to restore the reduced resolution frames to the original resolution via statistical conditional sampling. The sampling approach is based on the conditional probability of the CRF modeling by use of the constructed dictionary. Experimental results show that the proposed variable-resolution approach via statistical conditional sampling has potential for improving compression rates when compared to compressing the video at full resolution, while achieving higher video quality when compared to compressing the video at reduced resolution.

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)

Video on the Internet: An introduction to the digital encoding, compression, and transmission of moving image data.

Science.gov (United States)

Boudier, T; Shotton, D M

1999-01-01

In this paper, we seek to provide an introduction to the fast-moving field of digital video on the Internet, from the viewpoint of the biological microscopist who might wish to store or access videos, for instance in image databases such as the BioImage Database (http://www.bioimage.org). We describe and evaluate the principal methods used for encoding and compressing moving image data for digital storage and transmission over the Internet, which involve compromises between compression efficiency and retention of image fidelity, and describe the existing alternate software technologies for downloading or streaming compressed digitized videos using a Web browser. We report the results of experiments on video microscopy recordings and three-dimensional confocal animations of biological specimens to evaluate the compression efficiencies of the principal video compression-decompression algorithms (codecs) and to document the artefacts associated with each of them. Because MPEG-1 gives very high compression while yet retaining reasonable image quality, these studies lead us to recommend that video databases should store both a high-resolution original version of each video, ideally either uncompressed or losslessly compressed, and a separate edited and highly compressed MPEG-1 preview version that can be rapidly downloaded for interactive viewing by the database user. Copyright 1999 Academic Press.

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.

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

Science.gov (United States)

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

2001-12-01

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

Compressive Video Recovery Using Block Match Multi-Frame Motion Estimation Based on Single Pixel Cameras

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Sheng Bi

2016-03-01

Full Text Available Compressive sensing (CS theory has opened up new paths for the development of signal processing applications. Based on this theory, a novel single pixel camera architecture has been introduced to overcome the current limitations and challenges of traditional focal plane arrays. However, video quality based on this method is limited by existing acquisition and recovery methods, and the method also suffers from being time-consuming. In this paper, a multi-frame motion estimation algorithm is proposed in CS video to enhance the video quality. The proposed algorithm uses multiple frames to implement motion estimation. Experimental results show that using multi-frame motion estimation can improve the quality of recovered videos. To further reduce the motion estimation time, a block match algorithm is used to process motion estimation. Experiments demonstrate that using the block match algorithm can reduce motion estimation time by 30%.

Error Resilient Video Compression Using Behavior Models

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Jacco R. Taal

2004-03-01

Full Text Available Wireless and Internet video applications are inherently subjected to bit errors and packet errors, respectively. This is especially so if constraints on the end-to-end compression and transmission latencies are imposed. Therefore, it is necessary to develop methods to optimize the video compression parameters and the rate allocation of these applications that take into account residual channel bit errors. In this paper, we study the behavior of a predictive (interframe video encoder and model the encoders behavior using only the statistics of the original input data and of the underlying channel prone to bit errors. The resulting data-driven behavior models are then used to carry out group-of-pictures partitioning and to control the rate of the video encoder in such a way that the overall quality of the decoded video with compression and channel errors is optimized.

Optimal erasure protection for scalably compressed video streams with limited retransmission.

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Taubman, David; Thie, Johnson

2005-08-01

This paper shows how the priority encoding transmission (PET) framework may be leveraged to exploit both unequal error protection and limited retransmission for RD-optimized delivery of streaming media. Previous work on scalable media protection with PET has largely ignored the possibility of retransmission. Conversely, the PET framework has not been harnessed by the substantial body of previous work on RD optimized hybrid forward error correction/automatic repeat request schemes. We limit our attention to sources which can be modeled as independently compressed frames (e.g., video frames), where each element in the scalable representation of each frame can be transmitted in one or both of two transmission slots. An optimization algorithm determines the level of protection which should be assigned to each element in each slot, subject to transmission bandwidth constraints. To balance the protection assigned to elements which are being transmitted for the first time with those which are being retransmitted, the proposed algorithm formulates a collection of hypotheses concerning its own behavior in future transmission slots. We show how the PET framework allows for a decoupled optimization algorithm with only modest complexity. Experimental results obtained with Motion JPEG2000 compressed video demonstrate that substantial performance benefits can be obtained using the proposed framework.

An improvement analysis on video compression using file segmentation

Science.gov (United States)

Sharma, Shubhankar; Singh, K. John; Priya, M.

2017-11-01

From the past two decades the extreme evolution of the Internet has lead a massive rise in video technology and significantly video consumption over the Internet which inhabits the bulk of data traffic in general. Clearly, video consumes that so much data size on the World Wide Web, to reduce the burden on the Internet and deduction of bandwidth consume by video so that the user can easily access the video data.For this, many video codecs are developed such as HEVC/H.265 and V9. Although after seeing codec like this one gets a dilemma of which would be improved technology in the manner of rate distortion and the coding standard.This paper gives a solution about the difficulty for getting low delay in video compression and video application e.g. ad-hoc video conferencing/streaming or observation by surveillance. Also this paper describes the benchmark of HEVC and V9 technique of video compression on subjective oral estimations of High Definition video content, playback on web browsers. Moreover, this gives the experimental ideology of dividing the video file into several segments for compression and putting back together to improve the efficiency of video compression on the web as well as on the offline mode.

Digital cinema video compression

Science.gov (United States)

Husak, Walter

2003-05-01

The Motion Picture Industry began a transition from film based distribution and projection to digital distribution and projection several years ago. Digital delivery and presentation offers the prospect to increase the quality of the theatrical experience for the audience, reduce distribution costs to the distributors, and create new business opportunities for the theater owners and the studios. Digital Cinema also presents an opportunity to provide increased flexibility and security of the movies for the content owners and the theater operators. Distribution of content via electronic means to theaters is unlike any of the traditional applications for video compression. The transition from film-based media to electronic media represents a paradigm shift in video compression techniques and applications that will be discussed in this paper.

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

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Lerouge Sam

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4 .

Lightweight Object Tracking in Compressed Video Streams Demonstrated in Region-of-Interest Coding

Directory of Open Access Journals (Sweden)

Rik Van de Walle

2007-01-01

Full Text Available Video scalability is a recent video coding technology that allows content providers to offer multiple quality versions from a single encoded video file in order to target different kinds of end-user devices and networks. One form of scalability utilizes the region-of-interest concept, that is, the possibility to mark objects or zones within the video as more important than the surrounding area. The scalable video coder ensures that these regions-of-interest are received by an end-user device before the surrounding area and preferably in higher quality. In this paper, novel algorithms are presented making it possible to automatically track the marked objects in the regions of interest. Our methods detect the overall motion of a designated object by retrieving the motion vectors calculated during the motion estimation step of the video encoder. Using this knowledge, the region-of-interest is translated, thus following the objects within. Furthermore, the proposed algorithms allow adequate resizing of the region-of-interest. By using the available information from the video encoder, object tracking can be done in the compressed domain and is suitable for real-time and streaming applications. A time-complexity analysis is given for the algorithms proving the low complexity thereof and the usability for real-time applications. The proposed object tracking methods are generic and can be applied to any codec that calculates the motion vector field. In this paper, the algorithms are implemented within MPEG-4 fine-granularity scalability codec. Different tests on different video sequences are performed to evaluate the accuracy of the methods. Our novel algorithms achieve a precision up to 96.4%.

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

Science.gov (United States)

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

2015-05-01

possible reducing of the digital stream. Discrete cosine transformation is most widely used among possible orthogonal transformation. Errors of television measuring systems and data compression protocols analyzed In this paper. The main characteristics of measuring systems and detected sources of their error detected. The most effective methods of video compression are determined. The influence of video compression error on television measuring systems was researched. Obtained results will increase the accuracy of the measuring systems. In television image quality measuring system reduces distortion identical distortion in analog systems and specific distortions resulting from the process of coding / decoding digital video signal and errors in the transmission channel. By the distortions associated with encoding / decoding signal include quantization noise, reducing resolution, mosaic effect, "mosquito" effect edging on sharp drops brightness, blur colors, false patterns, the effect of "dirty window" and other defects. The size of video compression algorithms used in television measuring systems based on the image encoding with intra- and inter prediction individual fragments. The process of encoding / decoding image is non-linear in space and in time, because the quality of the playback of a movie at the reception depends on the pre- and post-history of a random, from the preceding and succeeding tracks, which can lead to distortion of the inadequacy of the sub-picture and a corresponding measuring signal.

A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video

Directory of Open Access Journals (Sweden)

Zhang Liangpei

2007-01-01

Full Text Available Super-resolution (SR reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the total variation (TV regularization is employed in the reconstruction model. We use the fixed-point iteration method and preconditioning techniques to efficiently solve the associated nonlinear Euler-Lagrange equations of the corresponding variational problem in SR. The proposed algorithm has been tested in several cases of motion and degradation. It is also compared with the Laplacian regularization-based SR algorithm and other TV-based SR algorithms. Experimental results are presented to illustrate the effectiveness of the proposed algorithm.

Real-time video compressing under DSP/BIOS

Science.gov (United States)

Chen, Qiu-ping; Li, Gui-ju

2009-10-01

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

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....

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.

WSNs Microseismic Signal Subsection Compression Algorithm Based on Compressed Sensing

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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.

A novel pulse compression algorithm for frequency modulated active thermography using band-pass filter

Science.gov (United States)

Chatterjee, Krishnendu; Roy, Deboshree; Tuli, Suneet

2017-05-01

This paper proposes a novel pulse compression algorithm, in the context of frequency modulated thermal wave imaging. The compression filter is derived from a predefined reference pixel in a recorded video, which contains direct measurement of the excitation signal alongside the thermal image of a test piece. The filter causes all the phases of the constituent frequencies to be adjusted to nearly zero value, so that on reconstruction a pulse is obtained. Further, due to band-limited nature of the excitation, signal-to-noise ratio is improved by suppressing out-of-band noise. The result is similar to that of a pulsed thermography experiment, although the peak power is drastically reduced. The algorithm is successfully demonstrated on mild steel and carbon fibre reference samples. Objective comparisons of the proposed pulse compression algorithm with the existing techniques are presented.

Low-latency video transmission over high-speed WPANs based on low-power video compression

DEFF Research Database (Denmark)

Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Ann

2010-01-01

This paper presents latency-constrained video transmission over high-speed wireless personal area networks (WPANs). Low-power video compression is proposed as an alternative to uncompressed video transmission. A video source rate control based on MINMAX quality criteria is introduced. Practical...

A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

Science.gov (United States)

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

2015-09-01

Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

A hardware-oriented concurrent TZ search algorithm for High-Efficiency Video Coding

Science.gov (United States)

Doan, Nghia; Kim, Tae Sung; Rhee, Chae Eun; Lee, Hyuk-Jae

2017-12-01

High-Efficiency Video Coding (HEVC) is the latest video coding standard, in which the compression performance is double that of its predecessor, the H.264/AVC standard, while the video quality remains unchanged. In HEVC, the test zone (TZ) search algorithm is widely used for integer motion estimation because it effectively searches the good-quality motion vector with a relatively small amount of computation. However, the complex computation structure of the TZ search algorithm makes it difficult to implement it in the hardware. This paper proposes a new integer motion estimation algorithm which is designed for hardware execution by modifying the conventional TZ search to allow parallel motion estimations of all prediction unit (PU) partitions. The algorithm consists of the three phases of zonal, raster, and refinement searches. At the beginning of each phase, the algorithm obtains the search points required by the original TZ search for all PU partitions in a coding unit (CU). Then, all redundant search points are removed prior to the estimation of the motion costs, and the best search points are then selected for all PUs. Compared to the conventional TZ search algorithm, experimental results show that the proposed algorithm significantly decreases the Bjøntegaard Delta bitrate (BD-BR) by 0.84%, and it also reduces the computational complexity by 54.54%.

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

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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

H.264/AVC Video Compression on Smartphones

Science.gov (United States)

Sharabayko, M. P.; Markov, N. G.

2017-01-01

In this paper, we studied the usage of H.264/AVC video compression tools by the flagship smartphones. The results show that only a subset of tools is used, meaning that there is still a potential to achieve higher compression efficiency within the H.264/AVC standard, but the most advanced smartphones are already reaching the compression efficiency limit of H.264/AVC.

Rate-distortion optimization for compressive video sampling

Science.gov (United States)

Liu, Ying; Vijayanagar, Krishna R.; Kim, Joohee

2014-05-01

The recently introduced compressed sensing (CS) framework enables low complexity video acquisition via sub- Nyquist rate sampling. In practice, the resulting CS samples are quantized and indexed by finitely many bits (bit-depth) for transmission. In applications where the bit-budget for video transmission is constrained, rate- distortion optimization (RDO) is essential for quality video reconstruction. In this work, we develop a double-level RDO scheme for compressive video sampling, where frame-level RDO is performed by adaptively allocating the fixed bit-budget per frame to each video block based on block-sparsity, and block-level RDO is performed by modelling the block reconstruction peak-signal-to-noise ratio (PSNR) as a quadratic function of quantization bit-depth. The optimal bit-depth and the number of CS samples are then obtained by setting the first derivative of the function to zero. In the experimental studies the model parameters are initialized with a small set of training data, which are then updated with local information in the model testing stage. Simulation results presented herein show that the proposed double-level RDO significantly enhances the reconstruction quality for a bit-budget constrained CS video transmission system.

Motion estimation for video coding efficient algorithms and architectures

CERN Document Server

Chakrabarti, Indrajit; Chatterjee, Sumit Kumar

2015-01-01

The need of video compression in the modern age of visual communication cannot be over-emphasized. This monograph will provide useful information to the postgraduate students and researchers who wish to work in the domain of VLSI design for video processing applications. In this book, one can find an in-depth discussion of several motion estimation algorithms and their VLSI implementation as conceived and developed by the authors. It records an account of research done involving fast three step search, successive elimination, one-bit transformation and its effective combination with diamond search and dynamic pixel truncation techniques. Two appendices provide a number of instances of proof of concept through Matlab and Verilog program segments. In this aspect, the book can be considered as first of its kind. The architectures have been developed with an eye to their applicability in everyday low-power handheld appliances including video camcorders and smartphones.

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.

Optimisation algorithms for ECG data compression.

Science.gov (United States)

Haugland, D; Heber, J G; Husøy, J H

1997-07-01

The use of exact optimisation algorithms for compressing digital electrocardiograms (ECGs) is demonstrated. As opposed to traditional time-domain methods, which use heuristics to select a small subset of representative signal samples, the problem of selecting the subset is formulated in rigorous mathematical terms. This approach makes it possible to derive algorithms guaranteeing the smallest possible reconstruction error when a bounded selection of signal samples is interpolated. The proposed model resembles well-known network models and is solved by a cubic dynamic programming algorithm. When applied to standard test problems, the algorithm produces a compressed representation for which the distortion is about one-half of that obtained by traditional time-domain compression techniques at reasonable compression ratios. This illustrates that, in terms of the accuracy of decoded signals, existing time-domain heuristics for ECG compression may be far from what is theoretically achievable. The paper is an attempt to bridge this gap.

ERGC: an efficient referential genome compression algorithm.

Science.gov (United States)

Saha, Subrata; Rajasekaran, Sanguthevar

2015-11-01

Genome sequencing has become faster and more affordable. Consequently, the number of available complete genomic sequences is increasing rapidly. As a result, the cost to store, process, analyze and transmit the data is becoming a bottleneck for research and future medical applications. So, the need for devising efficient data compression and data reduction techniques for biological sequencing data is growing by the day. Although there exists a number of standard data compression algorithms, they are not efficient in compressing biological data. These generic algorithms do not exploit some inherent properties of the sequencing data while compressing. To exploit statistical and information-theoretic properties of genomic sequences, we need specialized compression algorithms. Five different next-generation sequencing data compression problems have been identified and studied in the literature. We propose a novel algorithm for one of these problems known as reference-based genome compression. We have done extensive experiments using five real sequencing datasets. The results on real genomes show that our proposed algorithm is indeed competitive and performs better than the best known algorithms for this problem. It achieves compression ratios that are better than those of the currently best performing algorithms. The time to compress and decompress the whole genome is also very promising. The implementations are freely available for non-commercial purposes. They can be downloaded from http://engr.uconn.edu/∼rajasek/ERGC.zip. rajasek@engr.uconn.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Low-complexity JPEG-based progressive video codec for wireless video transmission

DEFF Research Database (Denmark)

Ukhanova, Ann; Forchhammer, Søren

2010-01-01

This paper discusses the question of video codec enhancement for wireless video transmission of high definition video data taking into account constraints on memory and complexity. Starting from parameter adjustment for JPEG2000 compression algorithm used for wireless transmission and achieving...

Algorithm for Compressing Time-Series Data

Science.gov (United States)

Hawkins, S. Edward, III; Darlington, Edward Hugo

2012-01-01

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Selecting a general-purpose data compression algorithm

Science.gov (United States)

Mathews, Gary Jason

1995-01-01

The National Space Science Data Center's Common Data Formate (CDF) is capable of storing many types of data such as scalar data items, vectors, and multidimensional arrays of bytes, integers, or floating point values. However, regardless of the dimensionality and data type, the data break down into a sequence of bytes that can be fed into a data compression function to reduce the amount of data without losing data integrity and thus remaining fully reconstructible. Because of the diversity of data types and high performance speed requirements, a general-purpose, fast, simple data compression algorithm is required to incorporate data compression into CDF. The questions to ask are how to evaluate and compare compression algorithms, and what compression algorithm meets all requirements. The object of this paper is to address these questions and determine the most appropriate compression algorithm to use within the CDF data management package that would be applicable to other software packages with similar data compression needs.

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.

High efficiency video coding (HEVC) algorithms and architectures

CERN Document Server

Budagavi, Madhukar; Sullivan, Gary

2014-01-01

This book provides developers, engineers, researchers and students with detailed knowledge about the High Efficiency Video Coding (HEVC) standard. HEVC is the successor to the widely successful H.264/AVC video compression standard, and it provides around twice as much compression as H.264/AVC for the same level of quality. The applications for HEVC will not only cover the space of the well-known current uses and capabilities of digital video – they will also include the deployment of new services and the delivery of enhanced video quality, such as ultra-high-definition television (UHDTV) and video with higher dynamic range, wider range of representable color, and greater representation precision than what is typically found today. HEVC is the next major generation of video coding design – a flexible, reliable and robust solution that will support the next decade of video applications and ease the burden of video on world-wide network traffic. This book provides a detailed explanation of the various parts ...

Quality Assessment of Compressed Video for Automatic License Plate Recognition

DEFF Research Database (Denmark)

Ukhanova, Ann; Støttrup-Andersen, Jesper; Forchhammer, Søren

2014-01-01

Definition of video quality requirements for video surveillance poses new questions in the area of quality assessment. This paper presents a quality assessment experiment for an automatic license plate recognition scenario. We explore the influence of the compression by H.264/AVC and H.265/HEVC s...... recognition in our study has a behavior similar to human recognition, allowing the use of the same mathematical models. We furthermore propose an application of one of the models for video surveillance systems......Definition of video quality requirements for video surveillance poses new questions in the area of quality assessment. This paper presents a quality assessment experiment for an automatic license plate recognition scenario. We explore the influence of the compression by H.264/AVC and H.265/HEVC...... standards on the recognition performance. We compare logarithmic and logistic functions for quality modeling. Our results show that a logistic function can better describe the dependence of recognition performance on the quality for both compression standards. We observe that automatic license plate...

An Efficient Fractal Video Sequences Codec with Multiviews

Directory of Open Access Journals (Sweden)

Shiping Zhu

2013-01-01

Full Text Available Multiview video consists of multiple views of the same scene. They require enormous amount of data to achieve high image quality, which makes it indispensable to compress multiview video. Therefore, data compression is a major issue for multiviews. In this paper, we explore an efficient fractal video codec to compress multiviews. The proposed scheme first compresses a view-dependent geometry of the base view using fractal video encoder with homogeneous region condition. With the extended fractional pel motion estimation algorithm and fast disparity estimation algorithm, it then generates prediction images of other views. The prediction image uses the image-based rendering techniques based on the decoded video. And the residual signals are obtained by the prediction image and the original image. Finally, it encodes residual signals by the fractal video encoder. The idea is also to exploit the statistical dependencies from both temporal and interview reference pictures for motion compensated prediction. Experimental results show that the proposed algorithm is consistently better than JMVC8.5, with 62.25% bit rate decrease and 0.37 dB PSNR increase based on the Bjontegaard metric, and the total encoding time (TET of the proposed algorithm is reduced by 92%.

NRGC: a novel referential genome compression algorithm.

Science.gov (United States)

Saha, Subrata; Rajasekaran, Sanguthevar

2016-11-15

Next-generation sequencing techniques produce millions to billions of short reads. The procedure is not only very cost effective but also can be done in laboratory environment. The state-of-the-art sequence assemblers then construct the whole genomic sequence from these reads. Current cutting edge computing technology makes it possible to build genomic sequences from the billions of reads within a minimal cost and time. As a consequence, we see an explosion of biological sequences in recent times. In turn, the cost of storing the sequences in physical memory or transmitting them over the internet is becoming a major bottleneck for research and future medical applications. Data compression techniques are one of the most important remedies in this context. We are in need of suitable data compression algorithms that can exploit the inherent structure of biological sequences. Although standard data compression algorithms are prevalent, they are not suitable to compress biological sequencing data effectively. In this article, we propose a novel referential genome compression algorithm (NRGC) to effectively and efficiently compress the genomic sequences. We have done rigorous experiments to evaluate NRGC by taking a set of real human genomes. The simulation results show that our algorithm is indeed an effective genome compression algorithm that performs better than the best-known algorithms in most of the cases. Compression and decompression times are also very impressive. The implementations are freely available for non-commercial purposes. They can be downloaded from: http://www.engr.uconn.edu/~rajasek/NRGC.zip CONTACT: rajasek@engr.uconn.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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...

A Novel High Efficiency Fractal Multiview Video Codec

Directory of Open Access Journals (Sweden)

Shiping Zhu

2015-01-01

Full Text Available Multiview video which is one of the main types of three-dimensional (3D video signals, captured by a set of video cameras from various viewpoints, has attracted much interest recently. Data compression for multiview video has become a major issue. In this paper, a novel high efficiency fractal multiview video codec is proposed. Firstly, intraframe algorithm based on the H.264/AVC intraprediction modes and combining fractal and motion compensation (CFMC algorithm in which range blocks are predicted by domain blocks in the previously decoded frame using translational motion with gray value transformation is proposed for compressing the anchor viewpoint video. Then temporal-spatial prediction structure and fast disparity estimation algorithm exploiting parallax distribution constraints are designed to compress the multiview video data. The proposed fractal multiview video codec can exploit temporal and spatial correlations adequately. Experimental results show that it can obtain about 0.36 dB increase in the decoding quality and 36.21% decrease in encoding bitrate compared with JMVC8.5, and the encoding time is saved by 95.71%. The rate-distortion comparisons with other multiview video coding methods also demonstrate the superiority of the proposed scheme.

PERFORMANCE ANALYSIS OF SET PARTITIONING IN HIERARCHICAL TREES (SPIHT ALGORITHM FOR A FAMILY OF WAVELETS USED IN COLOR IMAGE COMPRESSION

Directory of Open Access Journals (Sweden)

A. Sreenivasa Murthy

2014-11-01

Full Text Available With the spurt in the amount of data (Image, video, audio, speech, & text available on the net, there is a huge demand for memory & bandwidth savings. One has to achieve this, by maintaining the quality & fidelity of the data acceptable to the end user. Wavelet transform is an important and practical tool for data compression. Set partitioning in hierarchal trees (SPIHT is a widely used compression algorithm for wavelet transformed images. Among all wavelet transform and zero-tree quantization based image compression algorithms SPIHT has become the benchmark state-of-the-art algorithm because it is simple to implement & yields good results. In this paper we present a comparative study of various wavelet families for image compression with SPIHT algorithm. We have conducted experiments with Daubechies, Coiflet, Symlet, Bi-orthogonal, Reverse Bi-orthogonal and Demeyer wavelet types. The resulting image quality is measured objectively, using peak signal-to-noise ratio (PSNR, and subjectively, using perceived image quality (human visual perception, HVP for short. The resulting reduction in the image size is quantified by compression ratio (CR.

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.

Temporal Segmentation of MPEG Video Streams

Directory of Open Access Journals (Sweden)

Janko Calic

2002-06-01

Full Text Available Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

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,.

Efficient algorithms of multidimensional γ-ray spectra compression

International Nuclear Information System (INIS)

Morhac, M.; Matousek, V.

2006-01-01

The efficient algorithms to compress multidimensional γ-ray events are presented. Two alternative kinds of compression algorithms based on both the adaptive orthogonal and randomizing transforms are proposed. In both algorithms we employ the reduction of data volume due to the symmetry of the γ-ray spectra

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.

Basic prediction techniques in modern video coding standards

CERN Document Server

Kim, Byung-Gyu

2016-01-01

This book discusses in detail the basic algorithms of video compression that are widely used in modern video codec. The authors dissect complicated specifications and present material in a way that gets readers quickly up to speed by describing video compression algorithms succinctly, without going to the mathematical details and technical specifications. For accelerated learning, hybrid codec structure, inter- and intra- prediction techniques in MPEG-4, H.264/AVC, and HEVC are discussed together. In addition, the latest research in the fast encoder design for the HEVC and H.264/AVC is also included.

Continuity-Aware Scheduling Algorithm for Scalable Video Streaming

Directory of Open Access Journals (Sweden)

Atinat Palawan

2016-05-01

Full Text Available The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter. This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR.

Content-based video retrieval by example video clip

Science.gov (United States)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Passive ultra-brief video training improves performance of compression-only cardiopulmonary resuscitation.

Science.gov (United States)

Benoit, Justin L; Vogele, Jennifer; Hart, Kimberly W; Lindsell, Christopher J; McMullan, Jason T

2017-06-01

Bystander compression-only cardiopulmonary resuscitation (CPR) improves survival after out-of-hospital cardiac arrest. To broaden CPR training, 1-2min ultra-brief videos have been disseminated via the Internet and television. Our objective was to determine whether participants passively exposed to a televised ultra-brief video perform CPR better than unexposed controls. This before-and-after study was conducted with non-patients in an urban Emergency Department waiting room. The intervention was an ultra-brief CPR training video displayed via closed-circuit television 3-6 times/hour. Participants were unaware of the study and not told to watch the video. Pre-intervention, no video was displayed. Participants were asked to demonstrate compression-only CPR on a manikin. Performance was scored based on critical actions: check for responsiveness, call for help, begin compressions immediately, and correct hand placement, compression rate and depth. The primary outcome was the proportion of participants who performed all actions correctly. There were 50 control and 50 exposed participants. Mean age was 37, 51% were African-American, 52% were female, and 10% self-reported current CPR certification. There were no statistically significant differences in baseline characteristics between groups. The number of participants who performed all actions correctly was 0 (0%) control vs. 10 (20%) exposed (difference 20%, 95% confidence interval [CI] 8.9-31.1%, ptraining is associated with improved performance of compression-only CPR. Copyright © 2017 Elsevier B.V. All rights reserved.

Fundamental study of compression for movie files of coronary angiography

Science.gov (United States)

Ando, Takekazu; Tsuchiya, Yuichiro; Kodera, Yoshie

2005-04-01

When network distribution of movie files was considered as reference, it could be useful that the lossy compression movie files which has small file size. We chouse three kinds of coronary stricture movies with different moving speed as an examination object; heart rate of slow, normal and fast movies. The movies of MPEG-1, DivX5.11, WMV9 (Windows Media Video 9), and WMV9-VCM (Windows Media Video 9-Video Compression Manager) were made from three kinds of AVI format movies with different moving speeds. Five kinds of movies that are four kinds of compression movies and non-compression AVI instead of the DICOM format were evaluated by Thurstone's method. The Evaluation factors of movies were determined as "sharpness, granularity, contrast, and comprehensive evaluation." In the virtual bradycardia movie, AVI was the best evaluation at all evaluation factors except the granularity. In the virtual normal movie, an excellent compression technique is different in all evaluation factors. In the virtual tachycardia movie, MPEG-1 was the best evaluation at all evaluation factors expects the contrast. There is a good compression form depending on the speed of movies because of the difference of compression algorithm. It is thought that it is an influence by the difference of the compression between frames. The compression algorithm for movie has the compression between the frames and the intra-frame compression. As the compression algorithm give the different influence to image by each compression method, it is necessary to examine the relation of the compression algorithm and our results.

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Yin Wang

2015-12-01

Full Text Available There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for the next hop with the highest potential bandwidth capacity to resume communication. Key to this strategy is that each node merely maintains two parameters that contain its historical bandwidth varying trend and then predict its near future bandwidth capacity. Then, the forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by the sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environments.

High-Performance Motion Estimation for Image Sensors with Video Compression

Directory of Open Access Journals (Sweden)

Weizhi Xu

2015-08-01

Full Text Available It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve the time efficiency but neglected inter-frame data reuse. We propose a novel inter-frame data reuse scheme which can exploit both intra-frame and inter-frame data reuse for ME in video compression (VC-ME. Pixels of reconstructed frames are kept on-chip until they are used by the next current frame to avoid off-chip memory access. On-chip buffers with smart schedules of data access are designed to perform the new data reuse scheme. Three levels of the proposed inter-frame data reuse scheme are presented and analyzed. They give different choices with tradeoff between off-chip bandwidth requirement and on-chip memory size. All three levels have better data reuse efficiency than their intra-frame counterparts, so off-chip memory traffic is reduced effectively. Comparing the new inter-frame data reuse scheme with the traditional intra-frame data reuse scheme, the memory traffic can be reduced by 50% for VC-ME.

Video steganography based on bit-plane decomposition of wavelet-transformed video

Science.gov (United States)

Noda, Hideki; Furuta, Tomofumi; Niimi, Michiharu; Kawaguchi, Eiji

2004-06-01

This paper presents a steganography method using lossy compressed video which provides a natural way to send a large amount of secret data. The proposed method is based on wavelet compression for video data and bit-plane complexity segmentation (BPCS) steganography. BPCS steganography makes use of bit-plane decomposition and the characteristics of the human vision system, where noise-like regions in bit-planes of a dummy image are replaced with secret data without deteriorating image quality. In wavelet-based video compression methods such as 3-D set partitioning in hierarchical trees (SPIHT) algorithm and Motion-JPEG2000, wavelet coefficients in discrete wavelet transformed video are quantized into a bit-plane structure and therefore BPCS steganography can be applied in the wavelet domain. 3-D SPIHT-BPCS steganography and Motion-JPEG2000-BPCS steganography are presented and tested, which are the integration of 3-D SPIHT video coding and BPCS steganography, and that of Motion-JPEG2000 and BPCS, respectively. Experimental results show that 3-D SPIHT-BPCS is superior to Motion-JPEG2000-BPCS with regard to embedding performance. In 3-D SPIHT-BPCS steganography, embedding rates of around 28% of the compressed video size are achieved for twelve bit representation of wavelet coefficients with no noticeable degradation in video quality.

Spatial compression algorithm for the analysis of very large multivariate images

Science.gov (United States)

Keenan, Michael R [Albuquerque, NM

2008-07-15

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

Evaluation of Algorithms for Compressing Hyperspectral Data

Science.gov (United States)

Cook, Sid; Harsanyi, Joseph; Faber, Vance

2003-01-01

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

BIND – An algorithm for loss-less compression of nucleotide ...

Indian Academy of Sciences (India)

constituting the FNA data set. Supplementary table 2. Original and compressed file sizes (obtained using various compression algorithms) for 2679 files constituting the FFN data set. Supplementary table 3. Original and compressed file sizes (obtained using various compression algorithms) for 25 files constituting the ...

Video segmentation for post-production

Science.gov (United States)

Wills, Ciaran

2001-12-01

Specialist post-production is an industry that has much to gain from the application of content-based video analysis techniques. However the types of material handled in specialist post-production, such as television commercials, pop music videos and special effects are quite different in nature from the typical broadcast material which many video analysis techniques are designed to work with; shots are short and highly dynamic, and the transitions are often novel or ambiguous. We address the problem of scene change detection and develop a new algorithm which tackles some of the common aspects of post-production material that cause difficulties for past algorithms, such as illumination changes and jump cuts. Operating in the compressed domain on Motion JPEG compressed video, our algorithm detects cuts and fades by analyzing each JPEG macroblock in the context of its temporal and spatial neighbors. Analyzing the DCT coefficients directly we can extract the mean color of a block and an approximate detail level. We can also perform an approximated cross-correlation between two blocks. The algorithm is part of a set of tools being developed to work with an automated asset management system designed specifically for use in post-production facilities.

Algorithms and data structures for grammar-compressed strings

DEFF Research Database (Denmark)

Cording, Patrick Hagge

Textual databases for e.g. biological or web-data are growing rapidly, and it is often only feasible to store the data in compressed form. However, compressing the data comes at a price. Traditional algorithms for e.g. pattern matching requires all data to be decompressed - a computationally...... demanding task. In this thesis we design data structures for accessing and searching compressed data efficiently. Our results can be divided into two categories. In the first category we study problems related to pattern matching. In particular, we present new algorithms for counting and comparing...... substrings, and a new algorithm for finding all occurrences of a pattern in which we may insert gaps. In the other category we deal with accessing and decompressing parts of the compressed string. We show how to quickly access a single character of the compressed string, and present a data structure...

Objective video quality measure for application to tele-echocardiography.

Science.gov (United States)

Moore, Peter Thomas; O'Hare, Neil; Walsh, Kevin P; Ward, Neil; Conlon, Niamh

2008-08-01

Real-time tele-echocardiography is widely used to remotely diagnose or exclude congenital heart defects. Cost effective technical implementation is realised using low-bandwidth transmission systems and lossy compression (videoconferencing) schemes. In our study, DICOM video sequences were converted to common multimedia formats, which were then, compressed using three lossy compression algorithms. We then applied a digital (multimedia) video quality metric (VQM) to determine objectively a value for degradation due to compression. Three levels of compression were simulated by varying system bandwidth and compared to a subjective assessment of video clip quality by three paediatric cardiologists with more than 5 years of experience.

Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

Directory of Open Access Journals (Sweden)

Yongjian Nian

2013-01-01

Full Text Available A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.

Algorithms for Fast Computing of the 3D-DCT Transform

Directory of Open Access Journals (Sweden)

S. Hanus

2003-04-01

Full Text Available The algorithm for video compression based on the Three-DimensionalDiscrete Cosine Transform (3D-DCT is presented. The original algorithmof the 3D-DCT has high time complexity. We propose several enhancementsto the original algorithm and make the calculation of the DCT algorithmfeasible for future real-time video compression.

Rate-control algorithms testing by using video source model

DEFF Research Database (Denmark)

Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Anna

2008-01-01

In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set.......In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set....

Discontinuity minimization for omnidirectional video projections

Science.gov (United States)

Alshina, Elena; Zakharchenko, Vladyslav

2017-09-01

Advances in display technologies both for head mounted devices and television panels demand resolution increase beyond 4K for source signal in virtual reality video streaming applications. This poses a problem of content delivery trough a bandwidth limited distribution networks. Considering a fact that source signal covers entire surrounding space investigation reviled that compression efficiency may fluctuate 40% in average depending on origin selection at the conversion stage from 3D space to 2D projection. Based on these knowledge the origin selection algorithm for video compression applications has been proposed. Using discontinuity entropy minimization function projection origin rotation may be defined to provide optimal compression results. Outcome of this research may be applied across various video compression solutions for omnidirectional content.

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

Directory of Open Access Journals (Sweden)

Yu Zheng

2017-06-01

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

LFQC: a lossless compression algorithm for FASTQ files

Science.gov (United States)

Nicolae, Marius; Pathak, Sudipta; Rajasekaran, Sanguthevar

2015-01-01

Motivation: Next Generation Sequencing (NGS) technologies have revolutionized genomic research by reducing the cost of whole genome sequencing. One of the biggest challenges posed by modern sequencing technology is economic storage of NGS data. Storing raw data is infeasible because of its enormous size and high redundancy. In this article, we address the problem of storage and transmission of large FASTQ files using innovative compression techniques. Results: We introduce a new lossless non-reference based FASTQ compression algorithm named Lossless FASTQ Compressor. We have compared our algorithm with other state of the art big data compression algorithms namely gzip, bzip2, fastqz (Bonfield and Mahoney, 2013), fqzcomp (Bonfield and Mahoney, 2013), Quip (Jones et al., 2012), DSRC2 (Roguski and Deorowicz, 2014). This comparison reveals that our algorithm achieves better compression ratios on LS454 and SOLiD datasets. Availability and implementation: The implementations are freely available for non-commercial purposes. They can be downloaded from http://engr.uconn.edu/rajasek/lfqc-v1.1.zip. Contact: rajasek@engr.uconn.edu PMID:26093148

Experimental scheme and restoration algorithm of block compression sensing

Science.gov (United States)

Zhang, Linxia; Zhou, Qun; Ke, Jun

2018-01-01

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

A Super-resolution Reconstruction Algorithm for Surveillance Video

Directory of Open Access Journals (Sweden)

Jian Shao

2017-01-01

Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

SCALCE: boosting sequence compression algorithms using locally consistent encoding.

Science.gov (United States)

Hach, Faraz; Numanagic, Ibrahim; Alkan, Can; Sahinalp, S Cenk

2012-12-01

The high throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges for the computational infrastructure. Data management, storage and analysis have become major logistical obstacles for those adopting the new platforms. The requirement for large investment for this purpose almost signalled the end of the Sequence Read Archive hosted at the National Center for Biotechnology Information (NCBI), which holds most of the sequence data generated world wide. Currently, most HTS data are compressed through general purpose algorithms such as gzip. These algorithms are not designed for compressing data generated by the HTS platforms; for example, they do not take advantage of the specific nature of genomic sequence data, that is, limited alphabet size and high similarity among reads. Fast and efficient compression algorithms designed specifically for HTS data should be able to address some of the issues in data management, storage and communication. Such algorithms would also help with analysis provided they offer additional capabilities such as random access to any read and indexing for efficient sequence similarity search. Here we present SCALCE, a 'boosting' scheme based on Locally Consistent Parsing technique, which reorganizes the reads in a way that results in a higher compression speed and compression rate, independent of the compression algorithm in use and without using a reference genome. Our tests indicate that SCALCE can improve the compression rate achieved through gzip by a factor of 4.19-when the goal is to compress the reads alone. In fact, on SCALCE reordered reads, gzip running time can improve by a factor of 15.06 on a standard PC with a single core and 6 GB memory. Interestingly even the running time of SCALCE + gzip improves that of gzip alone by a factor of 2.09. When compared with the recently published BEETL, which aims to sort the (inverted) reads in lexicographic order for improving bzip2, SCALCE + gzip

Resolution enhancement of low quality videos using a high-resolution frame

NARCIS (Netherlands)

Pham, T.Q.; Van Vliet, L.J.; Schutte, K.

2006-01-01

This paper proposes an example-based Super-Resolution (SR) algorithm of compressed videos in the Discrete Cosine Transform (DCT) domain. Input to the system is a Low-Resolution (LR) compressed video together with a High-Resolution (HR) still image of similar content. Using a training set of

Fast and predictable video compression in software design and implementation of an H.261 codec

Science.gov (United States)

Geske, Dagmar; Hess, Robert

1998-09-01

The use of software codecs for video compression becomes commonplace in several videoconferencing applications. In order to reduce conflicts with other applications used at the same time, mechanisms for resource reservation on endsystems need to determine an upper bound for computing time used by the codec. This leads to the demand for predictable execution times of compression/decompression. Since compression schemes as H.261 inherently depend on the motion contained in the video, an adaptive admission control is required. This paper presents a data driven approach based on dynamical reduction of the number of processed macroblocks in peak situations. Besides the absolute speed is a point of interest. The question, whether and how software compression of high quality video is feasible on today's desktop computers, is examined.

Focal-plane change triggered video compression for low-power vision sensor systems.

Directory of Open Access Journals (Sweden)

Yu M Chi

Full Text Available Video sensors with embedded compression offer significant energy savings in transmission but incur energy losses in the complexity of the encoder. Energy efficient video compression architectures for CMOS image sensors with focal-plane change detection are presented and analyzed. The compression architectures use pixel-level computational circuits to minimize energy usage by selectively processing only pixels which generate significant temporal intensity changes. Using the temporal intensity change detection to gate the operation of a differential DCT based encoder achieves nearly identical image quality to traditional systems (4dB decrease in PSNR while reducing the amount of data that is processed by 67% and reducing overall power consumption reduction of 51%. These typical energy savings, resulting from the sparsity of motion activity in the visual scene, demonstrate the utility of focal-plane change triggered compression to surveillance vision systems.

Considerations and Algorithms for Compression of Sets

DEFF Research Database (Denmark)

Larsson, Jesper

We consider compression of unordered sets of distinct elements. After a discus- sion of the general problem, we focus on compressing sets of fixed-length bitstrings in the presence of statistical information. We survey techniques from previous work, suggesting some adjustments, and propose a novel...... compression algorithm that allows transparent incorporation of various estimates for probability distribution. Our experimental results allow the conclusion that set compression can benefit from incorporat- ing statistics, using our method or variants of previously known techniques....

Video error concealment using block matching and frequency selective extrapolation algorithms

Science.gov (United States)

P. K., Rajani; Khaparde, Arti

2017-06-01

Error Concealment (EC) is a technique at the decoder side to hide the transmission errors. It is done by analyzing the spatial or temporal information from available video frames. It is very important to recover distorted video because they are used for various applications such as video-telephone, video-conference, TV, DVD, internet video streaming, video games etc .Retransmission-based and resilient-based methods, are also used for error removal. But these methods add delay and redundant data. So error concealment is the best option for error hiding. In this paper, the error concealment methods such as Block Matching error concealment algorithm is compared with Frequency Selective Extrapolation algorithm. Both the works are based on concealment of manually error video frames as input. The parameter used for objective quality measurement was PSNR (Peak Signal to Noise Ratio) and SSIM(Structural Similarity Index). The original video frames along with error video frames are compared with both the Error concealment algorithms. According to simulation results, Frequency Selective Extrapolation is showing better quality measures such as 48% improved PSNR and 94% increased SSIM than Block Matching Algorithm.

Dual-Layer Video Encryption using RSA Algorithm

Science.gov (United States)

Chadha, Aman; Mallik, Sushmit; Chadha, Ankit; Johar, Ravdeep; Mani Roja, M.

2015-04-01

This paper proposes a video encryption algorithm using RSA and Pseudo Noise (PN) sequence, aimed at applications requiring sensitive video information transfers. The system is primarily designed to work with files encoded using the Audio Video Interleaved (AVI) codec, although it can be easily ported for use with Moving Picture Experts Group (MPEG) encoded files. The audio and video components of the source separately undergo two layers of encryption to ensure a reasonable level of security. Encryption of the video component involves applying the RSA algorithm followed by the PN-based encryption. Similarly, the audio component is first encrypted using PN and further subjected to encryption using the Discrete Cosine Transform. Combining these techniques, an efficient system, invulnerable to security breaches and attacks with favorable values of parameters such as encryption/decryption speed, encryption/decryption ratio and visual degradation; has been put forth. For applications requiring encryption of sensitive data wherein stringent security requirements are of prime concern, the system is found to yield negligible similarities in visual perception between the original and the encrypted video sequence. For applications wherein visual similarity is not of major concern, we limit the encryption task to a single level of encryption which is accomplished by using RSA, thereby quickening the encryption process. Although some similarity between the original and encrypted video is observed in this case, it is not enough to comprehend the happenings in the video.

Design considerations for view interpolation in a 3D video coding framework

NARCIS (Netherlands)

Morvan, Y.; Farin, D.S.; With, de P.H.N.; Lagendijk, R.L.; Weber, Jos H.; Berg, van den A.F.M.

2006-01-01

A 3D video stream typically consists of a set of views capturing simultaneously the same scene. For an efficient transmission of the 3D video, a compression technique is required. In this paper, we describe a coding architecture and appropriate algorithms that enable the compression and

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.

Processing Decoded Video for LCD-LED Backlight Display

DEFF Research Database (Denmark)

Nadernejad, Ehsan

The quality of digital images and video signal on visual media such as TV screens and LCD displays is affected by two main factors; the display technology and compression standards. Accurate knowledge about the characteristics of display and the video signal can be utilized to develop advanced...... on local LED-LCD backlight. Second, removing the digital video codec artifacts such as blocking and ringing artifacts by post-processing algorithms. A novel algorithm based on image features with optimal balance between visual quality and power consumption was developed. In addition, to remove flickering...... algorithms for signal (image or video) enhancement. One particular application of such algorithms is the case of LCDs with dynamic local backlight. The thesis addressed two main problems; first, designing algorithms that improve the visual quality of perceived image and video and reduce power consumption...

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

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.

Subjective evaluation of next-generation video compression algorithms: a case study

Science.gov (United States)

De Simone, Francesca; Goldmann, Lutz; Lee, Jong-Seok; Ebrahimi, Touradj; Baroncini, Vittorio

2010-08-01

This paper describes the details and the results of the subjective quality evaluation performed at EPFL, as a contribution to the effort of the Joint Collaborative Team on Video Coding (JCT-VC) for the definition of the next-generation video coding standard. The performance of 27 coding technologies have been evaluated with respect to two H.264/MPEG-4 AVC anchors, considering high definition (HD) test material. The test campaign involved a total of 494 naive observers and took place over a period of four weeks. While similar tests have been conducted as part of the standardization process of previous video coding technologies, the test campaign described in this paper is by far the most extensive in the history of video coding standardization. The obtained subjective quality scores show high consistency and support an accurate comparison of the performance of the different coding solutions.

3D video coding: an overview of present and upcoming standards

Science.gov (United States)

Merkle, Philipp; Müller, Karsten; Wiegand, Thomas

2010-07-01

An overview of existing and upcoming 3D video coding standards is given. Various different 3D video formats are available, each with individual pros and cons. The 3D video formats can be separated into two classes: video-only formats (such as stereo and multiview video) and depth-enhanced formats (such as video plus depth and multiview video plus depth). Since all these formats exist of at least two video sequences and possibly additional depth data, efficient compression is essential for the success of 3D video applications and technologies. For the video-only formats the H.264 family of coding standards already provides efficient and widely established compression algorithms: H.264/AVC simulcast, H.264/AVC stereo SEI message, and H.264/MVC. For the depth-enhanced formats standardized coding algorithms are currently being developed. New and specially adapted coding approaches are necessary, as the depth or disparity information included in these formats has significantly different characteristics than video and is not displayed directly, but used for rendering. Motivated by evolving market needs, MPEG has started an activity to develop a generic 3D video standard within the 3DVC ad-hoc group. Key features of the standard are efficient and flexible compression of depth-enhanced 3D video representations and decoupling of content creation and display requirements.

Data Compression by Shape Compensation for Mobile Video Sensors

Directory of Open Access Journals (Sweden)

Ben-Shung Chow

2009-04-01

Full Text Available Most security systems, with their transmission bandwidth and computing power both being sufficient, emphasize their automatic recognition techniques. However, in some situations such as baby monitors and intruder avoidance by mobile sensors, the decision function sometimes can be shifted to the concerned human to reduce the transmission and computation cost. We therefore propose a binary video compression method in low resolution to achieve a low cost mobile video communication for inexpensive camera sensors. Shape compensation as proposed in this communication successfully replaces the standard Discrete Cosine Transformation (DCT after motion compensation.

Hierarchical video summarization

Science.gov (United States)

Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

1998-12-01

We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

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.

Visual Communications for Heterogeneous Networks/Visually Optimized Scalable Image Compression. Final Report for September 1, 1995 - February 28, 2002

Energy Technology Data Exchange (ETDEWEB)

Hemami, S. S.

2003-06-03

The authors developed image and video compression algorithms that provide scalability, reconstructibility, and network adaptivity, and developed compression and quantization strategies that are visually optimal at all bit rates. The goal of this research is to enable reliable ''universal access'' to visual communications over the National Information Infrastructure (NII). All users, regardless of their individual network connection bandwidths, qualities-of-service, or terminal capabilities, should have the ability to access still images, video clips, and multimedia information services, and to use interactive visual communications services. To do so requires special capabilities for image and video compression algorithms: scalability, reconstructibility, and network adaptivity. Scalability allows an information service to provide visual information at many rates, without requiring additional compression or storage after the stream has been compressed the first time. Reconstructibility allows reliable visual communications over an imperfect network. Network adaptivity permits real-time modification of compression parameters to adjust to changing network conditions. Furthermore, to optimize the efficiency of the compression algorithms, they should be visually optimal, where each bit expended reduces the visual distortion. Visual optimality is achieved through first extensive experimentation to quantify human sensitivity to supra-threshold compression artifacts and then incorporation of these experimental results into quantization strategies and compression algorithms.

Analysing Music with Point-Set Compression Algorithms

DEFF Research Database (Denmark)

Meredith, David

2016-01-01

Several point-set pattern-discovery and compression algorithms designed for analysing music are reviewed and evaluated. Each algorithm takes as input a point-set representation of a score in which each note is represented as a point in pitch-time space. Each algorithm computes the maximal...... and sections in pieces of classical music. On the first task, the best-performing algorithms achieved success rates of around 84%. In the second task, the best algorithms achieved mean F1 scores of around 0.49, with scores for individual pieces rising as high as 0.71....

Detection of Double-Compressed H.264/AVC Video Incorporating the Features of the String of Data Bits and Skip Macroblocks

Directory of Open Access Journals (Sweden)

Heng Yao

2017-12-01

Full Text Available Today’s H.264/AVC coded videos have a high quality, high data-compression ratio. They also have a strong fault tolerance, better network adaptability, and have been widely applied on the Internet. With the popularity of powerful and easy-to-use video editing software, digital videos can be tampered with in various ways. Therefore, the double compression in the H.264/AVC video can be used as a first step in the study of video-tampering forensics. This paper proposes a simple, but effective, double-compression detection method that analyzes the periodic features of the string of data bits (SODBs and the skip macroblocks (S-MBs for all I-frames and P-frames in a double-compressed H.264/AVC video. For a given suspicious video, the SODBs and S-MBs are extracted for each frame. Both features are then incorporated to generate one enhanced feature to represent the periodic artifact of the double-compressed video. Finally, a time-domain analysis is conducted to detect the periodicity of the features. The primary Group of Pictures (GOP size is estimated based on an exhaustive strategy. The experimental results demonstrate the efficacy of the proposed method.

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD) Scheme.

Science.gov (United States)

Idbeaa, Tarik; Abdul Samad, Salina; Husain, Hafizah

2016-01-01

This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD). Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs) of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES) algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values.

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD Scheme.

Directory of Open Access Journals (Sweden)

Tarik Idbeaa

Full Text Available This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD. Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values.

Brief compression-only cardiopulmonary resuscitation training video and simulation with homemade mannequin improves CPR skills.

Science.gov (United States)

Wanner, Gregory K; Osborne, Arayel; Greene, Charlotte H

2016-11-29

Cardiopulmonary resuscitation (CPR) training has traditionally involved classroom-based courses or, more recently, home-based video self-instruction. These methods typically require preparation and purchase fee; which can dissuade many potential bystanders from receiving training. This study aimed to evaluate the effectiveness of teaching compression-only CPR to previously untrained individuals using our 6-min online CPR training video and skills practice on a homemade mannequin, reproduced by viewers with commonly available items (towel, toilet paper roll, t-shirt). Participants viewed the training video and practiced with the homemade mannequin. This was a parallel-design study with pre and post training evaluations of CPR skills (compression rate, depth, hand position, release), and hands-off time (time without compressions). CPR skills were evaluated using a sensor-equipped mannequin and two blinded CPR experts observed testing of participants. Twenty-four participants were included: 12 never-trained and 12 currently certified in CPR. Comparing pre and post training, the never-trained group had improvements in average compression rate per minute (64.3 to 103.9, p = 0.006), compressions with correct hand position in 1 min (8.3 to 54.3, p = 0.002), and correct compression release in 1 min (21.2 to 76.3, p 100/min), but an improved number of compressions with correct release (53.5 to 94.7, p 50 mm) remained problematic in both groups. Comparisons made between groups indicated significant improvements in compression depth, hand position, and hands-off time in never-trained compared to CPR-certified participants. Inter-rater agreement values were also calculated between the CPR experts and sensor-equipped mannequin. A brief internet-based video coupled with skill practice on a homemade mannequin improved compression-only CPR skills, especially in the previously untrained participants. This training method allows for widespread compression-only CPR

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

Science.gov (United States)

Culik, Karel II; Kari, Jarkko

1994-01-01

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

Videos and images from 25 years of teaching compressible flow

Science.gov (United States)

Settles, Gary

2008-11-01

Compressible flow is a very visual topic due to refractive optical flow visualization and the public fascination with high-speed flight. Films, video clips, and many images are available to convey this in the classroom. An overview of this material is given and selected examples are shown, drawn from educational films, the movies, television, etc., and accumulated over 25 years of teaching basic and advanced compressible-flow courses. The impact of copyright protection and the doctrine of fair use is also discussed.

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

Science.gov (United States)

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

The effects of multiview depth video compression on multiview rendering

NARCIS (Netherlands)

Merkle, P.; Morvan, Y.; Smolic, A.; Farin, D.S.; Mueller, K.; With, de P.H.N.; Wiegang, T.

2009-01-01

This article investigates the interaction between different techniques for depth compression and view synthesis rendering with multiview video plus scene depth data. Two different approaches for depth coding are compared, namely H.264/MVC, using temporal and inter-view reference images for efficient

Quasi Gradient Projection Algorithm for Sparse Reconstruction in Compressed Sensing

Directory of Open Access Journals (Sweden)

Xin Meng

2014-02-01

Full Text Available Compressed sensing is a novel signal sampling theory under the condition that the signal is sparse or compressible. The existing recovery algorithms based on the gradient projection can either need prior knowledge or recovery the signal poorly. In this paper, a new algorithm based on gradient projection is proposed, which is referred as Quasi Gradient Projection. The algorithm presented quasi gradient direction and two step sizes schemes along this direction. The algorithm doesn’t need any prior knowledge of the original signal. Simulation results demonstrate that the presented algorithm cans recovery the signal more correctly than GPSR which also don’t need prior knowledge. Meanwhile, the algorithm has a lower computation complexity.

An Unequal Secure Encryption Scheme for H.264/AVC Video Compression Standard

Science.gov (United States)

Fan, Yibo; Wang, Jidong; Ikenaga, Takeshi; Tsunoo, Yukiyasu; Goto, Satoshi

H.264/AVC is the newest video coding standard. There are many new features in it which can be easily used for video encryption. In this paper, we propose a new scheme to do video encryption for H.264/AVC video compression standard. We define Unequal Secure Encryption (USE) as an approach that applies different encryption schemes (with different security strength) to different parts of compressed video data. This USE scheme includes two parts: video data classification and unequal secure video data encryption. Firstly, we classify the video data into two partitions: Important data partition and unimportant data partition. Important data partition has small size with high secure protection, while unimportant data partition has large size with low secure protection. Secondly, we use AES as a block cipher to encrypt the important data partition and use LEX as a stream cipher to encrypt the unimportant data partition. AES is the most widely used symmetric cryptography which can ensure high security. LEX is a new stream cipher which is based on AES and its computational cost is much lower than AES. In this way, our scheme can achieve both high security and low computational cost. Besides the USE scheme, we propose a low cost design of hybrid AES/LEX encryption module. Our experimental results show that the computational cost of the USE scheme is low (about 25% of naive encryption at Level 0 with VEA used). The hardware cost for hybrid AES/LEX module is 4678 Gates and the AES encryption throughput is about 50Mbps.

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,...

Compressive sensing based algorithms for electronic defence

CERN Document Server

Mishra, Amit Kumar

2017-01-01

This book details some of the major developments in the implementation of compressive sensing in radio applications for electronic defense and warfare communication use. It provides a comprehensive background to the subject and at the same time describes some novel algorithms. It also investigates application value and performance-related parameters of compressive sensing in scenarios such as direction finding, spectrum monitoring, detection, and classification.

A New Algorithm for the On-Board Compression of Hyperspectral Images

Directory of Open Access Journals (Sweden)

Raúl Guerra

2018-03-01

Full Text Available Hyperspectral sensors are able to provide information that is useful for many different applications. However, the huge amounts of data collected by these sensors are not exempt of drawbacks, especially in remote sensing environments where the hyperspectral images are collected on-board satellites and need to be transferred to the earth’s surface. In this situation, an efficient compression of the hyperspectral images is mandatory in order to save bandwidth and storage space. Lossless compression algorithms have been traditionally preferred, in order to preserve all the information present in the hyperspectral cube for scientific purposes, despite their limited compression ratio. Nevertheless, the increment in the data-rate of the new-generation sensors is making more critical the necessity of obtaining higher compression ratios, making it necessary to use lossy compression techniques. A new transform-based lossy compression algorithm, namely Lossy Compression Algorithm for Hyperspectral Image Systems (HyperLCA, is proposed in this manuscript. This compressor has been developed for achieving high compression ratios with a good compression performance at a reasonable computational burden. An extensive amount of experiments have been performed in order to evaluate the goodness of the proposed HyperLCA compressor using different calibrated and uncalibrated hyperspectral images from the AVIRIS and Hyperion sensors. The results provided by the proposed HyperLCA compressor have been evaluated and compared against those produced by the most relevant state-of-the-art compression solutions. The theoretical and experimental evidence indicates that the proposed algorithm represents an excellent option for lossy compressing hyperspectral images, especially for applications where the available computational resources are limited, such as on-board scenarios.

Resource efficient data compression algorithms for demanding, WSN based biomedical applications.

Science.gov (United States)

Antonopoulos, Christos P; Voros, Nikolaos S

2016-02-01

During the last few years, medical research areas of critical importance such as Epilepsy monitoring and study, increasingly utilize wireless sensor network technologies in order to achieve better understanding and significant breakthroughs. However, the limited memory and communication bandwidth offered by WSN platforms comprise a significant shortcoming to such demanding application scenarios. Although, data compression can mitigate such deficiencies there is a lack of objective and comprehensive evaluation of relative approaches and even more on specialized approaches targeting specific demanding applications. The research work presented in this paper focuses on implementing and offering an in-depth experimental study regarding prominent, already existing as well as novel proposed compression algorithms. All algorithms have been implemented in a common Matlab framework. A major contribution of this paper, that differentiates it from similar research efforts, is the employment of real world Electroencephalography (EEG) and Electrocardiography (ECG) datasets comprising the two most demanding Epilepsy modalities. Emphasis is put on WSN applications, thus the respective metrics focus on compression rate and execution latency for the selected datasets. The evaluation results reveal significant performance and behavioral characteristics of the algorithms related to their complexity and the relative negative effect on compression latency as opposed to the increased compression rate. It is noted that the proposed schemes managed to offer considerable advantage especially aiming to achieve the optimum tradeoff between compression rate-latency. Specifically, proposed algorithm managed to combine highly completive level of compression while ensuring minimum latency thus exhibiting real-time capabilities. Additionally, one of the proposed schemes is compared against state-of-the-art general-purpose compression algorithms also exhibiting considerable advantages as far as the

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

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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.

Innovative Video Diagnostic Equipment for Material Science

Science.gov (United States)

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

2012-01-01

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

Using game theory for perceptual tuned rate control algorithm in video coding

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Luo, Jiancong; Ahmad, Ishfaq

2005-03-01

This paper proposes a game theoretical rate control technique for video compression. Using a cooperative gaming approach, which has been utilized in several branches of natural and social sciences because of its enormous potential for solving constrained optimization problems, we propose a dual-level scheme to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks. At the frame level, the algorithm allocates target bits to frames based on their coding complexity. At the macroblock level, the algorithm distributes bits to macroblocks by defining a bargaining game. Macroblocks play cooperatively to compete for shares of resources (bits) to optimize their quantization scales while considering the Human Visual System"s perceptual property. Since the whole frame is an entity perceived by viewers, macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint. The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution. Another advantage is that it allows multi-objective optimization with multiple decision makers (macroblocks). The simulation results testify the algorithm"s ability to achieve accurate bit rate with good perceptual quality, and to maintain a stable buffer level.

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

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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

A new modified fast fractal image compression algorithm

DEFF Research Database (Denmark)

Salarian, Mehdi; Nadernejad, Ehsan; MiarNaimi, Hossein

2013-01-01

In this paper, a new fractal image compression algorithm is proposed, in which the time of the encoding process is considerably reduced. The algorithm exploits a domain pool reduction approach, along with the use of innovative predefined values for contrast scaling factor, S, instead of searching...

The compression algorithm for the data acquisition system in HT-7 tokamak

International Nuclear Information System (INIS)

Zhu Lin; Luo Jiarong; Li Guiming; Yue Dongli

2003-01-01

HT-7 superconducting tokamak in the Institute of Plasma Physics of the Chinese Academy of Sciences is an experimental device for fusion research in China. The main task of the data acquisition system of HT-7 is to acquire, store, analyze and index the data. The volume of the data is nearly up to hundreds of million bytes. Besides the hardware and software support, a great capacity of data storage, process and transfer is a more important problem. To deal with this problem, the key technology is data compression algorithm. In the paper, the data format in HT-7 is introduced first, then the data compression algorithm, LZO, being a kind of portable lossless data compression algorithm with ANSIC, is analyzed. This compression algorithm, which fits well with the data acquisition and distribution in the nuclear fusion experiment, offers a pretty fast compression and extremely fast decompression. At last the performance evaluation of LZO application in HT-7 is given

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.

Distance Education Technology for the New Millennium Compressed Video Teaching. ZIFF Papiere 101.

Science.gov (United States)

Keegan, Desmond

This monograph combines an examination of theoretical issues raised by the introduction of two-way video and similar systems into distance education (DE) with practical advice on using compressed video systems in DE programs. Presented in the first half of the monograph are the following: analysis of the intrinsic links between DE and technology…

HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS

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V. T. Nguyen

2016-05-01

Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.

Using general-purpose compression algorithms for music analysis

DEFF Research Database (Denmark)

Louboutin, Corentin; Meredith, David

2016-01-01

General-purpose compression algorithms encode files as dictionaries of substrings with the positions of these strings’ occurrences. We hypothesized that such algorithms could be used for pattern discovery in music. We compared LZ77, LZ78, Burrows–Wheeler and COSIATEC on classifying folk song...... in the input data, COSIATEC outperformed LZ77 with a mean F1 score of 0.123, compared with 0.053 for LZ77. However, when the music was processed a voice at a time, the F1 score for LZ77 more than doubled to 0.124. We also discovered a significant correlation between compression factor and F1 score for all...

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

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

2017-04-01

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

FPGA Implementation of Gaussian Mixture Model Algorithm for 47 fps Segmentation of 1080p Video

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Mariangela Genovese

2013-01-01

Full Text Available Circuits and systems able to process high quality video in real time are fundamental in nowadays imaging systems. The circuit proposed in the paper, aimed at the robust identification of the background in video streams, implements the improved formulation of the Gaussian Mixture Model (GMM algorithm that is included in the OpenCV library. An innovative, hardware oriented, formulation of the GMM equations, the use of truncated binary multipliers, and ROM compression techniques allow reduced hardware complexity and increased processing capability. The proposed circuit has been designed having commercial FPGA devices as target and provides speed and logic resources occupation that overcome previously proposed implementations. The circuit, when implemented on Virtex6 or StratixIV, processes more than 45 frame per second in 1080p format and uses few percent of FPGA logic resources.

High-speed video analysis improves the accuracy of spinal cord compression measurement in a mouse contusion model.

Science.gov (United States)

Fournely, Marion; Petit, Yvan; Wagnac, Éric; Laurin, Jérôme; Callot, Virginie; Arnoux, Pierre-Jean

2018-01-01

Animal models of spinal cord injuries aim to utilize controlled and reproducible conditions. However, a literature review reveals that mouse contusion studies using equivalent protocols may show large disparities in the observed impact force vs. cord compression relationship. The overall purpose of this study was to investigate possible sources of bias in these measurements. The specific objective was to improve spinal cord compression measurements using a video-based setup to detect the impactor-spinal cord time-to-contact. A force-controlled 30kDyn unilateral contusion at C4 vertebral level was performed in six mice with the Infinite Horizon impactor (IH). High-speed video was used to determine the time-to-contact between the impactor tip and the spinal cord and to compute the related displacement of the tip into the tissue: the spinal cord compression and the compression ratio. Delayed time-to-contact detection with the IH device led to an underestimation of the cord compression. Compression values indicated by the IH were 64% lower than those based on video analysis (0.33mm vs. 0.88mm). Consequently, the mean compression ratio derived from the device was underestimated when compared to the value derived from video analysis (22% vs. 61%). Default time-to-contact detection from the IH led to significant errors in spinal cord compression assessment. Accordingly, this may explain some of the reported data discrepancies in the literature. The proposed setup could be implemented by users of contusion devices to improve the quantative description of the primary injury inflicted to the spinal cord. Copyright © 2017 Elsevier B.V. All rights reserved.

A Near-Lossless Image Compression Algorithm Suitable for Hardware Design in Wireless Endoscopy System

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Xie Xiang

2007-01-01

Full Text Available In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm based on the Bayer format image suitable for hardware design. This algorithm can provide low average compression rate ( bits/pixel with high image quality (larger than dB for endoscopic images. Especially, it has low complexity hardware overhead (only two line buffers and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI and high-quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters. In addition, the VLSI architecture of this compression algorithm is also given out. Its hardware design has been implemented in m CMOS process.

Selective encryption for H.264/AVC video coding

Science.gov (United States)

Shi, Tuo; King, Brian; Salama, Paul

2006-02-01

Due to the ease with which digital data can be manipulated and due to the ongoing advancements that have brought us closer to pervasive computing, the secure delivery of video and images has become a challenging problem. Despite the advantages and opportunities that digital video provide, illegal copying and distribution as well as plagiarism of digital audio, images, and video is still ongoing. In this paper we describe two techniques for securing H.264 coded video streams. The first technique, SEH264Algorithm1, groups the data into the following blocks of data: (1) a block that contains the sequence parameter set and the picture parameter set, (2) a block containing a compressed intra coded frame, (3) a block containing the slice header of a P slice, all the headers of the macroblock within the same P slice, and all the luma and chroma DC coefficients belonging to the all the macroblocks within the same slice, (4) a block containing all the ac coefficients, and (5) a block containing all the motion vectors. The first three are encrypted whereas the last two are not. The second method, SEH264Algorithm2, relies on the use of multiple slices per coded frame. The algorithm searches the compressed video sequence for start codes (0x000001) and then encrypts the next N bits of data.

Video quality pooling adaptive to perceptual distortion severity.

Science.gov (United States)

Park, Jincheol; Seshadrinathan, Kalpana; Lee, Sanghoon; Bovik, Alan Conrad

2013-02-01

It is generally recognized that severe video distortions that are transient in space and/or time have a large effect on overall perceived video quality. In order to understand this phenomena, we study the distribution of spatio-temporally local quality scores obtained from several video quality assessment (VQA) algorithms on videos suffering from compression and lossy transmission over communication channels. We propose a content adaptive spatial and temporal pooling strategy based on the observed distribution. Our method adaptively emphasizes "worst" scores along both the spatial and temporal dimensions of a video sequence and also considers the perceptual effect of large-area cohesive motion flow such as egomotion. We demonstrate the efficacy of the method by testing it using three different VQA algorithms on the LIVE Video Quality database and the EPFL-PoliMI video quality database.

Algorithm for Video Summarization of Bronchoscopy Procedures

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Leszczuk Mikołaj I

2011-12-01

Full Text Available Abstract Background The duration of bronchoscopy examinations varies considerably depending on the diagnostic and therapeutic procedures used. It can last more than 20 minutes if a complex diagnostic work-up is included. With wide access to videobronchoscopy, the whole procedure can be recorded as a video sequence. Common practice relies on an active attitude of the bronchoscopist who initiates the recording process and usually chooses to archive only selected views and sequences. However, it may be important to record the full bronchoscopy procedure as documentation when liability issues are at stake. Furthermore, an automatic recording of the whole procedure enables the bronchoscopist to focus solely on the performed procedures. Video recordings registered during bronchoscopies include a considerable number of frames of poor quality due to blurry or unfocused images. It seems that such frames are unavoidable due to the relatively tight endobronchial space, rapid movements of the respiratory tract due to breathing or coughing, and secretions which occur commonly in the bronchi, especially in patients suffering from pulmonary disorders. Methods The use of recorded bronchoscopy video sequences for diagnostic, reference and educational purposes could be considerably extended with efficient, flexible summarization algorithms. Thus, the authors developed a prototype system to create shortcuts (called summaries or abstracts of bronchoscopy video recordings. Such a system, based on models described in previously published papers, employs image analysis methods to exclude frames or sequences of limited diagnostic or education value. Results The algorithm for the selection or exclusion of specific frames or shots from video sequences recorded during bronchoscopy procedures is based on several criteria, including automatic detection of "non-informative", frames showing the branching of the airways and frames including pathological lesions. Conclusions

Processing Decoded Video for Backlight Dimming

DEFF Research Database (Denmark)

Burini, Nino; Korhonen, Jari

rendition of the signals, particularly in the case of LCDs with dynamic local backlight. This thesis shows that it is possible to model LCDs with dynamic backlight to design algorithms that improve the visual quality of 2D and 3D content, and that digital video coding artifacts like blocking or ringing can......Quality of digital image and video signals on TV screens is aected by many factors, including the display technology and compression standards. An accurate knowledge of the characteristics of the display andof the video signals can be used to develop advanced algorithms that improve the visual...... be reduced with post-processing. LCD screens with dynamic local backlight are modeled in their main aspects, like pixel luminance, light diusion and light perception. Following the model, novel algorithms based on optimization are presented and extended, then reduced in complexity, to produce backlights...

Unified compression and encryption algorithm for fast and secure network communications

International Nuclear Information System (INIS)

Rizvi, S.M.J.; Hussain, M.; Qaiser, N.

2005-01-01

Compression and encryption of data are two vital requirements for the fast and secure transmission of data in the network based communications. In this paper an algorithm is presented based on adaptive Huffman encoding for unified compression and encryption of Unicode encoded textual data. The Huffman encoding weakness that same tree is needed for decoding is utilized in the algorithm presented as an extra layer of security, which is updated whenever the frequency change is above the specified threshold level. The results show that we get compression comparable to popular zip format and in addition to that data has got an additional layer of encryption that makes it more secure. Thus unified algorithm presented here can be used for network communications between different branches of banks, e- Government programs and national database and registration centers where data transmission requires both compression and encryption. (author)

A real-time ECG data compression and transmission algorithm for an e-health device.

Science.gov (United States)

Lee, SangJoon; Kim, Jungkuk; Lee, Myoungho

2011-09-01

This paper introduces a real-time data compression and transmission algorithm between e-health terminals for a periodic ECGsignal. The proposed algorithm consists of five compression procedures and four reconstruction procedures. In order to evaluate the performance of the proposed algorithm, the algorithm was applied to all 48 recordings of MIT-BIH arrhythmia database, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), rms, SNR, and quality score (QS) values were obtained. The result showed that the CR was 27.9:1 and the PRD was 2.93 on average for all 48 data instances with a 15% window size. In addition, the performance of the algorithm was compared to those of similar algorithms introduced recently by others. It was found that the proposed algorithm showed clearly superior performance in all 48 data instances at a compression ratio lower than 15:1, whereas it showed similar or slightly inferior PRD performance for a data compression ratio higher than 20:1. In light of the fact that the similarity with the original data becomes meaningless when the PRD is higher than 2, the proposed algorithm shows significantly better performance compared to the performance levels of other algorithms. Moreover, because the algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.

Advanced algorithms for information science

International Nuclear Information System (INIS)

Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.

1998-01-01

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression

Advanced algorithms for information science

Energy Technology Data Exchange (ETDEWEB)

Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.

1998-12-31

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression.

Image compression-encryption algorithms by combining hyper-chaotic system with discrete fractional random transform

Science.gov (United States)

Gong, Lihua; Deng, Chengzhi; Pan, Shumin; Zhou, Nanrun

2018-07-01

Based on hyper-chaotic system and discrete fractional random transform, an image compression-encryption algorithm is designed. The original image is first transformed into a spectrum by the discrete cosine transform and the resulting spectrum is compressed according to the method of spectrum cutting. The random matrix of the discrete fractional random transform is controlled by a chaotic sequence originated from the high dimensional hyper-chaotic system. Then the compressed spectrum is encrypted by the discrete fractional random transform. The order of DFrRT and the parameters of the hyper-chaotic system are the main keys of this image compression and encryption algorithm. The proposed algorithm can compress and encrypt image signal, especially can encrypt multiple images once. To achieve the compression of multiple images, the images are transformed into spectra by the discrete cosine transform, and then the spectra are incised and spliced into a composite spectrum by Zigzag scanning. Simulation results demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.

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

Visual content highlighting via automatic extraction of embedded captions on MPEG compressed video

Science.gov (United States)

Yeo, Boon-Lock; Liu, Bede

1996-03-01

Embedded captions in TV programs such as news broadcasts, documentaries and coverage of sports events provide important information on the underlying events. In digital video libraries, such captions represent a highly condensed form of key information on the contents of the video. In this paper we propose a scheme to automatically detect the presence of captions embedded in video frames. The proposed method operates on reduced image sequences which are efficiently reconstructed from compressed MPEG video and thus does not require full frame decompression. The detection, extraction and analysis of embedded captions help to capture the highlights of visual contents in video documents for better organization of video, to present succinctly the important messages embedded in the images, and to facilitate browsing, searching and retrieval of relevant clips.

Efficient Foreground Extraction From HEVC Compressed Video for Application to Real-Time Analysis of Surveillance 'Big' Data.

Science.gov (United States)

Dey, Bhaskar; Kundu, Malay K

2015-11-01

While surveillance video is the biggest source of unstructured Big Data today, the emergence of high-efficiency video coding (HEVC) standard is poised to have a huge role in lowering the costs associated with transmission and storage. Among the benefits of HEVC over the legacy MPEG-4 Advanced Video Coding (AVC), is a staggering 40 percent or more bitrate reduction at the same visual quality. Given the bandwidth limitations, video data are compressed essentially by removing spatial and temporal correlations that exist in its uncompressed form. This causes compressed data, which are already de-correlated, to serve as a vital resource for machine learning with significantly fewer samples for training. In this paper, an efficient approach to foreground extraction/segmentation is proposed using novel spatio-temporal de-correlated block features extracted directly from the HEVC compressed video. Most related techniques, in contrast, work on uncompressed images claiming significant storage and computational resources not only for the decoding process prior to initialization but also for the feature selection/extraction and background modeling stage following it. The proposed approach has been qualitatively and quantitatively evaluated against several other state-of-the-art methods.

Statistical motion vector analysis for object tracking in compressed video streams

Science.gov (United States)

Leny, Marc; Prêteux, Françoise; Nicholson, Didier

2008-02-01

Compressed video is the digital raw material provided by video-surveillance systems and used for archiving and indexing purposes. Multimedia standards have therefore a direct impact on such systems. If MPEG-2 used to be the coding standard, MPEG-4 (part 2) has now replaced it in most installations, and MPEG-4 AVC/H.264 solutions are now being released. Finely analysing the complex and rich MPEG-4 streams is a challenging issue addressed in that paper. The system we designed is based on five modules: low-resolution decoder, motion estimation generator, object motion filtering, low-resolution object segmentation, and cooperative decision. Our contributions refer to as the statistical analysis of the spatial distribution of the motion vectors, the computation of DCT-based confidence maps, the automatic motion activity detection in the compressed file and a rough indexation by dedicated descriptors. The robustness and accuracy of the system are evaluated on a large corpus (hundreds of hours of in-and outdoor videos with pedestrians and vehicles). The objective benchmarking of the performances is achieved with respect to five metrics allowing to estimate the error part due to each module and for different implementations. This evaluation establishes that our system analyses up to 200 frames (720x288) per second (2.66 GHz CPU).

A novel high-frequency encoding algorithm for image compression

Science.gov (United States)

Siddeq, Mohammed M.; Rodrigues, Marcos A.

2017-12-01

In this paper, a new method for image compression is proposed whose quality is demonstrated through accurate 3D reconstruction from 2D images. The method is based on the discrete cosine transform (DCT) together with a high-frequency minimization encoding algorithm at compression stage and a new concurrent binary search algorithm at decompression stage. The proposed compression method consists of five main steps: (1) divide the image into blocks and apply DCT to each block; (2) apply a high-frequency minimization method to the AC-coefficients reducing each block by 2/3 resulting in a minimized array; (3) build a look up table of probability data to enable the recovery of the original high frequencies at decompression stage; (4) apply a delta or differential operator to the list of DC-components; and (5) apply arithmetic encoding to the outputs of steps (2) and (4). At decompression stage, the look up table and the concurrent binary search algorithm are used to reconstruct all high-frequency AC-coefficients while the DC-components are decoded by reversing the arithmetic coding. Finally, the inverse DCT recovers the original image. We tested the technique by compressing and decompressing 2D images including images with structured light patterns for 3D reconstruction. The technique is compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results demonstrate that the proposed compression method is perceptually superior to JPEG with equivalent quality to JPEG2000. Concerning 3D surface reconstruction from images, it is demonstrated that the proposed method is superior to both JPEG and JPEG2000.

Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm

Science.gov (United States)

Genovese, Mariangela; Napoli, Ettore

2013-05-01

The identification of moving objects is a fundamental step in computer vision processing chains. The development of low cost and lightweight smart cameras steadily increases the request of efficient and high performance circuits able to process high definition video in real time. The paper proposes two processor cores aimed to perform the real time background identification on High Definition (HD, 1920 1080 pixel) video streams. The implemented algorithm is the OpenCV version of the Gaussian Mixture Model (GMM), an high performance probabilistic algorithm for the segmentation of the background that is however computationally intensive and impossible to implement on general purpose CPU with the constraint of real time processing. In the proposed paper, the equations of the OpenCV GMM algorithm are optimized in such a way that a lightweight and low power implementation of the algorithm is obtained. The reported performances are also the result of the use of state of the art truncated binary multipliers and ROM compression techniques for the implementation of the non-linear functions. The first circuit has commercial FPGA devices as a target and provides speed and logic resource occupation that overcome previously proposed implementations. The second circuit is oriented to an ASIC (UMC-90nm) standard cell implementation. Both implementations are able to process more than 60 frames per second in 1080p format, a frame rate compatible with HD television.

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)

Resolution enhancement of low-quality videos using a high-resolution frame

Science.gov (United States)

Pham, Tuan Q.; van Vliet, Lucas J.; Schutte, Klamer

2006-01-01

This paper proposes an example-based Super-Resolution (SR) algorithm of compressed videos in the Discrete Cosine Transform (DCT) domain. Input to the system is a Low-Resolution (LR) compressed video together with a High-Resolution (HR) still image of similar content. Using a training set of corresponding LR-HR pairs of image patches from the HR still image, high-frequency details are transferred from the HR source to the LR video. The DCT-domain algorithm is much faster than example-based SR in spatial domain 6 because of a reduction in search dimensionality, which is a direct result of the compact and uncorrelated DCT representation. Fast searching techniques like tree-structure vector quantization 16 and coherence search1 are also key to the improved efficiency. Preliminary results on MJPEG sequence show promising result of the DCT-domain SR synthesis approach.

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%.

An Improved Fast Compressive Tracking Algorithm Based on Online Random Forest Classifier

Directory of Open Access Journals (Sweden)

Xiong Jintao

2016-01-01

Full Text Available The fast compressive tracking (FCT algorithm is a simple and efficient algorithm, which is proposed in recent years. But, it is difficult to deal with the factors such as occlusion, appearance changes, pose variation, etc in processing. The reasons are that, Firstly, even if the naive Bayes classifier is fast in training, it is not robust concerning the noise. Secondly, the parameters are required to vary with the unique environment for accurate tracking. In this paper, we propose an improved fast compressive tracking algorithm based on online random forest (FCT-ORF for robust visual tracking. Firstly, we combine ideas with the adaptive compressive sensing theory regarding the weighted random projection to exploit both local and discriminative information of the object. The second reason is the online random forest classifier for online tracking which is demonstrated with more robust to the noise adaptively and high computational efficiency. The experimental results show that the algorithm we have proposed has a better performance in the field of occlusion, appearance changes, and pose variation than the fast compressive tracking algorithm’s contribution.

APPLICABILITY ANALYSIS OF THE PHASE CORRELATION ALGORITHM FOR STABILIZATION OF VIDEO FRAMES SEQUENCES FOR CAPILLARY BLOOD FLOW

Directory of Open Access Journals (Sweden)

K. A. Karimov

2016-05-01

Full Text Available Videocapillaroscopy is a convenient and non-invasive method of blood flow parameters recovery in the capillaries. Capillaries position can vary at recorded video sequences due to the registration features of capillary blood flow. Stabilization algorithm of video capillary blood flow based on phase correlation is proposed and researched. This algorithm is compared to the known algorithms of video frames stabilization with full-frame superposition and with key points. Programs, based on discussed algorithms, are compared under processing the experimentally recorded video sequences of human capillaries and under processing of computer-simulated sequences of video frames with the specified offset. The full-frame superposition algorithm provides high quality of stabilization; however, the program based on this algorithm requires significant computational resources. Software implementation of the algorithm based on the detection of the key points is characterized by good performance, but provides low quality of stabilization for video sequences capillary blood flow. Algorithm based on phase correlation method provides high quality of stabilization and program realization of this algorithm requires minimal computational resources. It is shown that the phase correlation algorithm is the most useful for stabilization of video sequences for capillaries blood flow. Obtained findings can be used in the software for biomedical diagnostics.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

Science.gov (United States)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at

Human features detection in video surveillance

OpenAIRE

Barbosa, Patrícia Margarida Silva de Castro Neves

2016-01-01

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores Human activity recognition algorithms have been studied actively from decades using a sequence of 2D and 3D images from a video surveillance. This new surveillance solutions and the areas of image processing and analysis have been receiving special attention and interest from the scientific community. Thus, it became possible to witness the appearance of new video compression techniques, the tr...

The role of optical flow in automated quality assessment of full-motion video

Science.gov (United States)

Harguess, Josh; Shafer, Scott; Marez, Diego

2017-09-01

In real-world video data, such as full-motion-video (FMV) taken from unmanned vehicles, surveillance systems, and other sources, various corruptions to the raw data is inevitable. This can be due to the image acquisition process, noise, distortion, and compression artifacts, among other sources of error. However, we desire methods to analyze the quality of the video to determine whether the underlying content of the corrupted video can be analyzed by humans or machines and to what extent. Previous approaches have shown that motion estimation, or optical flow, can be an important cue in automating this video quality assessment. However, there are many different optical flow algorithms in the literature, each with their own advantages and disadvantages. We examine the effect of the choice of optical flow algorithm (including baseline and state-of-the-art), on motionbased automated video quality assessment algorithms.

ALGORITHM OF PLACEMENT OF VIDEO SURVEILLANCE CAMERAS AND ITS SOFTWARE IMPLEMENTATION

Directory of Open Access Journals (Sweden)

Loktev Alexey Alexeevich

2012-10-01

Full Text Available Comprehensive distributed safety, control, and monitoring systems applied by companies and organizations of different ownership structure play a substantial role in the present-day society. Video surveillance elements that ensure image processing and decision making in automated or automatic modes are the essential components of new systems. This paper covers the modeling of video surveillance systems installed in buildings, and the algorithm, or pattern, of video camera placement with due account for nearly all characteristics of buildings, detection and recognition facilities, and cameras themselves. This algorithm will be subsequently implemented as a user application. The project contemplates a comprehensive approach to the automatic placement of cameras that take account of their mutual positioning and compatibility of tasks. The project objective is to develop the principal elements of the algorithm of recognition of a moving object to be detected by several cameras. The image obtained by different cameras will be processed. Parameters of motion are to be identified to develop a table of possible options of routes. The implementation of the recognition algorithm represents an independent research project to be covered by a different article. This project consists in the assessment of the degree of complexity of an algorithm of camera placement designated for identification of cases of inaccurate algorithm implementation, as well as in the formulation of supplementary requirements and input data by means of intercrossing sectors covered by neighbouring cameras. The project also contemplates identification of potential problems in the course of development of a physical security and monitoring system at the stage of the project design development and testing. The camera placement algorithm has been implemented as a software application that has already been pilot tested on buildings and inside premises that have irregular dimensions. The

On system behaviour using complex networks of a compression algorithm

Science.gov (United States)

Walker, David M.; Correa, Debora C.; Small, Michael

2018-01-01

We construct complex networks of scalar time series using a data compression algorithm. The structure and statistics of the resulting networks can be used to help characterize complex systems, and one property, in particular, appears to be a useful discriminating statistic in surrogate data hypothesis tests. We demonstrate these ideas on systems with known dynamical behaviour and also show that our approach is capable of identifying behavioural transitions within electroencephalogram recordings as well as changes due to a bifurcation parameter of a chaotic system. The technique we propose is dependent on a coarse grained quantization of the original time series and therefore provides potential for a spatial scale-dependent characterization of the data. Finally the method is as computationally efficient as the underlying compression algorithm and provides a compression of the salient features of long time series.

The effect of depth compression on multiview rendering quality

NARCIS (Netherlands)

Merkle, P.; Morvan, Y.; Smolic, A.; Farin, D.S.; Mueller, K..; With, de P.H.N.; Wiegand, T.

2010-01-01

This paper presents a comparative study on different techniques for depth-image compression and its implications on the quality of multiview video plus depth virtual view rendering. A novel coding algorithm for depth images that concentrates on their special characteristics, namely smooth regions

Freeing Space for NASA: Incorporating a Lossless Compression Algorithm into NASA's FOSS System

Science.gov (United States)

Fiechtner, Kaitlyn; Parker, Allen

2011-01-01

NASA's Fiber Optic Strain Sensing (FOSS) system can gather and store up to 1,536,000 bytes (1.46 megabytes) per second. Since the FOSS system typically acquires hours - or even days - of data, the system can gather hundreds of gigabytes of data for a given test event. To store such large quantities of data more effectively, NASA is modifying a Lempel-Ziv-Oberhumer (LZO) lossless data compression program to compress data as it is being acquired in real time. After proving that the algorithm is capable of compressing the data from the FOSS system, the LZO program will be modified and incorporated into the FOSS system. Implementing an LZO compression algorithm will instantly free up memory space without compromising any data obtained. With the availability of memory space, the FOSS system can be used more efficiently on test specimens, such as Unmanned Aerial Vehicles (UAVs) that can be in flight for days. By integrating the compression algorithm, the FOSS system can continue gathering data, even on longer flights.

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)

Multiscale Architectures and Parallel Algorithms for Video Object Tracking

Science.gov (United States)

2011-10-01

larger number of cores using the IBM QS22 Blade for handling higher video processing workloads (but at higher cost per core), low power consumption and...Cell/B.E. Blade processors which have a lot more main memory but also higher power consumption . More detailed performance figures for HD and SD video...Parallelism in Algorithms and Architectures, pages 289–298, 2007. [3] S. Ali and M. Shah. COCOA - Tracking in aerial imagery. In Daniel J. Henry

Low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

Science.gov (United States)

Garrido-Cantos, Rosario; De Cock, Jan; Martínez, Jose Luis; Van Leuven, Sebastian; Cuenca, Pedro; Garrido, Antonio

2013-12-01

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

A Multi-Frame Post-Processing Approach to Improved Decoding of H.264/AVC Video

DEFF Research Database (Denmark)

Huang, Xin; Li, Huiying; Forchhammer, Søren

2007-01-01

Video compression techniques may yield visually annoying artifacts for limited bitrate coding. In order to improve video quality, a multi-frame based motion compensated filtering algorithm is reported based on combining multiple pictures to form a single super-resolution picture and decimation......, and annoying ringing artifacts are effectively suppressed....

Context-dependent JPEG backward-compatible high-dynamic range image compression

Science.gov (United States)

Korshunov, Pavel; Ebrahimi, Touradj

2013-10-01

High-dynamic range (HDR) imaging is expected, together with ultrahigh definition and high-frame rate video, to become a technology that may change photo, TV, and film industries. Many cameras and displays capable of capturing and rendering both HDR images and video are already available in the market. The popularity and full-public adoption of HDR content is, however, hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of low-dynamic range (LDR) displays that are unable to render HDR. To facilitate the wide spread of HDR usage, the backward compatibility of HDR with commonly used legacy technologies for storage, rendering, and compression of video and images are necessary. Although many tone-mapping algorithms are developed for generating viewable LDR content from HDR, there is no consensus of which algorithm to use and under which conditions. We, via a series of subjective evaluations, demonstrate the dependency of the perceptual quality of the tone-mapped LDR images on the context: environmental factors, display parameters, and image content itself. Based on the results of subjective tests, it proposes to extend JPEG file format, the most popular image format, in a backward compatible manner to deal with HDR images also. An architecture to achieve such backward compatibility with JPEG is proposed. A simple implementation of lossy compression demonstrates the efficiency of the proposed architecture compared with the state-of-the-art HDR image compression.

Holovideo: Real-time 3D range video encoding and decoding on GPU

Science.gov (United States)

Karpinsky, Nikolaus; Zhang, Song

2012-02-01

We present a 3D video-encoding technique called Holovideo that is capable of encoding high-resolution 3D videos into standard 2D videos, and then decoding the 2D videos back into 3D rapidly without significant loss of quality. Due to the nature of the algorithm, 2D video compression such as JPEG encoding with QuickTime Run Length Encoding (QTRLE) can be applied with little quality loss, resulting in an effective way to store 3D video at very small file sizes. We found that under a compression ratio of 134:1, Holovideo to OBJ file format, the 3D geometry quality drops at a negligible level. Several sets of 3D videos were captured using a structured light scanner, compressed using the Holovideo codec, and then uncompressed and displayed to demonstrate the effectiveness of the codec. With the use of OpenGL Shaders (GLSL), the 3D video codec can encode and decode in realtime. We demonstrated that for a video size of 512×512, the decoding speed is 28 frames per second (FPS) with a laptop computer using an embedded NVIDIA GeForce 9400 m graphics processing unit (GPU). Encoding can be done with this same setup at 18 FPS, making this technology suitable for applications such as interactive 3D video games and 3D video conferencing.

Brief compression-only cardiopulmonary resuscitation training video and simulation with homemade mannequin improves CPR skills

OpenAIRE

Wanner, Gregory K.; Osborne, Arayel; Greene, Charlotte H.

2016-01-01

Background Cardiopulmonary resuscitation (CPR) training has traditionally involved classroom-based courses or, more recently, home-based video self-instruction. These methods typically require preparation and purchase fee; which can dissuade many potential bystanders from receiving training. This study aimed to evaluate the effectiveness of teaching compression-only CPR to previously untrained individuals using our 6-min online CPR training video and skills practice on a homemade mannequin, r...

A new method for robust video watermarking resistant against key estimation attacks

Science.gov (United States)

Mitekin, Vitaly

2015-12-01

This paper presents a new method for high-capacity robust digital video watermarking and algorithms of embedding and extraction of watermark based on this method. Proposed method uses password-based two-dimensional pseudonoise arrays for watermark embedding, making brute-force attacks aimed at steganographic key retrieval mostly impractical. Proposed algorithm for 2-dimensional "noise-like" watermarking patterns generation also allows to significantly decrease watermark collision probability ( i.e. probability of correct watermark detection and extraction using incorrect steganographic key or password).. Experimental research provided in this work also shows that simple correlation-based watermark detection procedure can be used, providing watermark robustness against lossy compression and watermark estimation attacks. At the same time, without decreasing robustness of embedded watermark, average complexity of the brute-force key retrieval attack can be increased to 1014 watermark extraction attempts (compared to 104-106 for a known robust watermarking schemes). Experimental results also shows that for lowest embedding intensity watermark preserves it's robustness against lossy compression of host video and at the same time preserves higher video quality (PSNR up to 51dB) compared to known wavelet-based and DCT-based watermarking algorithms.

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.

Quantifying the effect of disruptions to temporal coherence on the intelligibility of compressed American Sign Language video

Science.gov (United States)

Ciaramello, Frank M.; Hemami, Sheila S.

2009-02-01

Communication of American Sign Language (ASL) over mobile phones would be very beneficial to the Deaf community. ASL video encoded to achieve the rates provided by current cellular networks must be heavily compressed and appropriate assessment techniques are required to analyze the intelligibility of the compressed video. As an extension to a purely spatial measure of intelligibility, this paper quantifies the effect of temporal compression artifacts on sign language intelligibility. These artifacts can be the result of motion-compensation errors that distract the observer or frame rate reductions. They reduce the the perception of smooth motion and disrupt the temporal coherence of the video. Motion-compensation errors that affect temporal coherence are identified by measuring the block-level correlation between co-located macroblocks in adjacent frames. The impact of frame rate reductions was quantified through experimental testing. A subjective study was performed in which fluent ASL participants rated the intelligibility of sequences encoded at a range of 5 different frame rates and with 3 different levels of distortion. The subjective data is used to parameterize an objective intelligibility measure which is highly correlated with subjective ratings at multiple frame rates.

Watermarking textures in video games

Science.gov (United States)

Liu, Huajian; Berchtold, Waldemar; Schäfer, Marcel; Lieb, Patrick; Steinebach, Martin

2014-02-01

Digital watermarking is a promising solution to video game piracy. In this paper, based on the analysis of special challenges and requirements in terms of watermarking textures in video games, a novel watermarking scheme for DDS textures in video games is proposed. To meet the performance requirements in video game applications, the proposed algorithm embeds the watermark message directly in the compressed stream in DDS files and can be straightforwardly applied in watermark container technique for real-time embedding. Furthermore, the embedding approach achieves high watermark payload to handle collusion secure fingerprinting codes with extreme length. Hence, the scheme is resistant to collusion attacks, which is indispensable in video game applications. The proposed scheme is evaluated in aspects of transparency, robustness, security and performance. Especially, in addition to classical objective evaluation, the visual quality and playing experience of watermarked games is assessed subjectively in game playing.

Study on data compression algorithm and its implementation in portable electronic device for Internet of Things applications

Directory of Open Access Journals (Sweden)

Khairi Nor Asilah

2017-01-01

Full Text Available An Internet of Things (IoT device is usually powered by a small battery, which does not last long. As a result, saving energy in IoT devices has become an important issue when it comes to this subject. Since power consumption is the primary cause of radio communication, some researchers have proposed several compression algorithms with the purpose of overcoming this particular problem. Several data compression algorithms from previous reference papers are discussed in this paper. The description of the compression algorithm in the reference papers was collected and summarized in a table form. From the analysis, MAS compression algorithm was selected as a project prototype due to its high potential for meeting the project requirements. Besides that, it also produced better performance regarding energy-saving, better memory usage, and data transmission efficiency. This method is also suitable to be implemented in WSN. MAS compression algorithm will be prototyped and applied in portable electronic devices for Internet of Things applications.

Study on data compression algorithm and its implementation in portable electronic device for Internet of Things applications

Science.gov (United States)

Asilah Khairi, Nor; Bahari Jambek, Asral

2017-11-01

An Internet of Things (IoT) device is usually powered by a small battery, which does not last long. As a result, saving energy in IoT devices has become an important issue when it comes to this subject. Since power consumption is the primary cause of radio communication, some researchers have proposed several compression algorithms with the purpose of overcoming this particular problem. Several data compression algorithms from previous reference papers are discussed in this paper. The description of the compression algorithm in the reference papers was collected and summarized in a table form. From the analysis, MAS compression algorithm was selected as a project prototype due to its high potential for meeting the project requirements. Besides that, it also produced better performance regarding energy-saving, better memory usage, and data transmission efficiency. This method is also suitable to be implemented in WSN. MAS compression algorithm will be prototyped and applied in portable electronic devices for Internet of Things applications.

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2015-05-01

Motion video analysis is a challenging task, especially in real-time applications. In most safety and security critical applications, a human observer is an obligatory part of the overall analysis system. Over the last years, substantial progress has been made in the development of automated image exploitation algorithms. Hence, we investigate how the benefits of automated video analysis can be integrated suitably into the current video exploitation systems. In this paper, a system design is introduced which strives to combine both the qualities of the human observer's perception and the automated algorithms, thus aiming to improve the overall performance of a real-time video analysis system. The system design builds on prior work where we showed the benefits for the human observer by means of a user interface which utilizes the human visual focus of attention revealed by the eye gaze direction for interaction with the image exploitation system; eye tracker-based interaction allows much faster, more convenient, and equally precise moving target acquisition in video images than traditional computer mouse selection. The system design also builds on prior work we did on automated target detection, segmentation, and tracking algorithms. Beside the system design, a first pilot study is presented, where we investigated how the participants (all non-experts in video analysis) performed in initializing an object tracking subsystem by selecting a target for tracking. Preliminary results show that the gaze + key press technique is an effective, efficient, and easy to use interaction technique when performing selection operations on moving targets in videos in order to initialize an object tracking function.

Compressive sampling by artificial neural networks for video

Science.gov (United States)

Szu, Harold; Hsu, Charles; Jenkins, Jeffrey; Reinhardt, Kitt

2011-06-01

We describe a smart surveillance strategy for handling novelty changes. Current sensors seem to keep all, redundant or not. The Human Visual System's Hubel-Wiesel (wavelet) edge detection mechanism pays attention to changes in movement, which naturally produce organized sparseness because a stagnant edge is not reported to the brain's visual cortex by retinal neurons. Sparseness is defined as an ordered set of ones (movement or not) relative to zeros that could be pseudo-orthogonal among themselves; then suited for fault tolerant storage and retrieval by means of Associative Memory (AM). The firing is sparse at the change locations. Unlike purely random sparse masks adopted in medical Compressive Sensing, these organized ones have an additional benefit of using the image changes to make retrievable graphical indexes. We coined this organized sparseness as Compressive Sampling; sensing but skipping over redundancy without altering the original image. Thus, we turn illustrate with video the survival tactics which animals that roam the Earth use daily. They acquire nothing but the space-time changes that are important to satisfy specific prey-predator relationships. We have noticed a similarity between the mathematical Compressive Sensing and this biological mechanism used for survival. We have designed a hardware implementation of the Human Visual System's Compressive Sampling scheme. To speed up further, our mixedsignal circuit design of frame differencing is built in on-chip processing hardware. A CMOS trans-conductance amplifier is designed here to generate a linear current output using a pair of differential input voltages from 2 photon detectors for change detection---one for the previous value and the other the subsequent value, ("write" synaptic weight by Hebbian outer products; "read" by inner product & pt. NL threshold) to localize and track the threat targets.

First- and third-party ground truth for key frame extraction from consumer video clips

Science.gov (United States)

Costello, Kathleen; Luo, Jiebo

2007-02-01

Extracting key frames (KF) from video is of great interest in many applications, such as video summary, video organization, video compression, and prints from video. KF extraction is not a new problem. However, current literature has been focused mainly on sports or news video. In the consumer video space, the biggest challenges for key frame selection from consumer videos are the unconstrained content and lack of any preimposed structure. In this study, we conduct ground truth collection of key frames from video clips taken by digital cameras (as opposed to camcorders) using both first- and third-party judges. The goals of this study are: (1) to create a reference database of video clips reasonably representative of the consumer video space; (2) to identify associated key frames by which automated algorithms can be compared and judged for effectiveness; and (3) to uncover the criteria used by both first- and thirdparty human judges so these criteria can influence algorithm design. The findings from these ground truths will be discussed.

A data compression algorithm for nuclear spectrum files

International Nuclear Information System (INIS)

Mika, J.F.; Martin, L.J.; Johnston, P.N.

1990-01-01

The total space occupied by computer files of spectra generated in nuclear spectroscopy systems can lead to problems of storage, and transmission time. An algorithm is presented which significantly reduces the space required to store nuclear spectra, without loss of any information content. Testing indicates that spectrum files can be routinely compressed by a factor of 5. (orig.)

Research of Video Steganalysis Algorithm Based on H265 Protocol

Directory of Open Access Journals (Sweden)

Wu Kaicheng

2015-01-01

This paper researches LSB matching VSA based on H265 protocol with the research background of 26 original Video sequences, it firstly extracts classification features out from training samples as input of SVM, and trains in SVM to obtain high-quality category classification model, and then tests whether there is suspicious information in the video sample. The experimental results show that VSA algorithm based on LSB matching can be more practical to obtain all frame embedded secret information and carrier and video of local frame embedded. In addition, VSA adopts the method of frame by frame with a strong robustness in resisting attack in the corresponding time domain.

Efficient Enhancement for Spatial Scalable Video Coding Transmission

Directory of Open Access Journals (Sweden)

Mayada Khairy

2017-01-01

Full Text Available Scalable Video Coding (SVC is an international standard technique for video compression. It is an extension of H.264 Advanced Video Coding (AVC. In the encoding of video streams by SVC, it is suitable to employ the macroblock (MB mode because it affords superior coding efficiency. However, the exhaustive mode decision technique that is usually used for SVC increases the computational complexity, resulting in a longer encoding time (ET. Many other algorithms were proposed to solve this problem with imperfection of increasing transmission time (TT across the network. To minimize the ET and TT, this paper introduces four efficient algorithms based on spatial scalability. The algorithms utilize the mode-distribution correlation between the base layer (BL and enhancement layers (ELs and interpolation between the EL frames. The proposed algorithms are of two categories. Those of the first category are based on interlayer residual SVC spatial scalability. They employ two methods, namely, interlayer interpolation (ILIP and the interlayer base mode (ILBM method, and enable ET and TT savings of up to 69.3% and 83.6%, respectively. The algorithms of the second category are based on full-search SVC spatial scalability. They utilize two methods, namely, full interpolation (FIP and the full-base mode (FBM method, and enable ET and TT savings of up to 55.3% and 76.6%, respectively.

Robust video watermarking via optimization algorithm for quantization of pseudo-random semi-global statistics

Science.gov (United States)

Kucukgoz, Mehmet; Harmanci, Oztan; Mihcak, Mehmet K.; Venkatesan, Ramarathnam

2005-03-01

In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks.

Video Segmentation Using Fast Marching and Region Growing Algorithms

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Eftychis Sifakis

2002-04-01

Full Text Available The algorithm presented in this paper is comprised of three main stages: (1 classification of the image sequence and, in the case of a moving camera, parametric motion estimation, (2 change detection having as reference a fixed frame, an appropriately selected frame or a displaced frame, and (3 object localization using local colour features. The image sequence classification is based on statistical tests on the frame difference. The change detection module uses a two-label fast marching algorithm. Finally, the object localization uses a region growing algorithm based on the colour similarity. Video object segmentation results are shown using the COST 211 data set.

Performance and Complexity Co-evaluation of the Advanced Video Coding Standard for Cost-Effective Multimedia Communications

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Saponara Sergio

2004-01-01

Full Text Available The advanced video codec (AVC standard, recently defined by a joint video team (JVT of ITU-T and ISO/IEC, is introduced in this paper together with its performance and complexity co-evaluation. While the basic framework is similar to the motion-compensated hybrid scheme of previous video coding standards, additional tools improve the compression efficiency at the expense of an increased implementation cost. As a first step to bridge the gap between the algorithmic design of a complex multimedia system and its cost-effective realization, a high-level co-evaluation approach is proposed and applied to a real-life AVC design. An exhaustive analysis of the codec compression efficiency versus complexity (memory and computational costs project space is carried out at the early algorithmic design phase. If all new coding features are used, the improved AVC compression efficiency (up to 50% compared to current video coding technology comes with a complexity increase of a factor 2 for the decoder and larger than one order of magnitude for the encoder. This represents a challenge for resource-constrained multimedia systems such as wireless devices or high-volume consumer electronics. The analysis also highlights important properties of the AVC framework allowing for complexity reduction at the high system level: when combining the new coding features, the implementation complexity accumulates, while the global compression efficiency saturates. Thus, a proper use of the AVC tools maintains the same performance as the most complex configuration while considerably reducing complexity. The reported results provide inputs to assist the profile definition in the standard, highlight the AVC bottlenecks, and select optimal trade-offs between algorithmic performance and complexity.

The Physics of Compressive Sensing and the Gradient-Based Recovery Algorithms

OpenAIRE

Dai, Qi; Sha, Wei

2009-01-01

The physics of compressive sensing (CS) and the gradient-based recovery algorithms are presented. First, the different forms for CS are summarized. Second, the physical meanings of coherence and measurement are given. Third, the gradient-based recovery algorithms and their geometry explanations are provided. Finally, we conclude the report and give some suggestion for future work.

The CCSDS Lossless Data Compression Algorithm for Space Applications

Science.gov (United States)

Yeh, Pen-Shu; Day, John H. (Technical Monitor)

2001-01-01

In the late 80's, when the author started working at the Goddard Space Flight Center (GSFC) for the National Aeronautics and Space Administration (NASA), several scientists there were in the process of formulating the next generation of Earth viewing science instruments, the Moderate Resolution Imaging Spectroradiometer (MODIS). The instrument would have over thirty spectral bands and would transmit enormous data through the communications channel. This was when the author was assigned the task of investigating lossless compression algorithms for space implementation to compress science data in order to reduce the requirement on bandwidth and storage.

Wavelet transform and Huffman coding based electrocardiogram compression algorithm: Application to telecardiology

International Nuclear Information System (INIS)

Chouakri, S A; Djaafri, O; Taleb-Ahmed, A

2013-01-01

We present in this work an algorithm for electrocardiogram (ECG) signal compression aimed to its transmission via telecommunication channel. Basically, the proposed ECG compression algorithm is articulated on the use of wavelet transform, leading to low/high frequency components separation, high order statistics based thresholding, using level adjusted kurtosis value, to denoise the ECG signal, and next a linear predictive coding filter is applied to the wavelet coefficients producing a lower variance signal. This latter one will be coded using the Huffman encoding yielding an optimal coding length in terms of average value of bits per sample. At the receiver end point, with the assumption of an ideal communication channel, the inverse processes are carried out namely the Huffman decoding, inverse linear predictive coding filter and inverse discrete wavelet transform leading to the estimated version of the ECG signal. The proposed ECG compression algorithm is tested upon a set of ECG records extracted from the MIT-BIH Arrhythmia Data Base including different cardiac anomalies as well as the normal ECG signal. The obtained results are evaluated in terms of compression ratio and mean square error which are, respectively, around 1:8 and 7%. Besides the numerical evaluation, the visual perception demonstrates the high quality of ECG signal restitution where the different ECG waves are recovered correctly

General purpose graphic processing unit implementation of adaptive pulse compression algorithms

Science.gov (United States)

Cai, Jingxiao; Zhang, Yan

2017-07-01

This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

Delivering Diagnostic Quality Video over Mobile Wireless Networks for Telemedicine

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Sira P. Rao

2009-01-01

Full Text Available In real-time remote diagnosis of emergency medical events, mobility can be enabled by wireless video communications. However, clinical use of this potential advance will depend on definitive and compelling demonstrations of the reliability of diagnostic quality video. Because the medical domain has its own fidelity criteria, it is important to incorporate diagnostic video quality criteria into any video compression system design. To this end, we used flexible algorithms for region-of-interest (ROI video compression and obtained feedback from medical experts to develop criteria for diagnostically lossless (DL quality. The design of the system occurred in three steps-measurement of bit rate at which DL quality is achieved through evaluation of videos by medical experts, incorporation of that information into a flexible video encoder through the notion of encoder states, and an encoder state update option based on a built-in quality criterion. Medical experts then evaluated our system for the diagnostic quality of the video, allowing us to verify that it is possible to realize DL quality in the ROI at practical communication data transfer rates, enabling mobile medical assessment over bit-rate limited wireless channels. This work lays the scientific foundation for additional validation through prototyped technology, field testing, and clinical trials.

Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

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Zhang, Jin-Yu; Meng, Xiang-Bing; Xu, Wei; Zhang, Wei; Zhang, Yong

2014-01-01

This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method. PMID:24696649

Research on the Compression Algorithm of the Infrared Thermal Image Sequence Based on Differential Evolution and Double Exponential Decay Model

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Jin-Yu Zhang

2014-01-01

Full Text Available This paper has proposed a new thermal wave image sequence compression algorithm by combining double exponential decay fitting model and differential evolution algorithm. This study benchmarked fitting compression results and precision of the proposed method was benchmarked to that of the traditional methods via experiment; it investigated the fitting compression performance under the long time series and improved model and validated the algorithm by practical thermal image sequence compression and reconstruction. The results show that the proposed algorithm is a fast and highly precise infrared image data processing method.

DMPDS: A Fast Motion Estimation Algorithm Targeting High Resolution Videos and Its FPGA Implementation

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Gustavo Sanchez

2012-01-01

Full Text Available This paper presents a new fast motion estimation (ME algorithm targeting high resolution digital videos and its efficient hardware architecture design. The new Dynamic Multipoint Diamond Search (DMPDS algorithm is a fast algorithm which increases the ME quality when compared with other fast ME algorithms. The DMPDS achieves a better digital video quality reducing the occurrence of local minima falls, especially in high definition videos. The quality results show that the DMPDS is able to reach an average PSNR gain of 1.85 dB when compared with the well-known Diamond Search (DS algorithm. When compared to the optimum results generated by the Full Search (FS algorithm the DMPDS shows a lose of only 1.03 dB in the PSNR. On the other hand, the DMPDS reached a complexity reduction higher than 45 times when compared to FS. The quality gains related to DS caused an expected increase in the DMPDS complexity which uses 6.4-times more calculations than DS. The DMPDS architecture was designed focused on high performance and low cost, targeting to process Quad Full High Definition (QFHD videos in real time (30 frames per second. The architecture was described in VHDL and synthesized to Altera Stratix 4 and Xilinx Virtex 5 FPGAs. The synthesis results show that the architecture is able to achieve processing rates higher than 53 QFHD fps, reaching the real-time requirements. The DMPDS architecture achieved the highest processing rate when compared to related works in the literature. This high processing rate was obtained designing an architecture with a high operation frequency and low numbers of cycles necessary to process each block.

The Modified Frequency Algorithm of Digital Watermarking of Still Images Resistant to JPEG Compression

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V. A. Batura

2015-01-01

Full Text Available Digital watermarking is an effective copyright protection for multimedia products (in particular, still images. Digital marking represents process of embedding into object of protection of a digital watermark which is invisible for a human eye. However there is rather large number of the harmful influences capable to destroy the watermark which is embedded into the still image. The most widespread attack is JPEG compression that is caused by efficiency of this format of compression and its big prevalence on the Internet.The new algorithm which is modification of algorithm of Elham is presented in the present article. The algorithm of digital marking of motionless images carries out embedding of a watermark in frequency coefficients of discrete Hadamard transform of the chosen image blocks. The choice of blocks of the image for embedding of a digital watermark is carried out on the basis of the set threshold of entropy of pixels. The choice of low-frequency coefficients for embedding is carried out on the basis of comparison of values of coefficients of discrete cosine transformation with a predetermined threshold, depending on the product of the built-in watermark coefficient on change coefficient.Resistance of new algorithm to compression of JPEG, noising, filtration, change of color, the size and histogram equalization is in details analysed. Research of algorithm consists in comparison of the appearance taken from the damaged image of a watermark with the introduced logo. Ability of algorithm to embedding of a watermark with a minimum level of distortions of the image is in addition analysed. It is established that the new algorithm in comparison by initial algorithm of Elham showed full resistance to compression of JPEG, and also the improved resistance to a noising, change of brightness and histogram equalization.The developed algorithm can be used for copyright protection on the static images. Further studies will be used to study the

Shot Boundary Detection in Soccer Video using Twin-comparison Algorithm and Dominant Color Region

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Matko Šarić

2008-06-01

Full Text Available The first step in generic video processing is temporal segmentation, i.e. shot boundary detection. Camera shot transitions can be either abrupt (e.g. cuts or gradual (e.g. fades, dissolves, wipes. Sports video is one of the most challenging domains for robust shot boundary detection. We proposed a shot boundary detection algorithm for soccer video based on the twin-comparison method and the absolute difference between frames in their ratios of dominant colored pixels to total number of pixels. With this approach the detection of gradual transitions is improved by decreasing the number of false positives caused by some camera operations. We also compared performances of our algorithm and the standard twin-comparison method.

An Algorithm to Compress Line-transition Data for Radiative-transfer Calculations

Science.gov (United States)

Cubillos, Patricio E.

2017-11-01

Molecular line-transition lists are an essential ingredient for radiative-transfer calculations. With recent databases now surpassing the billion-line mark, handling them has become computationally prohibitive, due to both the required processing power and memory. Here I present a temperature-dependent algorithm to separate strong from weak line transitions, reformatting the large majority of the weaker lines into a cross-section data file, and retaining the detailed line-by-line information of the fewer strong lines. For any given molecule over the 0.3-30 μm range, this algorithm reduces the number of lines to a few million, enabling faster radiative-transfer computations without a significant loss of information. The final compression rate depends on how densely populated the spectrum is. I validate this algorithm by comparing Exomol’s HCN extinction-coefficient spectra between the complete (65 million line transitions) and compressed (7.7 million) line lists. Over the 0.6-33 μm range, the average difference between extinction-coefficient values is less than 1%. A Python/C implementation of this algorithm is open-source and available at https://github.com/pcubillos/repack. So far, this code handles the Exomol and HITRAN line-transition format.

A Multiresolution Image Completion Algorithm for Compressing Digital Color Images

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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.

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

Science.gov (United States)

Khan, Tareq H.; Wahid, Khan A.

2014-01-01

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

An optimized compression algorithm for real-time ECG data transmission in wireless network of medical information systems.

Science.gov (United States)

Cho, Gyoun-Yon; Lee, Seo-Joon; Lee, Tae-Ro

2015-01-01

Recent medical information systems are striving towards real-time monitoring models to care patients anytime and anywhere through ECG signals. However, there are several limitations such as data distortion and limited bandwidth in wireless communications. In order to overcome such limitations, this research focuses on compression. Few researches have been made to develop a specialized compression algorithm for ECG data transmission in real-time monitoring wireless network. Not only that, recent researches' algorithm is not appropriate for ECG signals. Therefore this paper presents a more developed algorithm EDLZW for efficient ECG data transmission. Results actually showed that the EDLZW compression ratio was 8.66, which was a performance that was 4 times better than any other recent compression method widely used today.

Experimental Study of Concealment Data in Video Sequences MPEG-2

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A. A. Alimov

2011-03-01

Full Text Available MPEG-2 uses video compression with loses based on the use of discrete cosine transformation (DCT to small blocks of encoded image. As a result, there is range of factors, each of which corresponds to a frequency index of the encoded block. The human eye, due to natural approximation, does not perceive the difference when the high-frequency DCT coefficients change. The investigated algorithm uses this feature of the human vision to embed required data in video stream invisibly.

Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2016-05-01

Motion video analysis is a challenging task, particularly if real-time analysis is required. It is therefore an important issue how to provide suitable assistance for the human operator. Given that the use of customized video analysis systems is more and more established, one supporting measure is to provide system functions which perform subtasks of the analysis. Recent progress in the development of automated image exploitation algorithms allow, e.g., real-time moving target tracking. Another supporting measure is to provide a user interface which strives to reduce the perceptual, cognitive and motor load of the human operator for example by incorporating the operator's visual focus of attention. A gaze-enhanced user interface is able to help here. This work extends prior work on automated target recognition, segmentation, and tracking algorithms as well as about the benefits of a gaze-enhanced user interface for interaction with moving targets. We also propose a prototypical system design aiming to combine both the qualities of the human observer's perception and the automated algorithms in order to improve the overall performance of a real-time video analysis system. In this contribution, we address two novel issues analyzing gaze-based interaction with target tracking algorithms. The first issue extends the gaze-based triggering of a target tracking process, e.g., investigating how to best relaunch in the case of track loss. The second issue addresses the initialization of tracking algorithms without motion segmentation where the operator has to provide the system with the object's image region in order to start the tracking algorithm.

Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder

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Chan-seob Park

2014-01-01

Full Text Available The joint collaborative team on video coding (JCT-VC is developing the next-generation video coding standard which is called high efficiency video coding (HEVC. In the HEVC, there are three units in block structure: coding unit (CU, prediction unit (PU, and transform unit (TU. The CU is the basic unit of region splitting like macroblock (MB. Each CU performs recursive splitting into four blocks with equal size, starting from the tree block. In this paper, we propose a fast CU depth decision algorithm for HEVC technology to reduce its computational complexity. In 2N×2N PU, the proposed method compares the rate-distortion (RD cost and determines the depth using the compared information. Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. Experimental result shows that the proposed algorithm achieves the average time-saving factor of 44.84% in the random access (RA at Main profile configuration with the HEVC test model (HM 10.0 reference software. Compared to HM 10.0 encoder, a small BD-bitrate loss of 0.17% is also observed without significant loss of image quality.

Reconfigurable Secure Video Codec Based on DWT and AES Processor

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Rached Tourki

2010-01-01

Full Text Available In this paper, we proposed a secure video codec based on the discrete wavelet transformation (DWT and the Advanced Encryption Standard (AES processor. Either, use of video coding with DWT or encryption using AES is well known. However, linking these two designs to achieve secure video coding is leading. The contributions of our work are as follows. First, a new method for image and video compression is proposed. This codec is a synthesis of JPEG and JPEG2000,which is implemented using Huffman coding to the JPEG and DWT to the JPEG2000. Furthermore, an improved motion estimation algorithm is proposed. Second, the encryptiondecryption effects are achieved by the AES processor. AES is aim to encrypt group of LL bands. The prominent feature of this method is an encryption of LL bands by AES-128 (128-bit keys, or AES-192 (192-bit keys, or AES-256 (256-bit keys.Third, we focus on a method that implements partial encryption of LL bands. Our approach provides considerable levels of security (key size, partial encryption, mode encryption, and has very limited adverse impact on the compression efficiency. The proposed codec can provide up to 9 cipher schemes within a reasonable software cost. Latency, correlation, PSNR and compression rate results are analyzed and shown.

Spatial correlation genetic algorithm for fractal image compression

International Nuclear Information System (INIS)

Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

2006-01-01

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

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.

Reconstruction algorithm in compressed sensing based on maximum a posteriori estimation

International Nuclear Information System (INIS)

Takeda, Koujin; Kabashima, Yoshiyuki

2013-01-01

We propose a systematic method for constructing a sparse data reconstruction algorithm in compressed sensing at a relatively low computational cost for general observation matrix. It is known that the cost of ℓ 1 -norm minimization using a standard linear programming algorithm is O(N 3 ). We show that this cost can be reduced to O(N 2 ) by applying the approach of posterior maximization. Furthermore, in principle, the algorithm from our approach is expected to achieve the widest successful reconstruction region, which is evaluated from theoretical argument. We also discuss the relation between the belief propagation-based reconstruction algorithm introduced in preceding works and our approach

Dynamic video encryption algorithm for H.264/AVC based on a spatiotemporal chaos system.

Science.gov (United States)

Xu, Hui; Tong, Xiao-Jun; Zhang, Miao; Wang, Zhu; Li, Ling-Hao

2016-06-01

Video encryption schemes mostly employ the selective encryption method to encrypt parts of important and sensitive video information, aiming to ensure the real-time performance and encryption efficiency. The classic block cipher is not applicable to video encryption due to the high computational overhead. In this paper, we propose the encryption selection control module to encrypt video syntax elements dynamically which is controlled by the chaotic pseudorandom sequence. A novel spatiotemporal chaos system and binarization method is used to generate a key stream for encrypting the chosen syntax elements. The proposed scheme enhances the resistance against attacks through the dynamic encryption process and high-security stream cipher. Experimental results show that the proposed method exhibits high security and high efficiency with little effect on the compression ratio and time cost.

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

Science.gov (United States)

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

2010-03-01

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

A Robust Parallel Algorithm for Combinatorial Compressed Sensing

Science.gov (United States)

Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian

2018-04-01

In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

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...

ITERATION FREE FRACTAL COMPRESSION USING GENETIC ALGORITHM FOR STILL COLOUR IMAGES

Directory of Open Access Journals (Sweden)

A.R. Nadira Banu Kamal

2014-02-01

Full Text Available The storage requirements for images can be excessive, if true color and a high-perceived image quality are desired. An RGB image may be viewed as a stack of three gray-scale images that when fed into the red, green and blue inputs of a color monitor, produce a color image on the screen. The abnormal size of many images leads to long, costly, transmission times. Hence, an iteration free fractal algorithm is proposed in this research paper to design an efficient search of the domain pools for colour image compression using Genetic Algorithm (GA. The proposed methodology reduces the coding process time and intensive computation tasks. Parameters such as image quality, compression ratio and coding time are analyzed. It is observed that the proposed method achieves excellent performance in image quality with reduction in storage space.

Video game for learning and metaphorization of recursive algorithms

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Ricardo Inacio Alvares Silva

2013-09-01

Full Text Available The learning of recursive algorithms in computer programming is problematic, because its execution and resolution is not natural to the thinking way people are trained and used to since young. As with other topics in algorithms, we use metaphors to make parallels between the abstract and the concrete to help in understanding the operation of recursive algorithms. However, the classic metaphors employed in this area, such as calculating factorial recursively and Towers of Hanoi game, may just confuse more or be insufficient. In this work, we produced a computer game to assist students in computer courses in learning recursive algorithms. It was designed to have regular video game characteristics, with narrative and classical gameplay elements, commonly found in this kind of product. Aiding to education occurs through metaphorization, or in other words, through experiences provided by game situations that refer to recursive algorithms. To this end, we designed and imbued in the game four valid metaphors related to the theory, and other minor references to the subject.

High Definition Video Streaming Using H.264 Video Compression

OpenAIRE

Bechqito, Yassine

2009-01-01

This thesis presents high definition video streaming using H.264 codec implementation. The experiment carried out in this study was done for an offline streaming video but a model for live high definition streaming is introduced, as well. Prior to the actual experiment, this study describes digital media streaming. Also, the different technologies involved in video streaming are covered. These include streaming architecture and a brief overview on H.264 codec as well as high definition t...

Compressive Online Robust Principal Component Analysis with Multiple Prior Information

DEFF Research Database (Denmark)

Van Luong, Huynh; Deligiannis, Nikos; Seiler, Jürgen

-rank components. Unlike conventional batch RPCA, which processes all the data directly, our method considers a small set of measurements taken per data vector (frame). Moreover, our method incorporates multiple prior information signals, namely previous reconstructed frames, to improve these paration...... and thereafter, update the prior information for the next frame. Using experiments on synthetic data, we evaluate the separation performance of the proposed algorithm. In addition, we apply the proposed algorithm to online video foreground and background separation from compressive measurements. The results show...

VIDEO DENOISING USING SWITCHING ADAPTIVE DECISION BASED ALGORITHM WITH ROBUST MOTION ESTIMATION TECHNIQUE

Directory of Open Access Journals (Sweden)

V. Jayaraj

2010-08-01

Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.

Evaluation of a wavelet-based compression algorithm applied to the silicon drift detectors data of the ALICE experiment at CERN

International Nuclear Information System (INIS)

Falchieri, Davide; Gandolfi, Enzo; Masotti, Matteo

2004-01-01

This paper evaluates the performances of a wavelet-based compression algorithm applied to the data produced by the silicon drift detectors of the ALICE experiment at CERN. This compression algorithm is a general purpose lossy technique, in other words, its application could prove useful even on a wide range of other data reduction's problems. In particular the design targets relevant for our wavelet-based compression algorithm are the following ones: a high-compression coefficient, a reconstruction error as small as possible and a very limited execution time. Interestingly, the results obtained are quite close to the ones achieved by the algorithm implemented in the first prototype of the chip CARLOS, the chip that will be used in the silicon drift detectors readout chain

A new chest compression depth feedback algorithm for high-quality CPR based on smartphone.

Science.gov (United States)

Song, Yeongtak; Oh, Jaehoon; Chee, Youngjoon

2015-01-01

Although many smartphone application (app) programs provide education and guidance for basic life support, they do not commonly provide feedback on the chest compression depth (CCD) and rate. The validation of its accuracy has not been reported to date. This study was a feasibility assessment of use of the smartphone as a CCD feedback device. In this study, we proposed the concept of a new real-time CCD estimation algorithm using a smartphone and evaluated the accuracy of the algorithm. Using the double integration of the acceleration signal, which was obtained from the accelerometer in the smartphone, we estimated the CCD in real time. Based on its periodicity, we removed the bias error from the accelerometer. To evaluate this instrument's accuracy, we used a potentiometer as the reference depth measurement. The evaluation experiments included three levels of CCD (insufficient, adequate, and excessive) and four types of grasping orientations with various compression directions. We used the difference between the reference measurement and the estimated depth as the error. The error was calculated for each compression. When chest compressions were performed with adequate depth for the patient who was lying on a flat floor, the mean (standard deviation) of the errors was 1.43 (1.00) mm. When the patient was lying on an oblique floor, the mean (standard deviation) of the errors was 3.13 (1.88) mm. The error of the CCD estimation was tolerable for the algorithm to be used in the smartphone-based CCD feedback app to compress more than 51 mm, which is the 2010 American Heart Association guideline.

Quality of Experience Assessment of Video Quality in Social Clouds

Directory of Open Access Journals (Sweden)

Asif Ali Laghari

2017-01-01

Full Text Available Video sharing on social clouds is popular among the users around the world. High-Definition (HD videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS. Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE level of end users. To assess the QoE of video compression, we conducted subjective (QoE experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

Low-Complexity Hierarchical Mode Decision Algorithms Targeting VLSI Architecture Design for the H.264/AVC Video Encoder

Directory of Open Access Journals (Sweden)

Guilherme Corrêa

2012-01-01

Full Text Available In H.264/AVC, the encoding process can occur according to one of the 13 intraframe coding modes or according to one of the 8 available interframes block sizes, besides the SKIP mode. In the Joint Model reference software, the choice of the best mode is performed through exhaustive executions of the entire encoding process, which significantly increases the encoder's computational complexity and sometimes even forbids its use in real-time applications. Considering this context, this work proposes a set of heuristic algorithms targeting hardware architectures that lead to earlier selection of one encoding mode. The amount of repetitions of the encoding process is reduced by 47 times, at the cost of a relatively small cost in compression performance. When compared to other works, the fast hierarchical mode decision results are expressively more satisfactory in terms of computational complexity reduction, quality, and bit rate. The low-complexity mode decision architecture proposed is thus a very good option for real-time coding of high-resolution videos. The solution is especially interesting for embedded and mobile applications with support to multimedia systems, since it yields good compression rates and image quality with a very high reduction in the encoder complexity.

CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

Science.gov (United States)

Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

2014-01-01

We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

Medical video server construction.

Science.gov (United States)

Dańda, Jacek; Juszkiewicz, Krzysztof; Leszczuk, Mikołaj; Loziak, Krzysztof; Papir, Zdzisław; Sikora, Marek; Watza, Rafal

2003-01-01

The paper discusses two implementation options for a Digital Video Library, a repository used for archiving, accessing, and browsing of video medical records. Two crucial issues to be decided on are a video compression format and a video streaming platform. The paper presents numerous decision factors that have to be taken into account. The compression formats being compared are DICOM as a format representative for medical applications, both MPEGs, and several new formats targeted for an IP networking. The comparison includes transmission rates supported, compression rates, and at least options for controlling a compression process. The second part of the paper presents the ISDN technique as a solution for provisioning of tele-consultation services between medical parties that are accessing resources uploaded to a digital video library. There are several backbone techniques (like corporate LANs/WANs, leased lines or even radio/satellite links) available, however, the availability of network resources for hospitals was the prevailing choice criterion pointing to ISDN solutions. Another way to provide access to the Digital Video Library is based on radio frequency domain solutions. The paper describes possibilities of both, wireless and cellular network's data transmission service to be used as a medical video server transport layer. For the cellular net-work based solution two communication techniques are used: Circuit Switched Data and Packet Switched Data.

Novel prediction- and subblock-based algorithm for fractal image compression

International Nuclear Information System (INIS)

Chung, K.-L.; Hsu, C.-H.

2006-01-01

Fractal encoding is the most consuming part in fractal image compression. In this paper, a novel two-phase prediction- and subblock-based fractal encoding algorithm is presented. Initially the original gray image is partitioned into a set of variable-size blocks according to the S-tree- and interpolation-based decomposition principle. In the first phase, each current block of variable-size range block tries to find the best matched domain block based on the proposed prediction-based search strategy which utilizes the relevant neighboring variable-size domain blocks. The first phase leads to a significant computation-saving effect. If the domain block found within the predicted search space is unacceptable, in the second phase, a subblock strategy is employed to partition the current variable-size range block into smaller blocks to improve the image quality. Experimental results show that our proposed prediction- and subblock-based fractal encoding algorithm outperforms the conventional full search algorithm and the recently published spatial-correlation-based algorithm by Truong et al. in terms of encoding time and image quality. In addition, the performance comparison among our proposed algorithm and the other two algorithms, the no search-based algorithm and the quadtree-based algorithm, are also investigated

Enhancement system of nighttime infrared video image and visible video image

Science.gov (United States)

Wang, Yue; Piao, Yan

2016-11-01

Visibility of Nighttime video image has a great significance for military and medicine areas, but nighttime video image has so poor quality that we can't recognize the target and background. Thus we enhance the nighttime video image by fuse infrared video image and visible video image. According to the characteristics of infrared and visible images, we proposed improved sift algorithm andαβ weighted algorithm to fuse heterologous nighttime images. We would deduced a transfer matrix from improved sift algorithm. The transfer matrix would rapid register heterologous nighttime images. And theαβ weighted algorithm can be applied in any scene. In the video image fusion system, we used the transfer matrix to register every frame and then used αβ weighted method to fuse every frame, which reached the time requirement soft video. The fused video image not only retains the clear target information of infrared video image, but also retains the detail and color information of visible video image and the fused video image can fluency play.

Self-aligning and compressed autosophy video databases

Science.gov (United States)

Holtz, Klaus E.

1993-04-01

Autosophy, an emerging new science, explains `self-assembling structures,' such as crystals or living trees, in mathematical terms. This research provides a new mathematical theory of `learning' and a new `information theory' which permits the growing of self-assembling data network in a computer memory similar to the growing of `data crystals' or `data trees' without data processing or programming. Autosophy databases are educated very much like a human child to organize their own internal data storage. Input patterns, such as written questions or images, are converted to points in a mathematical omni dimensional hyperspace. The input patterns are then associated with output patterns, such as written answers or images. Omni dimensional information storage will result in enormous data compression because each pattern fragment is only stored once. Pattern recognition in the text or image files is greatly simplified by the peculiar omni dimensional storage method. Video databases will absorb input images from a TV camera and associate them with textual information. The `black box' operations are totally self-aligning where the input data will determine their own hyperspace storage locations. Self-aligning autosophy databases may lead to a new generation of brain-like devices.

Algorithms for the automatic identification of MARFEs and UFOs in JET database of visible camera videos

International Nuclear Information System (INIS)

Murari, A.; Camplani, M.; Cannas, B.; Usai, P.; Mazon, D.; Delaunay, F.

2010-01-01

MARFE instabilities and UFOs leave clear signatures in JET fast visible camera videos. Given the potential harmful consequences of these events, particularly as triggers of disruptions, it would be important to have the means of detecting them automatically. In this paper, the results of various algorithms to identify automatically the MARFEs and UFOs in JET visible videos are reported. The objective is to retrieve the videos, which have captured these events, exploring the whole JET database of images, as a preliminary step to the development of real-time identifiers in the future. For the detection of MARFEs, a complete identifier has been finalized, using morphological operators and Hu moments. The final algorithm manages to identify the videos with MARFEs with a success rate exceeding 80%. Due to the lack of a complete statistics of examples, the UFO identifier is less developed, but a preliminary code can detect UFOs quite reliably. (authors)

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

Science.gov (United States)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

The effects of scene characteristics, resolution, and compression on the ability to recognize objects in video

Science.gov (United States)

Dumke, Joel; Ford, Carolyn G.; Stange, Irena W.

2011-03-01

Public safety practitioners increasingly use video for object recognition tasks. These end users need guidance regarding how to identify the level of video quality necessary for their application. The quality of video used in public safety applications must be evaluated in terms of its usability for specific tasks performed by the end user. The Public Safety Communication Research (PSCR) project performed a subjective test as one of the first in a series to explore visual intelligibility in video-a user's ability to recognize an object in a video stream given various conditions. The test sought to measure the effects on visual intelligibility of three scene parameters (target size, scene motion, scene lighting), several compression rates, and two resolutions (VGA (640x480) and CIF (352x288)). Seven similarly sized objects were used as targets in nine sets of near-identical source scenes, where each set was created using a different combination of the parameters under study. Viewers were asked to identify the objects via multiple choice questions. Objective measurements were performed on each of the scenes, and the ability of the measurement to predict visual intelligibility was studied.

Simultaneous optical image compression and encryption using error-reduction phase retrieval algorithm

International Nuclear Information System (INIS)

Liu, Wei; Liu, Shutian; Liu, Zhengjun

2015-01-01

We report a simultaneous image compression and encryption scheme based on solving a typical optical inverse problem. The secret images to be processed are multiplexed as the input intensities of a cascaded diffractive optical system. At the output plane, a compressed complex-valued data with a lot fewer measurements can be obtained by utilizing error-reduction phase retrieval algorithm. The magnitude of the output image can serve as the final ciphertext while its phase serves as the decryption key. Therefore the compression and encryption are simultaneously completed without additional encoding and filtering operations. The proposed strategy can be straightforwardly applied to the existing optical security systems that involve diffraction and interference. Numerical simulations are performed to demonstrate the validity and security of the proposal. (paper)

Handling the data management needs of high-throughput sequencing data: SpeedGene, a compression algorithm for the efficient storage of genetic data

Science.gov (United States)

2012-01-01

Background As Next-Generation Sequencing data becomes available, existing hardware environments do not provide sufficient storage space and computational power to store and process the data due to their enormous size. This is and will be a frequent problem that is encountered everyday by researchers who are working on genetic data. There are some options available for compressing and storing such data, such as general-purpose compression software, PBAT/PLINK binary format, etc. However, these currently available methods either do not offer sufficient compression rates, or require a great amount of CPU time for decompression and loading every time the data is accessed. Results Here, we propose a novel and simple algorithm for storing such sequencing data. We show that, the compression factor of the algorithm ranges from 16 to several hundreds, which potentially allows SNP data of hundreds of Gigabytes to be stored in hundreds of Megabytes. We provide a C++ implementation of the algorithm, which supports direct loading and parallel loading of the compressed format without requiring extra time for decompression. By applying the algorithm to simulated and real datasets, we show that the algorithm gives greater compression rate than the commonly used compression methods, and the data-loading process takes less time. Also, The C++ library provides direct-data-retrieving functions, which allows the compressed information to be easily accessed by other C++ programs. Conclusions The SpeedGene algorithm enables the storage and the analysis of next generation sequencing data in current hardware environment, making system upgrades unnecessary. PMID:22591016

Content Adaptive True Motion Estimator for H.264 Video Compression

Directory of Open Access Journals (Sweden)

P. Kulla

2007-12-01

Full Text Available Content adaptive true motion estimator for H.264 video coding is a fast block-based matching estimator with implemented multi-stage approach to estimate motion fields between two image frames. It considers the theory of 3D scene objects projection into 2D image plane for selection of motion vector candidates from the higher stages. The stages of the algorithm and its hierarchy are defined upon motion estimation reliability measurement (image blocks including two different directions of spatial gradient, blocks with one dominant spatial gradient and blocks including minimal spatial gradient. Parameters of the image classification into stages are set adaptively upon image structure. Due to search strategy are the estimated motion fields more corresponding to a true motion in an image sequence as in the case of conventional motion estimation algorithms that use fixed sets of motion vector candidates from tight neighborhood.

Study of Temporal Effects on Subjective Video Quality of Experience.

Science.gov (United States)

Bampis, Christos George; Zhi Li; Moorthy, Anush Krishna; Katsavounidis, Ioannis; Aaron, Anne; Bovik, Alan Conrad

2017-11-01

HTTP adaptive streaming is being increasingly deployed by network content providers, such as Netflix and YouTube. By dividing video content into data chunks encoded at different bitrates, a client is able to request the appropriate bitrate for the segment to be played next based on the estimated network conditions. However, this can introduce a number of impairments, including compression artifacts and rebuffering events, which can severely impact an end-user's quality of experience (QoE). We have recently created a new video quality database, which simulates a typical video streaming application, using long video sequences and interesting Netflix content. Going beyond previous efforts, the new database contains highly diverse and contemporary content, and it includes the subjective opinions of a sizable number of human subjects regarding the effects on QoE of both rebuffering and compression distortions. We observed that rebuffering is always obvious and unpleasant to subjects, while bitrate changes may be less obvious due to content-related dependencies. Transient bitrate drops were preferable over rebuffering only on low complexity video content, while consistently low bitrates were poorly tolerated. We evaluated different objective video quality assessment algorithms on our database and found that objective video quality models are unreliable for QoE prediction on videos suffering from both rebuffering events and bitrate changes. This implies the need for more general QoE models that take into account objective quality models, rebuffering-aware information, and memory. The publicly available video content as well as metadata for all of the videos in the new database can be found at http://live.ece.utexas.edu/research/LIVE_NFLXStudy/nflx_index.html.

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

Science.gov (United States)

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

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

Science.gov (United States)

Gunay, Omer; Ozsarac, Ismail; Kamisli, Fatih

2017-05-01

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

32Still Image Compression Algorithm Based on Directional Filter Banks

OpenAIRE

Chunling Yang; Duanwu Cao; Li Ma

2010-01-01

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

High Dynamic Range Video

CERN Document Server

Myszkowski, Karol

2008-01-01

This book presents a complete pipeline forHDR image and video processing fromacquisition, through compression and quality evaluation, to display. At the HDR image and video acquisition stage specialized HDR sensors or multi-exposure techniques suitable for traditional cameras are discussed. Then, we present a practical solution for pixel values calibration in terms of photometric or radiometric quantities, which are required in some technically oriented applications. Also, we cover the problem of efficient image and video compression and encoding either for storage or transmission purposes, in

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

Energy Technology Data Exchange (ETDEWEB)

Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch [University of Applied Sciences and Arts Northwestern Switzerland FHNW, 5210 Windisch (Switzerland)

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

Science.gov (United States)

Felix, Simon; Bolzern, Roman; Battaglia, Marina

2017-11-01

One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

Science.gov (United States)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Voit, Michael; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2017-05-01

Real-time motion video analysis is a challenging and exhausting task for the human observer, particularly in safety and security critical domains. Hence, customized video analysis systems providing functions for the analysis of subtasks like motion detection or target tracking are welcome. While such automated algorithms relieve the human operators from performing basic subtasks, they impose additional interaction duties on them. Prior work shows that, e.g., for interaction with target tracking algorithms, a gaze-enhanced user interface is beneficial. In this contribution, we present an investigation on interaction with an independent motion detection (IDM) algorithm. Besides identifying an appropriate interaction technique for the user interface - again, we compare gaze-based and traditional mouse-based interaction - we focus on the benefit an IDM algorithm might provide for an UAS video analyst. In a pilot study, we exposed ten subjects to the task of moving target detection in UAS video data twice, once performing with automatic support, once performing without it. We compare the two conditions considering performance in terms of effectiveness (correct target selections). Additionally, we report perceived workload (measured using the NASA-TLX questionnaire) and user satisfaction (measured using the ISO 9241-411 questionnaire). The results show that a combination of gaze input and automated IDM algorithm provides valuable support for the human observer, increasing the number of correct target selections up to 62% and reducing workload at the same time.

Towards the compression of parton densities through machine learning algorithms

CERN Document Server

Carrazza, Stefano

2016-01-01

One of the most fascinating challenges in the context of parton density function (PDF) is the determination of the best combined PDF uncertainty from individual PDF sets. Since 2014 multiple methodologies have been developed to achieve this goal. In this proceedings we first summarize the strategy adopted by the PDF4LHC15 recommendation and then, we discuss about a new approach to Monte Carlo PDF compression based on clustering through machine learning algorithms.

The formation of spiral galaxies: adiabatic compression with Young's algorithm and the relation of dark matter haloes to their primordial antecedents

NARCIS (Netherlands)

Katz, Harley; McGaugh, Stacy S.; Sellwood, J. A.; de Blok, W. J. G.

We utilize Young's algorithm to model the adiabatic compression of the dark matter haloes of galaxies in the THINGS survey to determine the relationship between the halo fit to the rotation curve and the corresponding primordial halo prior to compression. Young's algorithm conserves radial action

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

International Nuclear Information System (INIS)

Tang Jie; Nett, Brian E; Chen Guanghong

2009-01-01

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

Algoritmi selektivnog šifrovanja - pregled sa ocenom performansi / Selective encryption algorithms: Overview with performance evaluation

Directory of Open Access Journals (Sweden)

Boriša Ž. Jovanović

2010-10-01

Full Text Available Digitalni multimedijalni sadržaj postaje zastupljeniji i sve više se razmenjuje putem računarskih mreža i javnih kanala (satelitske komunikacije, bežične mreže, internet, itd. koji predstavljaju nebezbedne medijume za prenos informacija osetljive sadržine. Sve više na značaju dobijaju mehanizmi kriptološke zaštite slika i video sadržaja. Tradicionalni sistemi kriptografske obrade u sistemima za prenos ovih vrsta informacija garantuju visok stepen sigurnosti, ali i imaju svoje nedostatke - visoku cenu implementacije i znatno kašnjenje u prenosu podataka. Pomenuti nedostaci se prevazilaze primenom algoritama selektivnog šifrovanja. / Digital multimedia content is becoming widely used and increasingly exchanged over computer network and public channels (satelite, wireless networks, Internet, etc. which is unsecured transmission media for ex changing that kind of information. Mechanisms made to encrypt image and video data are becoming more and more significant. Traditional cryptographic techniques can guarantee a high level of security but at the cost of expensive implementation and important transmission delays. These shortcomings can be exceeded using selective encryption algorithms. Introduction In traditional image and video content protection schemes, called fully layered, the whole content is first compressed. Then, the compressed bitstream is entirely encrypted using a standard cipher (DES - Data Encryption Algorithm, IDEA - International Data Encryption Algorithm, AES - Advanced Encryption Algorithm etc.. The specific characteristics of this kind of data, high-transmission rate with limited bandwidth, make standard encryption algorithms inadequate. Another limitation of traditional systems consists of altering the whole bitstream syntax which may disable some codec functionalities on the delivery site coder and decoder on the receiving site. Selective encryption is a new trend in image and video content protection. As its

Digital video transcoding for transmission and storage

CERN Document Server

Sun, Huifang; Chen, Xuemin

2004-01-01

Professionals in the video and multimedia industries need a book that explains industry standards for video coding and how to convert the compressed information between standards. Digital Video Transcoding for Transmission and Storage answers this demand while also supplying the theories and principles of video compression and transcoding technologies. Emphasizing digital video transcoding techniques, this book summarizes its content via examples of practical methods for transcoder implementation. It relates almost all of its featured transcoding technologies to practical applications.This vol

The art of assessing quality for images and video

International Nuclear Information System (INIS)

Deriche, M.

2011-01-01

The early years of this century have witnessed a tremendous growth in the use of digital multimedia data for di?erent communication applications. Researchers from around the world are spending substantial research efforts in developing techniques for improving the appearance of images/video. However, as we know, preserving high quality is a challenging task. Images are subject to distortions during acquisition, compression, transmission, analysis, and reconstruction. For this reason, the research area focusing on image and video quality assessment has attracted a lot of attention in recent years. In particular, compression applications and other multimedia applications need powerful techniques for evaluating quality objectively without human interference. This tutorial will cover the di?erent faces of image quality assessment. We will motivate the need for robust image quality assessment techniques, then discuss the main algorithms found in the literature with a critical perspective. We will present the di?erent metrics used for full reference, reduced reference and no reference applications. We will then discuss the difference between image and video quality assessment. In all of the above, we will take a critical approach to explain which metric can be used for which application. Finally we will discuss the different approaches to analyze the performance of image/video quality metrics, and end the tutorial with some perspectives on newly introduced metrics and their potential applications.

Non-US data compression and coding research. FASAC Technical Assessment Report

Energy Technology Data Exchange (ETDEWEB)

Gray, R.M.; Cohn, M.; Craver, L.W.; Gersho, A.; Lookabaugh, T.; Pollara, F.; Vetterli, M.

1993-11-01

This assessment of recent data compression and coding research outside the United States examines fundamental and applied work in the basic areas of signal decomposition, quantization, lossless compression, and error control, as well as application development efforts in image/video compression and speech/audio compression. Seven computer scientists and engineers who are active in development of these technologies in US academia, government, and industry carried out the assessment. Strong industrial and academic research groups in Western Europe, Israel, and the Pacific Rim are active in the worldwide search for compression algorithms that provide good tradeoffs among fidelity, bit rate, and computational complexity, though the theoretical roots and virtually all of the classical compression algorithms were developed in the United States. Certain areas, such as segmentation coding, model-based coding, and trellis-coded modulation, have developed earlier or in more depth outside the United States, though the United States has maintained its early lead in most areas of theory and algorithm development. Researchers abroad are active in other currently popular areas, such as quantizer design techniques based on neural networks and signal decompositions based on fractals and wavelets, but, in most cases, either similar research is or has been going on in the United States, or the work has not led to useful improvements in compression performance. Because there is a high degree of international cooperation and interaction in this field, good ideas spread rapidly across borders (both ways) through international conferences, journals, and technical exchanges. Though there have been no fundamental data compression breakthroughs in the past five years--outside or inside the United State--there have been an enormous number of significant improvements in both places in the tradeoffs among fidelity, bit rate, and computational complexity.

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.

Multiple Moving Object Detection for Fast Video Content Description in Compressed Domain

Directory of Open Access Journals (Sweden)

Boris Mansencal

2007-11-01

Full Text Available Indexing deals with the automatic extraction of information with the objective of automatically describing and organizing the content. Thinking of a video stream, different types of information can be considered semantically important. Since we can assume that the most relevant one is linked to the presence of moving foreground objects, their number, their shape, and their appearance can constitute a good mean for content description. For this reason, we propose to combine both motion information and region-based color segmentation to extract moving objects from an MPEG2 compressed video stream starting only considering low-resolution data. This approach, which we refer to as “rough indexing,” consists in processing P-frame motion information first, and then in performing I-frame color segmentation. Next, since many details can be lost due to the low-resolution data, to improve the object detection results, a novel spatiotemporal filtering has been developed which is constituted by a quadric surface modeling the object trace along time. This method enables to effectively correct possible former detection errors without heavily increasing the computational effort.

Supplementary Material for: Compressing an Ensemble With Statistical Models: An Algorithm for Global 3D Spatio-Temporal Temperature

KAUST Repository

Castruccio, Stefano; Genton, Marc G.

2016-01-01

algorithms can be used to mitigate this problem, but since they are designed to compress generic scientific datasets, they do not account for the nature of climate model output and they compress only individual simulations. In this work, we propose a

Smartphone based automatic organ validation in ultrasound video.

Science.gov (United States)

Vaish, Pallavi; Bharath, R; Rajalakshmi, P

2017-07-01

Telesonography involves transmission of ultrasound video from remote areas to the doctors for getting diagnosis. Due to the lack of trained sonographers in remote areas, the ultrasound videos scanned by these untrained persons do not contain the proper information that is required by a physician. As compared to standard methods for video transmission, mHealth driven systems need to be developed for transmitting valid medical videos. To overcome this problem, we are proposing an organ validation algorithm to evaluate the ultrasound video based on the content present. This will guide the semi skilled person to acquire the representative data from patient. Advancement in smartphone technology allows us to perform high medical image processing on smartphone. In this paper we have developed an Application (APP) for a smartphone which can automatically detect the valid frames (which consist of clear organ visibility) in an ultrasound video and ignores the invalid frames (which consist of no-organ visibility), and produces a compressed sized video. This is done by extracting the GIST features from the Region of Interest (ROI) of the frame and then classifying the frame using SVM classifier with quadratic kernel. The developed application resulted with the accuracy of 94.93% in classifying valid and invalid images.

A New RTL Design Approach for a DCT/IDCT-Based Image Compression Architecture using the mCBE Algorithm

Directory of Open Access Journals (Sweden)

Rachmad Vidya Wicaksana Putra

2012-09-01

Full Text Available In the literature, several approaches of designing a DCT/IDCT-based image compression system have been proposed. In this paper, we present a new RTL design approach with as main focus developing a DCT/IDCT-based image compression architecture using a self-created algorithm. This algorithm can efficiently minimize the amount of shifter-adders to substitute multipliers. We call this new algorithm the multiplication from Common Binary Expression (mCBE Algorithm. Besides this algorithm, we propose alternative quantization numbers, which can be implemented simply as shifters in digital hardware. Mostly, these numbers can retain a good compressed-image quality compared to JPEG recommendations. These ideas lead to our design being small in circuit area, multiplierless, and low in complexity. The proposed 8-point 1D-DCT design has only six stages, while the 8-point 1D-IDCT design has only seven stages (one stage being defined as equal to the delay of one shifter or 2-input adder. By using the pipelining method, we can achieve a high-speed architecture with latency as a trade-off consideration. The design has been synthesized and can reach a speed of up to 1.41ns critical path delay (709.22MHz.

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.

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.

Real-time heart rate measurement for multi-people using compressive tracking

Science.gov (United States)

Liu, Lingling; Zhao, Yuejin; Liu, Ming; Kong, Lingqin; Dong, Liquan; Ma, Feilong; Pang, Zongguang; Cai, Zhi; Zhang, Yachu; Hua, Peng; Yuan, Ruifeng

2017-09-01

The rise of aging population has created a demand for inexpensive, unobtrusive, automated health care solutions. Image PhotoPlethysmoGraphy(IPPG) aids in the development of these solutions by allowing for the extraction of physiological signals from video data. However, the main deficiencies of the recent IPPG methods are non-automated, non-real-time and susceptible to motion artifacts(MA). In this paper, a real-time heart rate(HR) detection method for multiple subjects simultaneously was proposed and realized using the open computer vision(openCV) library, which consists of getting multiple subjects' facial video automatically through a Webcam, detecting the region of interest (ROI) in the video, reducing the false detection rate by our improved Adaboost algorithm, reducing the MA by our improved compress tracking(CT) algorithm, wavelet noise-suppression algorithm for denoising and multi-threads for higher detection speed. For comparison, HR was measured simultaneously using a medical pulse oximetry device for every subject during all sessions. Experimental results on a data set of 30 subjects show that the max average absolute error of heart rate estimation is less than 8 beats per minute (BPM), and the processing speed of every frame has almost reached real-time: the experiments with video recordings of ten subjects under the condition of the pixel resolution of 600× 800 pixels show that the average HR detection time of 10 subjects was about 17 frames per second (fps).

[Medical image compression: a review].

Science.gov (United States)

Noreña, Tatiana; Romero, Eduardo

2013-01-01

Modern medicine is an increasingly complex activity , based on the evidence ; it consists of information from multiple sources : medical record text , sound recordings , images and videos generated by a large number of devices . Medical imaging is one of the most important sources of information since they offer comprehensive support of medical procedures for diagnosis and follow-up . However , the amount of information generated by image capturing gadgets quickly exceeds storage availability in radiology services , generating additional costs in devices with greater storage capacity . Besides , the current trend of developing applications in cloud computing has limitations, even though virtual storage is available from anywhere, connections are made through internet . In these scenarios the optimal use of information necessarily requires powerful compression algorithms adapted to medical activity needs . In this paper we present a review of compression techniques used for image storage , and a critical analysis of them from the point of view of their use in clinical settings.

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.

Detection of Defective Sensors in Phased Array Using Compressed Sensing and Hybrid Genetic Algorithm

Directory of Open Access Journals (Sweden)

Shafqat Ullah Khan

2016-01-01

Full Text Available A compressed sensing based array diagnosis technique has been presented. This technique starts from collecting the measurements of the far-field pattern. The system linking the difference between the field measured using the healthy reference array and the field radiated by the array under test is solved using a genetic algorithm (GA, parallel coordinate descent (PCD algorithm, and then a hybridized GA with PCD algorithm. These algorithms are applied for fully and partially defective antenna arrays. The simulation results indicate that the proposed hybrid algorithm outperforms in terms of localization of element failure with a small number of measurements. In the proposed algorithm, the slow and early convergence of GA has been avoided by combining it with PCD algorithm. It has been shown that the hybrid GA-PCD algorithm provides an accurate diagnosis of fully and partially defective sensors as compared to GA or PCD alone. Different simulations have been provided to validate the performance of the designed algorithms in diversified scenarios.

An ROI multi-resolution compression method for 3D-HEVC

Science.gov (United States)

Ti, Chunli; Guan, Yudong; Xu, Guodong; Teng, Yidan; Miao, Xinyuan

2017-09-01

3D High Efficiency Video Coding (3D-HEVC) provides a significant potential on increasing the compression ratio of multi-view RGB-D videos. However, the bit rate still rises dramatically with the improvement of the video resolution, which will bring challenges to the transmission network, especially the mobile network. This paper propose an ROI multi-resolution compression method for 3D-HEVC to better preserve the information in ROI on condition of limited bandwidth. This is realized primarily through ROI extraction and compression multi-resolution preprocessed video as alternative data according to the network conditions. At first, the semantic contours are detected by the modified structured forests to restrain the color textures inside objects. The ROI is then determined utilizing the contour neighborhood along with the face region and foreground area of the scene. Secondly, the RGB-D videos are divided into slices and compressed via 3D-HEVC under different resolutions for selection by the audiences and applications. Afterwards, the reconstructed low-resolution videos from 3D-HEVC encoder are directly up-sampled via Laplace transformation and used to replace the non-ROI areas of the high-resolution videos. Finally, the ROI multi-resolution compressed slices are obtained by compressing the ROI preprocessed videos with 3D-HEVC. The temporal and special details of non-ROI are reduced in the low-resolution videos, so the ROI will be better preserved by the encoder automatically. Experiments indicate that the proposed method can keep the key high-frequency information with subjective significance while the bit rate is reduced.

An compression algorithm for medical images and a display with the decoding function

International Nuclear Information System (INIS)

Gotoh, Toshiyuki; Nakagawa, Yukihiro; Shiohara, Morito; Yoshida, Masumi

1990-01-01

This paper describes and efficient image compression method for medical images, a high-speed display with the decoding function. In our method, an input image is divided into blocks, and either of Discrete Cosine Transform coding (DCT) or Block Truncation Coding (BTC) is adaptively applied on each block to improve image quality. The display, we developed, receives the compressed data from the host computer and reconstruct images of good quality at high speed using four decoding microprocessors on which our algorithm is implemented in pipeline. By the experiments, our method and display were verified to be effective. (author)

Test and Evaluation of Teleconferencing Video Codecs Transmitting at 1.5 Mbps.

Science.gov (United States)

1985-08-01

video teleconferencing codecs on the market as of November 1984 to facilitate the choice of an appropriate frame format and data compression algorithm...Engineer, computer company, male 5. Chapter Officer, national civic organization, female Group Y: 6. Marketing Representative, communication systems...both mon:tors to C4ve t e evi uators an idea what kind of cictures they will have to ; ucge . Special suggestions were given regardinc the sequences witn

Endotracheal Intubation Using the Macintosh Laryngoscope or KingVision Video Laryngoscope during Uninterrupted Chest Compression

Directory of Open Access Journals (Sweden)

Ewelina Gaszynska

2014-01-01

Full Text Available Objective. Advanced airway management, endotracheal intubation (ETI, during CPR is more difficult than, for example, during anesthesia. However, new devices such as video laryngoscopes should help in such circumstances. The aim of this study was to assess the performance of the KingVision video laryngoscopes in a manikin cardiopulmonary resuscitation (CPR scenario. Methods. Thirty students enrolled in the third year of paramedic school took part in the study. The simulated CPR scenario was ETI using the standard laryngoscope with a Macintosh blade (MCL and ETI using the KingVision video laryngoscope performed during uninterrupted chest compressions. The primary endpoints were the time needed for ETI and the success ratio. Results. The mean time required for intubation was similar for both laryngoscopes: 16.6 (SD 5.11, median 15.64, range 7.9–27.9 seconds versus 17.91 (SD 5.6, median 16.28, range 10.6–28.6 seconds for the MCL and KingVision, respectively (P=0.1888. On the first attempt at ETI, the success rate during CPR was comparable between the evaluated laryngoscopes: P=0.9032. Conclusion. The KingVision video laryngoscope proves to be less superior when used for endotracheal intubation during CPR compared to the standard laryngoscope with a Mackintosh blade. This proves true in terms of shortening the time needed for ETI and increasing the success ratio.

Extended image differencing for change detection in UAV video mosaics

Science.gov (United States)

Saur, Günter; Krüger, Wolfgang; Schumann, Arne

2014-03-01

Change detection is one of the most important tasks when using unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. We address changes of short time scale, i.e. the observations are taken in time distances from several minutes up to a few hours. Each observation is a short video sequence acquired by the UAV in near-nadir view and the relevant changes are, e.g., recently parked or moved vehicles. In this paper we extend our previous approach of image differencing for single video frames to video mosaics. A precise image-to-image registration combined with a robust matching approach is needed to stitch the video frames to a mosaic. Additionally, this matching algorithm is applied to mosaic pairs in order to align them to a common geometry. The resulting registered video mosaic pairs are the input of the change detection procedure based on extended image differencing. A change mask is generated by an adaptive threshold applied to a linear combination of difference images of intensity and gradient magnitude. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed size of shadows, and compression or transmission artifacts. The special effects of video mosaicking such as geometric distortions and artifacts at moving objects have to be considered, too. In our experiments we analyze the influence of these effects on the change detection results by considering several scenes. The results show that for video mosaics this task is more difficult than for single video frames. Therefore, we extended the image registration by estimating an elastic transformation using a thin plate spline approach. The results for mosaics are comparable to that of single video frames and are useful for interactive image exploitation due to a larger scene coverage.

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

Science.gov (United States)

Elahi, Sana; kaleem, Muhammad; Omer, Hammad

2018-01-01

Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

Deep linear autoencoder and patch clustering-based unified one-dimensional coding of image and video

Science.gov (United States)

Li, Honggui

2017-09-01

This paper proposes a unified one-dimensional (1-D) coding framework of image and video, which depends on deep learning neural network and image patch clustering. First, an improved K-means clustering algorithm for image patches is employed to obtain the compact inputs of deep artificial neural network. Second, for the purpose of best reconstructing original image patches, deep linear autoencoder (DLA), a linear version of the classical deep nonlinear autoencoder, is introduced to achieve the 1-D representation of image blocks. Under the circumstances of 1-D representation, DLA is capable of attaining zero reconstruction error, which is impossible for the classical nonlinear dimensionality reduction methods. Third, a unified 1-D coding infrastructure for image, intraframe, interframe, multiview video, three-dimensional (3-D) video, and multiview 3-D video is built by incorporating different categories of videos into the inputs of patch clustering algorithm. Finally, it is shown in the results of simulation experiments that the proposed methods can simultaneously gain higher compression ratio and peak signal-to-noise ratio than those of the state-of-the-art methods in the situation of low bitrate transmission.

Speech Data Compression using Vector Quantization

OpenAIRE

H. B. Kekre; Tanuja K. Sarode

2008-01-01

Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table s...

Distortion-Based Link Adaptation for Wireless Video Transmission

Directory of Open Access Journals (Sweden)

Andrew Nix

2008-06-01

Full Text Available Wireless local area networks (WLANs such as IEEE 802.11a/g utilise numerous transmission modes, each providing different throughputs and reliability levels. Most link adaptation algorithms proposed in the literature (i maximise the error-free data throughput, (ii do not take into account the content of the data stream, and (iii rely strongly on the use of ARQ. Low-latency applications, such as real-time video transmission, do not permit large numbers of retransmission. In this paper, a novel link adaptation scheme is presented that improves the quality of service (QoS for video transmission. Rather than maximising the error-free throughput, our scheme minimises the video distortion of the received sequence. With the use of simple and local rate distortion measures and end-to-end distortion models at the video encoder, the proposed scheme estimates the received video distortion at the current transmission rate, as well as on the adjacent lower and higher rates. This allows the system to select the link-speed which offers the lowest distortion and to adapt to the channel conditions. Simulation results are presented using the MPEG-4/AVC H.264 video compression standard over IEEE 802.11g. The results show that the proposed system closely follows the optimum theoretic solution.

Resource-Constrained Low-Complexity Video Coding for Wireless Transmission

DEFF Research Database (Denmark)

Ukhanova, Ann

of video quality. We proposed a new metric for objective quality assessment that considers frame rate. As many applications deal with wireless video transmission, we performed an analysis of compression and transmission systems with a focus on power-distortion trade-off. We proposed an approach...... for ratedistortion-complexity optimization of upcoming video compression standard HEVC. We also provided a new method allowing decrease of power consumption on mobile devices in 3G networks. Finally, we proposed low-delay and low-power approaches for video transmission over wireless personal area networks, including......Constrained resources like memory, power, bandwidth and delay requirements in many mobile systems pose limitations for video applications. Standard approaches for video compression and transmission do not always satisfy system requirements. In this thesis we have shown that it is possible to modify...

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

KAUST Repository

Halim Boukaram, Wajih

2017-09-14

We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

KAUST Repository

Halim Boukaram, Wajih; Turkiyyah, George; Ltaief, Hatem; Keyes, David E.

2017-01-01

We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

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.

Hierarchical compression of Caenorhabditis elegans locomotion reveals phenotypic differences in the organization of behaviour.

Science.gov (United States)

Gomez-Marin, Alex; Stephens, Greg J; Brown, André E X

2016-08-01

Regularities in animal behaviour offer insights into the underlying organizational and functional principles of nervous systems and automated tracking provides the opportunity to extract features of behaviour directly from large-scale video data. Yet how to effectively analyse such behavioural data remains an open question. Here, we explore whether a minimum description length principle can be exploited to identify meaningful behaviours and phenotypes. We apply a dictionary compression algorithm to behavioural sequences from the nematode worm Caenorhabditis elegans freely crawling on an agar plate both with and without food and during chemotaxis. We find that the motifs identified by the compression algorithm are rare but relevant for comparisons between worms in different environments, suggesting that hierarchical compression can be a useful step in behaviour analysis. We also use compressibility as a new quantitative phenotype and find that the behaviour of wild-isolated strains of C. elegans is more compressible than that of the laboratory strain N2 as well as the majority of mutant strains examined. Importantly, in distinction to more conventional phenotypes such as overall motor activity or aggregation behaviour, the increased compressibility of wild isolates is not explained by the loss of function of the gene npr-1, which suggests that erratic locomotion is a laboratory-derived trait with a novel genetic basis. Because hierarchical compression can be applied to any sequence, we anticipate that compressibility can offer insights into the organization of behaviour in other animals including humans. © 2016 The Authors.

A novel directional asymmetric sampling search algorithm for fast block-matching motion estimation

Science.gov (United States)

Li, Yue-e.; Wang, Qiang

2011-11-01

This paper proposes a novel directional asymmetric sampling search (DASS) algorithm for video compression. Making full use of the error information (block distortions) of the search patterns, eight different direction search patterns are designed for various situations. The strategy of local sampling search is employed for the search of big-motion vector. In order to further speed up the search, early termination strategy is adopted in procedure of DASS. Compared to conventional fast algorithms, the proposed method has the most satisfactory PSNR values for all test sequences.

Video Bandwidth Compression System.

Science.gov (United States)

1980-08-01

scaling function, located between the inverse DPCM and inverse transform , on the decoder matrix multiplier chips. 1"V1 T.. ---- i.13 SECURITY...Bit Unpacker and Inverse DPCM Slave Sync Board 15 e. Inverse DPCM Loop Boards 15 f. Inverse Transform Board 16 g. Composite Video Output Board 16...36 a. Display Refresh Memory 36 (1) Memory Section 37 (2) Timing and Control 39 b. Bit Unpacker and Inverse DPCM 40 c. Inverse Transform Processor 43

VLSI-based video event triggering for image data compression

Science.gov (United States)

Williams, Glenn L.

1994-02-01

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Motion Vector Estimation Using Line-Square Search Block Matching Algorithm for Video Sequences

Directory of Open Access Journals (Sweden)

Guo Bao-long

2004-09-01

Full Text Available Motion estimation and compensation techniques are widely used for video coding applications but the real-time motion estimation is not easily achieved due to its enormous computations. In this paper, a new fast motion estimation algorithm based on line search is presented, in which computation complexity is greatly reduced by using the line search strategy and a parallel search pattern. Moreover, the accurate search is achieved because the small square search pattern is used. It has a best-case scenario of only 9 search points, which is 4 search points less than the diamond search algorithm. Simulation results show that, compared with the previous techniques, the LSPS algorithm significantly reduces the computational requirements for finding motion vectors, and also produces close performance in terms of motion compensation errors.

Complexity-aware high efficiency video coding

CERN Document Server

Correa, Guilherme; Agostini, Luciano; Cruz, Luis A da Silva

2016-01-01

This book discusses computational complexity of High Efficiency Video Coding (HEVC) encoders with coverage extending from the analysis of HEVC compression efficiency and computational complexity to the reduction and scaling of its encoding complexity. After an introduction to the topic and a review of the state-of-the-art research in the field, the authors provide a detailed analysis of the HEVC encoding tools compression efficiency and computational complexity.  Readers will benefit from a set of algorithms for scaling the computational complexity of HEVC encoders, all of which take advantage from the flexibility of the frame partitioning structures allowed by the standard.  The authors also provide a set of early termination methods based on data mining and machine learning techniques, which are able to reduce the computational complexity required to find the best frame partitioning structures. The applicability of the proposed methods is finally exemplified with an encoding time control system that emplo...

Image Steganography of Multiple File Types with Encryption and Compression Algorithms

Directory of Open Access Journals (Sweden)

Ernest Andreigh C. Centina

2017-05-01

Full Text Available The goals of this study were to develop a system intended for securing files through the technique of image steganography integrated with cryptography by utilizing ZLIB Algorithm for compressing and decompressing secret files, DES Algorithm for encryption and decryption, and Least Significant Bit Algorithm for file embedding and extraction to avoid compromise on highly confidential files from exploits of unauthorized persons. Ensuing to this, the system is in acc ordance with ISO 9126 international quality standards. Every quality criteria of the system was evaluated by 10 Information Technology professionals, and the arithmetic Mean and Standard Deviation of the survey were computed. The result exhibits that m ost of them strongly agreed that the system is excellently effective based on Functionality, Reliability, Usability, Efficiency, Maintainability and Portability conformance to ISO 9126 standards. The system was found to be a useful tool for both governmen t agencies and private institutions for it could keep not only the message secret but also the existence of that particular message or file et maintaining the privacy of highly confidential and sensitive files from unauthorized access.

Blind prediction of natural video quality.

Science.gov (United States)

Saad, Michele A; Bovik, Alan C; Charrier, Christophe

2014-03-01

We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.

Perceived Quality of Full HD Video - Subjective Quality Assessment

Directory of Open Access Journals (Sweden)

Juraj Bienik

2016-01-01

Full Text Available In recent years, an interest in multimedia services has become a global trend and this trend is still rising. The video quality is a very significant part from the bundle of multimedia services, which leads to a requirement for quality assessment in the video domain. Video quality of a streamed video across IP networks is generally influenced by two factors “transmission link imperfection and efficiency of compression standards. This paper deals with subjective video quality assessment and the impact of the compression standards H.264, H.265 and VP9 on perceived video quality of these compression standards. The evaluation is done for four full HD sequences, the difference of scenes is in the content“ distinction is based on Spatial (SI and Temporal (TI Index of test sequences. Finally, experimental results follow up to 30% bitrate reducing of H.265 and VP9 compared with the reference H.264.

Rate control scheme for consistent video quality in scalable video codec.

Science.gov (United States)

Seo, Chan-Won; Han, Jong-Ki; Nguyen, Truong Q

2011-08-01

Multimedia data delivered to mobile devices over wireless channels or the Internet are complicated by bandwidth fluctuation and the variety of mobile devices. Scalable video coding has been developed as an extension of H.264/AVC to solve this problem. Since scalable video codec provides various scalabilities to adapt the bitstream for the channel conditions and terminal types, scalable codec is one of the useful codecs for wired or wireless multimedia communication systems, such as IPTV and streaming services. In such scalable multimedia communication systems, video quality fluctuation degrades the visual perception significantly. It is important to efficiently use the target bits in order to maintain a consistent video quality or achieve a small distortion variation throughout the whole video sequence. The scheme proposed in this paper provides a useful function to control video quality in applications supporting scalability, whereas conventional schemes have been proposed to control video quality in the H.264 and MPEG-4 systems. The proposed algorithm decides the quantization parameter of the enhancement layer to maintain a consistent video quality throughout the entire sequence. The video quality of the enhancement layer is controlled based on a closed-form formula which utilizes the residual data and quantization error of the base layer. The simulation results show that the proposed algorithm controls the frame quality of the enhancement layer in a simple operation, where the parameter decision algorithm is applied to each frame.

Video segmentation and camera motion characterization using compressed data

Science.gov (United States)

Milanese, Ruggero; Deguillaume, Frederic; Jacot-Descombes, Alain

1997-10-01

We address the problem of automatically extracting visual indexes from videos, in order to provide sophisticated access methods to the contents of a video server. We focus on tow tasks, namely the decomposition of a video clip into uniform segments, and the characterization of each shot by camera motion parameters. For the first task we use a Bayesian classification approach to detecting scene cuts by analyzing motion vectors. For the second task a least- squares fitting procedure determines the pan/tilt/zoom camera parameters. In order to guarantee the highest processing speed, all techniques process and analyze directly MPEG-1 motion vectors, without need for video decompression. Experimental results are reported for a database of news video clips.

On Normalized Compression Distance and Large Malware

OpenAIRE

Borbely, Rebecca Schuller

2015-01-01

Normalized Compression Distance (NCD) is a popular tool that uses compression algorithms to cluster and classify data in a wide range of applications. Existing discussions of NCD's theoretical merit rely on certain theoretical properties of compression algorithms. However, we demonstrate that many popular compression algorithms don't seem to satisfy these theoretical properties. We explore the relationship between some of these properties and file size, demonstrating that this theoretical pro...

An efficient CU partition algorithm for HEVC based on improved Sobel operator

Science.gov (United States)

Sun, Xuebin; Chen, Xiaodong; Xu, Yong; Sun, Gang; Yang, Yunsheng

2018-04-01

As the latest video coding standard, High Efficiency Video Coding (HEVC) achieves over 50% bit rate reduction with similar video quality compared with previous standards H.264/AVC. However, the higher compression efficiency is attained at the cost of significantly increasing computational load. In order to reduce the complexity, this paper proposes a fast coding unit (CU) partition technique to speed up the process. To detect the edge features of each CU, a more accurate improved Sobel filtering is developed and performed By analyzing the textural features of CU, an early CU splitting termination is proposed to decide whether a CU should be decomposed into four lower-dimensions CUs or not. Compared with the reference software HM16.7, experimental results indicate the proposed algorithm can lessen the encoding time up to 44.09% on average, with a negligible bit rate increase of 0.24%, and quality losses lower 0.03 dB, respectively. In addition, the proposed algorithm gets a better trade-off between complexity and rate-distortion among the other proposed works.

A New Video Coding Algorithm Using 3D-Subband Coding and Lattice Vector Quantization

Energy Technology Data Exchange (ETDEWEB)

Choi, J.H. [Taejon Junior College, Taejon (Korea, Republic of); Lee, K.Y. [Sung Kyun Kwan University, Suwon (Korea, Republic of)

1997-12-01

In this paper, we propose an efficient motion adaptive 3-dimensional (3D) video coding algorithm using 3D subband coding (3D-SBC) and lattice vector quantization (LVQ) for low bit rate. Instead of splitting input video sequences into the fixed number of subbands along the temporal axes, we decompose them into temporal subbands of variable size according to motions in frames. Each spatio-temporally splitted 7 subbands are partitioned by quad tree technique and coded with lattice vector quantization(LVQ). The simulation results show 0.1{approx}4.3dB gain over H.261 in peak signal to noise ratio(PSNR) at low bit rate (64Kbps). (author). 13 refs., 13 figs., 4 tabs.

Using Genetic Algorithm for Eye Detection and Tracking in Video Sequence

Directory of Open Access Journals (Sweden)

Takuya Akashi

2007-04-01

Full Text Available We propose a high-speed size and orientation invariant eye tracking method, which can acquire numerical parameters to represent the size and orientation of the eye. In this paper, we discuss that high tolerance in human head movement and real-time processing that are needed for many applications, such as eye gaze tracking. The generality of the method is also important. We use template matching with genetic algorithm, in order to overcome these problems. A high speed and accuracy tracking scheme using Evolutionary Video Processing for eye detection and tracking is proposed. Usually, a genetic algorithm is unsuitable for a real-time processing, however, we achieved real-time processing. The generality of this proposed method is provided by the artificial iris template used. In our simulations, an eye tracking accuracy is 97.9% and, an average processing time of 28 milliseconds per frame.

Short-term change detection for UAV video

Science.gov (United States)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer

Effect of video decoder errors on video interpretability

Science.gov (United States)

Young, Darrell L.

2014-06-01

The advancement in video compression technology can result in more sensitivity to bit errors. Bit errors can propagate causing sustained loss of interpretability. In the worst case, the decoder "freezes" until it can re-synchronize with the stream. Detection of artifacts enables downstream processes to avoid corrupted frames. A simple template approach to detect block stripes and a more advanced cascade approach to detect compression artifacts was shown to correlate to the presence of artifacts and decoder messages.

A nonlinear relaxation/quasi-Newton algorithm for the compressible Navier-Stokes equations

Science.gov (United States)

Edwards, Jack R.; Mcrae, D. S.

1992-01-01

A highly efficient implicit method for the computation of steady, two-dimensional compressible Navier-Stokes flowfields is presented. The discretization of the governing equations is hybrid in nature, with flux-vector splitting utilized in the streamwise direction and central differences with flux-limited artificial dissipation used for the transverse fluxes. Line Jacobi relaxation is used to provide a suitable initial guess for a new nonlinear iteration strategy based on line Gauss-Seidel sweeps. The applicability of quasi-Newton methods as convergence accelerators for this and other line relaxation algorithms is discussed, and efficient implementations of such techniques are presented. Convergence histories and comparisons with experimental data are presented for supersonic flow over a flat plate and for several high-speed compression corner interactions. Results indicate a marked improvement in computational efficiency over more conventional upwind relaxation strategies, particularly for flowfields containing large pockets of streamwise subsonic flow.

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...

Surpassing the Theoretical 1-Norm Phase Transition in Compressive Sensing by Tuning the Smoothed L0 Algorithm

DEFF Research Database (Denmark)

Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas

2013-01-01

Reconstruction of an undersampled signal is at the root of compressive sensing: when is an algorithm capable of reconstructing the signal? what quality is achievable? and how much time does reconstruction require? We have considered the worst-case performance of the smoothed ℓ0 norm reconstruction...... algorithm in a noiseless setup. Through an empirical tuning of its parameters, we have improved the phase transition (capabilities) of the algorithm for fixed quality and required time. In this paper, we present simulation results that show a phase transition surpassing that of the theoretical ℓ1 approach......: the proposed modified algorithm obtains 1-norm phase transition with greatly reduced required computation time....

A method of mobile video transmission based on J2ee

Science.gov (United States)

Guo, Jian-xin; Zhao, Ji-chun; Gong, Jing; Chun, Yang

2013-03-01

As 3G (3rd-generation) networks evolve worldwide, the rising demand for mobile video services and the enormous growth of video on the internet is creating major new revenue opportunities for mobile network operators and application developers. The text introduced a method of mobile video transmission based on J2ME, giving the method of video compressing, then describing the video compressing standard, and then describing the software design. The proposed mobile video method based on J2EE is a typical mobile multimedia application, which has a higher availability and a wide range of applications. The users can get the video through terminal devices such as phone.

a Sensor Aided H.264/AVC Video Encoder for Aerial Video Sequences with in the Loop Metadata Correction

Science.gov (United States)

Cicala, L.; Angelino, C. V.; Ruatta, G.; Baccaglini, E.; Raimondo, N.

2015-08-01

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

Study on the effects of sample selection on spectral reflectance reconstruction based on the algorithm of compressive sensing

International Nuclear Information System (INIS)

Zhang, Leihong; Liang, Dong

2016-01-01

In order to solve the problem that reconstruction efficiency and precision is not high, in this paper different samples are selected to reconstruct spectral reflectance, and a new kind of spectral reflectance reconstruction method based on the algorithm of compressive sensing is provided. Four different color numbers of matte color cards such as the ColorChecker Color Rendition Chart and Color Checker SG, the copperplate paper spot color card of Panton, and the Munsell colors card are chosen as training samples, the spectral image is reconstructed respectively by the algorithm of compressive sensing and pseudo-inverse and Wiener, and the results are compared. These methods of spectral reconstruction are evaluated by root mean square error and color difference accuracy. The experiments show that the cumulative contribution rate and color difference of the Munsell colors card are better than those of the other three numbers of color cards in the same conditions of reconstruction, and the accuracy of the spectral reconstruction will be affected by the training sample of different numbers of color cards. The key technology of reconstruction means that the uniformity and representation of the training sample selection has important significance upon reconstruction. In this paper, the influence of the sample selection on the spectral image reconstruction is studied. The precision of the spectral reconstruction based on the algorithm of compressive sensing is higher than that of the traditional algorithm of spectral reconstruction. By the MATLAB simulation results, it can be seen that the spectral reconstruction precision and efficiency are affected by the different color numbers of the training sample. (paper)

Automatic video segmentation employing object/camera modeling techniques

NARCIS (Netherlands)

Farin, D.S.

2005-01-01

Practically established video compression and storage techniques still process video sequences as rectangular images without further semantic structure. However, humans watching a video sequence immediately recognize acting objects as semantic units. This semantic object separation is currently not

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

Science.gov (United States)

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

2017-09-01

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

A New RTL Design Approach for a DCT/IDCT-Based Image Compression Architecture using the mCBE Algorithm

Directory of Open Access Journals (Sweden)

Rachmad Vidya Wicaksana Putra

2013-09-01

Full Text Available In  the  literature, several approaches  of  designing  a  DCT/IDCT-based image compression system have been proposed.  In this paper,  we present a new RTL design approach with as main  focus developing a  DCT/IDCT-based image compression  architecture  using  a  self-created  algorithm.  This  algorithm  can efficiently  minimize  the  amount  of  shifter -adders  to  substitute  multiplier s.  We call  this  new  algorithm  the  multiplication  from  Common  Binary  Expression (mCBE  Algorithm. Besides this algorithm, we propose alternative quantization numbers,  which  can  be  implemented  simply  as  shifters  in  digital  hardware. Mostly, these numbers can retain a good compressed-image quality  compared to JPEG  recommendations.  These  ideas  lead  to  our  design  being  small  in  circuit area,  multiplierless,  and  low  in  complexity.  The  proposed  8-point  1D-DCT design  has  only  six  stages,  while  the  8-point  1D-IDCT  design  has  only  seven stages  (one  stage  being  defined as  equal  to  the  delay  of  one  shifter  or  2-input adder. By using the pipelining method, we can achieve a high-speed architecture with latency as    a  trade-off consideration. The  design has been synthesized and can reach a speed of up to 1.41ns critical path delay (709.22MHz. 

Automatic Performance Evaluation for Video Summarization

Science.gov (United States)

2004-07-01

Multimedia 2002, pp.189–198. [14] S. Uchihashi, J. Foote, A. Girgensohn and J. Boreczky, “Video Manga : Generating Seman- tically Meaningful Video...DeMenthon, V. Kobla and D. Doermann, “Video Summarization by Curve Simplification”, ACM Multimedia 98, Bristol, England, pp. 211-218, September 1998. 26 [2...J. Au, “Video Keyframe Production by Efficient Clustering of Compressed Chromaticity Signatures”, ACM Multimedia 2000, Juan-Les-Pins, France, pp. 365

Application of digital compression techniques to optical surveillance systems

International Nuclear Information System (INIS)

Johnson, C.S.

1991-01-01

There are many benefits to handling video images electronically, however, the amount of digital data in a normal video image is a major obstacle. The solution is to remove the high frequency and redundant information in a process that is referred to as compression. Compression allows the number of digital bits required for a given image to be reduced for more efficient storage or transmission of images. The next question is how much compression can be done without impairing the image quality beyond its usefulness for a given application. This paper discusses image compression that might be applied to provide useful images in unattended nuclear facility surveillance applications

Comparative data compression techniques and multi-compression results

International Nuclear Information System (INIS)

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

2013-01-01

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

An Attention-Information-Based Spatial Adaptation Framework for Browsing Videos via Mobile Devices

Directory of Open Access Journals (Sweden)

Li Houqiang

2007-01-01

Full Text Available With the growing popularity of personal digital assistant devices and smart phones, more and more consumers are becoming quite enthusiastic to appreciate videos via mobile devices. However, limited display size of the mobile devices has been imposing significant barriers for users to enjoy browsing high-resolution videos. In this paper, we present an attention-information-based spatial adaptation framework to address this problem. The whole framework includes two major parts: video content generation and video adaptation system. During video compression, the attention information in video sequences will be detected using an attention model and embedded into bitstreams with proposed supplement-enhanced information (SEI structure. Furthermore, we also develop an innovative scheme to adaptively adjust quantization parameters in order to simultaneously improve the quality of overall encoding and the quality of transcoding the attention areas. When the high-resolution bitstream is transmitted to mobile users, a fast transcoding algorithm we developed earlier will be applied to generate a new bitstream for attention areas in frames. The new low-resolution bitstream containing mostly attention information, instead of the high-resolution one, will be sent to users for display on the mobile devices. Experimental results show that the proposed spatial adaptation scheme is able to improve both subjective and objective video qualities.

Efficient Compression of Far Field Matrices in Multipole Algorithms based on Spherical Harmonics and Radiating Modes

Directory of Open Access Journals (Sweden)

A. Schroeder

2012-09-01

Full Text Available This paper proposes a compression of far field matrices in the fast multipole method and its multilevel extension for electromagnetic problems. The compression is based on a spherical harmonic representation of radiation patterns in conjunction with a radiating mode expression of the surface current. The method is applied to study near field effects and the far field of an antenna placed on a ship surface. Furthermore, the electromagnetic scattering of an electrically large plate is investigated. It is demonstrated, that the proposed technique leads to a significant memory saving, making multipole algorithms even more efficient without compromising the accuracy.

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

Science.gov (United States)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.

Compressibility-aware media retargeting with structure preserving.

Science.gov (United States)

Wang, Shu-Fan; Lai, Shang-Hong

2011-03-01

A number of algorithms have been proposed for intelligent image/video retargeting with image content retained as much as possible. However, they usually suffer from some artifacts in the results, such as ridge or structure twist. In this paper, we present a structure-preserving media retargeting technique that preserves the content and image structure as best as possible. Different from the previous pixel or grid based methods, we estimate the image content saliency from the structure of the content. A block structure energy is introduced with a top-down strategy to constrain the image structure inside to deform uniformly in either x or y direction. However, the flexibilities for retargeting are quite different for different images. To cope with this problem, we propose a compressibility assessment scheme for media retargeting by combining the entropies of image gradient magnitude and orientation distributions. Thus, the resized media is produced to preserve the image content and structure as best as possible. Our experiments demonstrate that the proposed method provides resized images/videos with better preservation of content and structure than those by the previous methods.

A compressed sensing based 3D resistivity inversion algorithm for hydrogeological applications

Science.gov (United States)

Ranjan, Shashi; Kambhammettu, B. V. N. P.; Peddinti, Srinivasa Rao; Adinarayana, J.

2018-04-01

Image reconstruction from discrete electrical responses pose a number of computational and mathematical challenges. Application of smoothness constrained regularized inversion from limited measurements may fail to detect resistivity anomalies and sharp interfaces separated by hydro stratigraphic units. Under favourable conditions, compressed sensing (CS) can be thought of an alternative to reconstruct the image features by finding sparse solutions to highly underdetermined linear systems. This paper deals with the development of a CS assisted, 3-D resistivity inversion algorithm for use with hydrogeologists and groundwater scientists. CS based l1-regularized least square algorithm was applied to solve the resistivity inversion problem. Sparseness in the model update vector is introduced through block oriented discrete cosine transformation, with recovery of the signal achieved through convex optimization. The equivalent quadratic program was solved using primal-dual interior point method. Applicability of the proposed algorithm was demonstrated using synthetic and field examples drawn from hydrogeology. The proposed algorithm has outperformed the conventional (smoothness constrained) least square method in recovering the model parameters with much fewer data, yet preserving the sharp resistivity fronts separated by geologic layers. Resistivity anomalies represented by discrete homogeneous blocks embedded in contrasting geologic layers were better imaged using the proposed algorithm. In comparison to conventional algorithm, CS has resulted in an efficient (an increase in R2 from 0.62 to 0.78; a decrease in RMSE from 125.14 Ω-m to 72.46 Ω-m), reliable, and fast converging (run time decreased by about 25%) solution.

Quality and noise measurements in mobile phone video capture

Science.gov (United States)

Petrescu, Doina; Pincenti, John

2011-02-01

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

Music analysis and point-set compression

DEFF Research Database (Denmark)

Meredith, David

2015-01-01

COSIATEC, SIATECCompress and Forth’s algorithm are point-set compression algorithms developed for discovering repeated patterns in music, such as themes and motives that would be of interest to a music analyst. To investigate their effectiveness and versatility, these algorithms were evaluated...... on three analytical tasks that depend on the discovery of repeated patterns: classifying folk song melodies into tune families, discovering themes and sections in polyphonic music, and discovering subject and countersubject entries in fugues. Each algorithm computes a compressed encoding of a point......-set representation of a musical object in the form of a list of compact patterns, each pattern being given with a set of vectors indicating its occurrences. However, the algorithms adopt different strategies in their attempts to discover encodings that maximize compression.The best-performing algorithm on the folk...

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.

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

Science.gov (United States)

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

2012-12-01

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

Attacks, applications, and evaluation of known watermarking algorithms with Checkmark

Science.gov (United States)

Meerwald, Peter; Pereira, Shelby

2002-04-01

The Checkmark benchmarking tool was introduced to provide a framework for application-oriented evaluation of watermarking schemes. In this article we introduce new attacks and applications into the existing Checkmark framework. In addition to describing new attacks and applications, we also compare the performance of some well-known watermarking algorithms (proposed by Bruyndonckx,Cox, Fridrich, Dugad, Kim, Wang, Xia, Xie, Zhu and Pereira) with respect to the Checkmark benchmark. In particular, we consider the non-geometric application which contains tests that do not change the geometry of image. This attack constraint is artificial, but yet important for research purposes since a number of algorithms may be interesting, but would score poorly with respect to specific applications simply because geometric compensation has not been incorporated. We note, however, that with the help of image registration, even research algorithms that do not have counter-measures against geometric distortion -- such as a template or reference watermark -- can be evaluated. In the first version of the Checkmark benchmarking program, application-oriented evaluation was introduced, along with many new attacks not already considered in the literature. A second goal of this paper is to introduce new attacks and new applications into the Checkmark framework. In particular, we introduce the following new applications: video frame watermarking, medical imaging and watermarking of logos. Video frame watermarking includes low compression attacks and distortions which warp the edges of the video as well as general projective transformations which may result from someone filming the screen at a cinema. With respect to medical imaging, only small distortions are considered and furthermore it is essential that no distortions are present at embedding. Finally for logos, we consider images of small sizes and particularly compression, scaling, aspect ratio and other small distortions. The challenge

Energy minimization of mobile video devices with a hardware H.264/AVC encoder based on energy-rate-distortion optimization

Science.gov (United States)

Kang, Donghun; Lee, Jungeon; Jung, Jongpil; Lee, Chul-Hee; Kyung, Chong-Min

2014-09-01

In mobile video systems powered by battery, reducing the encoder's compression energy consumption is critical to prolong its lifetime. Previous Energy-rate-distortion (E-R-D) optimization methods based on a software codec is not suitable for practical mobile camera systems because the energy consumption is too large and encoding rate is too low. In this paper, we propose an E-R-D model for the hardware codec based on the gate-level simulation framework to measure the switching activity and the energy consumption. From the proposed E-R-D model, an energy minimizing algorithm for mobile video camera sensor have been developed with the GOP (Group of Pictures) size and QP(Quantization Parameter) as run-time control variables. Our experimental results show that the proposed algorithm provides up to 31.76% of energy consumption saving while satisfying the rate and distortion constraints.

Robust efficient video fingerprinting

Science.gov (United States)

Puri, Manika; Lubin, Jeffrey

2009-02-01

We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

Hierarchical event selection for video storyboards with a case study on snooker video visualization.

Science.gov (United States)

Parry, Matthew L; Legg, Philip A; Chung, David H S; Griffiths, Iwan W; Chen, Min

2011-12-01

Video storyboard, which is a form of video visualization, summarizes the major events in a video using illustrative visualization. There are three main technical challenges in creating a video storyboard, (a) event classification, (b) event selection and (c) event illustration. Among these challenges, (a) is highly application-dependent and requires a significant amount of application specific semantics to be encoded in a system or manually specified by users. This paper focuses on challenges (b) and (c). In particular, we present a framework for hierarchical event representation, and an importance-based selection algorithm for supporting the creation of a video storyboard from a video. We consider the storyboard to be an event summarization for the whole video, whilst each individual illustration on the board is also an event summarization but for a smaller time window. We utilized a 3D visualization template for depicting and annotating events in illustrations. To demonstrate the concepts and algorithms developed, we use Snooker video visualization as a case study, because it has a concrete and agreeable set of semantic definitions for events and can make use of existing techniques of event detection and 3D reconstruction in a reliable manner. Nevertheless, most of our concepts and algorithms developed for challenges (b) and (c) can be applied to other application areas. © 2010 IEEE

Adaptive learning compressive tracking based on Markov location prediction

Science.gov (United States)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

Supercomputer implementation of finite element algorithms for high speed compressible flows. Progress report, period ending 30 June 1986

International Nuclear Information System (INIS)

Thornton, E.A.; Ramakrishnan, R.

1986-06-01

Prediction of compressible flow phenomena using the finite element method is of recent origin and considerable interest. Two shock capturing finite element formulations for high speed compressible flows are described. A Taylor-Galerkin formulation uses a Taylor series expansion in time coupled with a Galerkin weighted residual statement. The Taylor-Galerkin algorithms use explicit artificial dissipation, and the performance of three dissipation models are compared. A Petrov-Galerkin algorithm has as its basis the concepts of streamline upwinding. Vectorization strategies are developed to implement the finite element formulations on the NASA Langley VPS-32. The vectorization scheme results in finite element programs that use vectors of length of the order of the number of nodes or elements. The use of the vectorization procedure speeds up processing rates by over two orders of magnitude. The Taylor-Galerkin and Petrov-Galerkin algorithms are evaluated for 2D inviscid flows on criteria such as solution accuracy, shock resolution, computational speed and storage requirements. The convergence rates for both algorithms are enhanced by local time-stepping schemes. Extension of the vectorization procedure for predicting 2D viscous and 3D inviscid flows are demonstrated. Conclusions are drawn regarding the applicability of the finite element procedures for realistic problems that require hundreds of thousands of nodes

An efficient adaptive arithmetic coding image compression technology

International Nuclear Information System (INIS)

Wang Xing-Yuan; Yun Jiao-Jiao; Zhang Yong-Lei

2011-01-01

This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

A high-speed lossless data compression system for space applications

Science.gov (United States)

Miko, Joe; Fong, Wai; Miller, Warner

1993-01-01

This paper reports on the integration of a lossless data compression/decompression chipset into a space data system architecture. For its compression engine, the data system incorporates the Universal Source Encoder (USE) designed for the NASA/Goddard Space Flight Center. Currently, the data compression testbed generates video frames consisting of 512 lines of 512 pixels having 8-bit resolution. Each image is passed through the USE where the lines are internally partitioned into 16-word blocks. These blocks are adaptively encoded across widely varying entropy levels using a Rice 12-option set coding algorithm. The current system operates at an Input/Output rate of 10 Msamples/s or 80 Mbits/s for each buffered input line. Frame and line synchronization for each image are maintained through the use of uniquely decodable command words. Length information of each variable length compressed image line is also included in the output stream. The data and command information are passed to the next stage of the system architecture through a serial fiber-optic transmitter. The initial segment of this stage consists of packetizer hardware which adds an appropriate CCSDS header to the received source data. An uncompressed mode is optionally available to pass image lines directly to the packetizer hardware. A data decompression testbed has also been developed to confirm the data compression operation.

Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC

Directory of Open Access Journals (Sweden)

Sima Ahmadpour

2017-01-01

Full Text Available Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC video compression technique of three different movies.

Performance Analysis of Video Transmission Using Sequential Distortion Minimization Method for Digital Video Broadcasting Terrestrial

Directory of Open Access Journals (Sweden)

Novita Astin

2016-12-01

Full Text Available This paper presents about the transmission of Digital Video Broadcasting system with streaming video resolution 640x480 on different IQ rate and modulation. In the video transmission, distortion often occurs, so the received video has bad quality. Key frames selection algorithm is flexibel on a change of video, but on these methods, the temporal information of a video sequence is omitted. To minimize distortion between the original video and received video, we aimed at adding methodology using sequential distortion minimization algorithm. Its aim was to create a new video, better than original video without significant loss of content between the original video and received video, fixed sequentially. The reliability of video transmission was observed based on a constellation diagram, with the best result on IQ rate 2 Mhz and modulation 8 QAM. The best video transmission was also investigated using SEDIM (Sequential Distortion Minimization Method and without SEDIM. The experimental result showed that the PSNR (Peak Signal to Noise Ratio average of video transmission using SEDIM was an increase from 19,855 dB to 48,386 dB and SSIM (Structural Similarity average increase 10,49%. The experimental results and comparison of proposed method obtained a good performance. USRP board was used as RF front-end on 2,2 GHz.

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.

Halftoning processing on a JPEG-compressed image

Science.gov (United States)

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

2003-12-01

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

Effective Quality-of-Service Renegotiating Schemes for Streaming Video

Directory of Open Access Journals (Sweden)

Song Hwangjun

2004-01-01

Full Text Available This paper presents effective quality-of-service renegotiating schemes for streaming video. The conventional network supporting quality of service generally allows a negotiation at a call setup. However, it is not efficient for the video application since the compressed video traffic is statistically nonstationary. Thus, we consider the network supporting quality-of-service renegotiations during the data transmission and study effective quality-of-service renegotiating schemes for streaming video. The token bucket model, whose parameters are token filling rate and token bucket size, is adopted for the video traffic model. The renegotiating time instants and the parameters are determined by analyzing the statistical information of compressed video traffic. In this paper, two renegotiating approaches, that is, fixed renegotiating interval case and variable renegotiating interval case, are examined. Finally, the experimental results are provided to show the performance of the proposed schemes.

SVC VIDEO STREAM ALLOCATION AND ADAPTATION IN HETEROGENEOUS NETWORK

Directory of Open Access Journals (Sweden)

E. A. Pakulova

2016-07-01

Full Text Available The paper deals with video data transmission in format H.264/SVC standard with QoS requirements satisfaction. The Sender-Side Path Scheduling (SSPS algorithm and Sender-Side Video Adaptation (SSVA algorithm were developed. SSPS algorithm gives the possibility to allocate video traffic among several interfaces while SSVA algorithm dynamically changes the quality of video sequence in relation to QoS requirements. It was shown that common usage of two developed algorithms enables to aggregate throughput of access networks, increase parameters of Quality of Experience and decrease losses in comparison with Round Robin algorithm. For evaluation of proposed solution, the set-up was made. The trace files with throughput of existing public networks were used in experiments. Based on this information the throughputs of networks were limited and losses for paths were set. The results of research may be used for study and transmission of video data in heterogeneous wireless networks.

Spectral Compressive Sensing with Polar Interpolation

DEFF Research Database (Denmark)

Fyhn, Karsten; Dadkhahi, Hamid; F. Duarte, Marco

2013-01-01

. In this paper, we introduce a greedy recovery algorithm that leverages a band-exclusion function and a polar interpolation function to address these two issues in spectral compressive sensing. Our algorithm is geared towards line spectral estimation from compressive measurements and outperforms most existing...

Incorporation of local dependent reliability information into the Prior Image Constrained Compressed Sensing (PICCS) reconstruction algorithm

International Nuclear Information System (INIS)

Vaegler, Sven; Sauer, Otto; Stsepankou, Dzmitry; Hesser, Juergen

2015-01-01

The reduction of dose in cone beam computer tomography (CBCT) arises from the decrease of the tube current for each projection as well as from the reduction of the number of projections. In order to maintain good image quality, sophisticated image reconstruction techniques are required. The Prior Image Constrained Compressed Sensing (PICCS) incorporates prior images into the reconstruction algorithm and outperforms the widespread used Feldkamp-Davis-Kress-algorithm (FDK) when the number of projections is reduced. However, prior images that contain major variations are not appropriately considered so far in PICCS. We therefore propose the partial-PICCS (pPICCS) algorithm. This framework is a problem-specific extension of PICCS and enables the incorporation of the reliability of the prior images additionally. We assumed that the prior images are composed of areas with large and small deviations. Accordingly, a weighting matrix considered the assigned areas in the objective function. We applied our algorithm to the problem of image reconstruction from few views by simulations with a computer phantom as well as on clinical CBCT projections from a head-and-neck case. All prior images contained large local variations. The reconstructed images were compared to the reconstruction results by the FDK-algorithm, by Compressed Sensing (CS) and by PICCS. To show the gain of image quality we compared image details with the reference image and used quantitative metrics (root-mean-square error (RMSE), contrast-to-noise-ratio (CNR)). The pPICCS reconstruction framework yield images with substantially improved quality even when the number of projections was very small. The images contained less streaking, blurring and inaccurately reconstructed structures compared to the images reconstructed by FDK, CS and conventional PICCS. The increased image quality is also reflected in large RMSE differences. We proposed a modification of the original PICCS algorithm. The pPICCS algorithm

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.

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.

LZ-Compressed String Dictionaries

OpenAIRE

Arz, Julian; Fischer, Johannes

2013-01-01

We show how to compress string dictionaries using the Lempel-Ziv (LZ78) data compression algorithm. Our approach is validated experimentally on dictionaries of up to 1.5 GB of uncompressed text. We achieve compression ratios often outperforming the existing alternatives, especially on dictionaries containing many repeated substrings. Our query times remain competitive.

Sub-component modeling for face image reconstruction in video communications

Science.gov (United States)

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

2008-08-01

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

Compression and fast retrieval of SNP data.

Science.gov (United States)

Sambo, Francesco; Di Camillo, Barbara; Toffolo, Gianna; Cobelli, Claudio

2014-11-01

The increasing interest in rare genetic variants and epistatic genetic effects on complex phenotypic traits is currently pushing genome-wide association study design towards datasets of increasing size, both in the number of studied subjects and in the number of genotyped single nucleotide polymorphisms (SNPs). This, in turn, is leading to a compelling need for new methods for compression and fast retrieval of SNP data. We present a novel algorithm and file format for compressing and retrieving SNP data, specifically designed for large-scale association studies. Our algorithm is based on two main ideas: (i) compress linkage disequilibrium blocks in terms of differences with a reference SNP and (ii) compress reference SNPs exploiting information on their call rate and minor allele frequency. Tested on two SNP datasets and compared with several state-of-the-art software tools, our compression algorithm is shown to be competitive in terms of compression rate and to outperform all tools in terms of time to load compressed data. Our compression and decompression algorithms are implemented in a C++ library, are released under the GNU General Public License and are freely downloadable from http://www.dei.unipd.it/~sambofra/snpack.html. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

No Reference Video-Quality-Assessment Model for Monitoring Video Quality of IPTV Services

Science.gov (United States)

Yamagishi, Kazuhisa; Okamoto, Jun; Hayashi, Takanori; Takahashi, Akira

Service providers should monitor the quality of experience of a communication service in real time to confirm its status. To do this, we previously proposed a packet-layer model that can be used for monitoring the average video quality of typical Internet protocol television content using parameters derived from transmitted packet headers. However, it is difficult to monitor the video quality per user using the average video quality because video quality depends on the video content. To accurately monitor the video quality per user, a model that can be used for estimating the video quality per video content rather than the average video quality should be developed. Therefore, to take into account the impact of video content on video quality, we propose a model that calculates the difference in video quality between the video quality of the estimation-target video and the average video quality estimated using a packet-layer model. We first conducted extensive subjective quality assessments for different codecs and video sequences. We then model their characteristics based on parameters related to compression and packet loss. Finally, we verify the performance of the proposed model by applying it to unknown data sets different from the training data sets used for developing the model.

The compressed word problem for groups

CERN Document Server

Lohrey, Markus

2014-01-01

The Compressed Word Problem for Groups provides a detailed exposition of known results on the compressed word problem, emphasizing efficient algorithms for the compressed word problem in various groups. The author presents the necessary background along with the most recent results on the compressed word problem to create a cohesive self-contained book accessible to computer scientists as well as mathematicians. Readers will quickly reach the frontier of current research which makes the book especially appealing for students looking for a currently active research topic at the intersection of group theory and computer science. The word problem introduced in 1910 by Max Dehn is one of the most important decision problems in group theory. For many groups, highly efficient algorithms for the word problem exist. In recent years, a new technique based on data compression for providing more efficient algorithms for word problems, has been developed, by representing long words over group generators in a compres...

ADAPTIVE STREAMING OVER HTTP (DASH UNTUK APLIKASI VIDEO STREAMING

Directory of Open Access Journals (Sweden)

I Made Oka Widyantara

2015-12-01

Full Text Available This paper aims to analyze Internet-based streaming video service in the communication media with variable bit rates. The proposed scheme on Dynamic Adaptive Streaming over HTTP (DASH using the internet network that adapts to the protocol Hyper Text Transfer Protocol (HTTP. DASH technology allows a video in the video segmentation into several packages that will distreamingkan. DASH initial stage is to compress the video source to lower the bit rate video codec uses H.26. Video compressed further in the segmentation using MP4Box generates streaming packets with the specified duration. These packages are assembled into packets in a streaming media format Presentation Description (MPD or known as MPEG-DASH. Streaming video format MPEG-DASH run on a platform with the player bitdash teritegrasi bitcoin. With this scheme, the video will have several variants of the bit rates that gave rise to the concept of scalability of streaming video services on the client side. The main target of the mechanism is smooth the MPEG-DASH streaming video display on the client. The simulation results show that the scheme based scalable video streaming MPEG-DASH able to improve the quality of image display on the client side, where the procedure bufering videos can be made constant and fine for the duration of video views

Hybrid compression of video with graphics in DTV communication systems

OpenAIRE

Schaar, van der, M.; With, de, P.H.N.

2000-01-01

Advanced broadcast manipulation of TV sequences and enhanced user interfaces for TV systems have resulted in an increased amount of pre- and post-editing of video sequences, where graphical information is inserted. However, in the current broadcasting chain, there are no provisions for enabling an efficient transmission/storage of these mixed video and graphics signals and, at this emerging stage of DTV systems, introducing new standards is not desired. Nevertheless, in the professional video...

Robust steganographic method utilizing properties of MJPEG compression standard

Directory of Open Access Journals (Sweden)

Jakub Oravec

2015-06-01

Full Text Available This article presents design of steganographic method, which uses video container as cover data. Video track was recorded by webcam and was further encoded by compression standard MJPEG. Proposed method also takes in account effects of lossy compression. The embedding process is realized by switching places of transform coefficients, which are computed by Discrete Cosine Transform. The article contains possibilities, used techniques, advantages and drawbacks of chosen solution. The results are presented at the end of the article.

High speed fluorescence imaging with compressed ultrafast photography

Science.gov (United States)

Thompson, J. V.; Mason, J. D.; Beier, H. T.; Bixler, J. N.

2017-02-01

Fluorescent lifetime imaging is an optical technique that facilitates imaging molecular interactions and cellular functions. Because the excited lifetime of a fluorophore is sensitive to its local microenvironment,1, 2 measurement of fluorescent lifetimes can be used to accurately detect regional changes in temperature, pH, and ion concentration. However, typical state of the art fluorescent lifetime methods are severely limited when it comes to acquisition time (on the order of seconds to minutes) and video rate imaging. Here we show that compressed ultrafast photography (CUP) can be used in conjunction with fluorescent lifetime imaging to overcome these acquisition rate limitations. Frame rates up to one hundred billion frames per second have been demonstrated with compressed ultrafast photography using a streak camera.3 These rates are achieved by encoding time in the spatial direction with a pseudo-random binary pattern. The time domain information is then reconstructed using a compressed sensing algorithm, resulting in a cube of data (x,y,t) for each readout image. Thus, application of compressed ultrafast photography will allow us to acquire an entire fluorescent lifetime image with a single laser pulse. Using a streak camera with a high-speed CMOS camera, acquisition rates of 100 frames per second can be achieved, which will significantly enhance our ability to quantitatively measure complex biological events with high spatial and temporal resolution. In particular, we will demonstrate the ability of this technique to do single-shot fluorescent lifetime imaging of cells and microspheres.

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

Moving image compression and generalization capability of constructive neural networks

Science.gov (United States)

Ma, Liying; Khorasani, Khashayar

2001-03-01

To date numerous techniques have been proposed to compress digital images to ease their storage and transmission over communication channels. Recently, a number of image compression algorithms using Neural Networks NNs have been developed. Particularly, several constructive feed-forward neural networks FNNs have been proposed by researchers for image compression, and promising results have been reported. At the previous SPIE AeroSense conference 2000, we proposed to use a constructive One-Hidden-Layer Feedforward Neural Network OHL-FNN for compressing digital images. In this paper, we first investigate the generalization capability of the proposed OHL-FNN in the presence of additive noise for network training and/ or generalization. Extensive experimental results for different scenarios are presented. It is revealed that the constructive OHL-FNN is not as robust to additive noise in input image as expected. Next, the constructive OHL-FNN is applied to moving images, video sequences. The first, or other specified frame in a moving image sequence is used to train the network. The remaining moving images that follow are then generalized/compressed by this trained network. Three types of correlation-like criteria measuring the similarity of any two images are introduced. The relationship between the generalization capability of the constructed net and the similarity of images is investigated in some detail. It is shown that the constructive OHL-FNN is promising even for changing images such as those extracted from a football game.

Search in Real-Time Video Games

OpenAIRE

Cowling, Peter I.; Buro, Michael; Bida, Michal; Botea, Adi; Bouzy, Bruno; Butz, Martin V.; Hingston, Philip; Muñoz-Avila, Hector; Nau, Dana; Sipper, Moshe

2013-01-01

This chapter arises from the discussions of an experienced international group of researchers interested in the potential for creative application of algorithms for searching finite discrete graphs, which have been highly successful in a wide range of application areas, to address a broad range of problems arising in video games. The chapter first summarises the state of the art in search algorithms for games. It then considers the challenges in implementing these algorithms in video games (p...

Intelligent video surveillance systems

CERN Document Server

Dufour, Jean-Yves

2012-01-01

Belonging to the wider academic field of computer vision, video analytics has aroused a phenomenal surge of interest since the current millennium. Video analytics is intended to solve the problem of the incapability of exploiting video streams in real time for the purpose of detection or anticipation. It involves analyzing the videos using algorithms that detect and track objects of interest over time and that indicate the presence of events or suspect behavior involving these objects.The aims of this book are to highlight the operational attempts of video analytics, to identify possi

Methods and Algorithms for Detecting Objects in Video Files

Directory of Open Access Journals (Sweden)

Nguyen The Cuong

2018-01-01

Full Text Available Video files are files that store motion pictures and sounds like in real life. In today's world, the need for automated processing of information in video files is increasing. Automated processing of information has a wide range of application including office/home surveillance cameras, traffic control, sports applications, remote object detection, and others. In particular, detection and tracking of object movement in video file plays an important role. This article describes the methods of detecting objects in video files. Today, this problem in the field of computer vision is being studied worldwide.

Wavelet compression algorithm applied to abdominal ultrasound images

International Nuclear Information System (INIS)

Lin, Cheng-Hsun; Pan, Su-Feng; LU, Chin-Yuan; Lee, Ming-Che

2006-01-01

We sought to investigate acceptable compression ratios of lossy wavelet compression on 640 x 480 x 8 abdominal ultrasound (US) images. We acquired 100 abdominal US images with normal and abnormal findings from the view station of a 932-bed teaching hospital. The US images were then compressed at quality factors (QFs) of 3, 10, 30, and 50 followed outcomes of a pilot study. This was equal to the average compression ratios of 4.3:1, 8.5:1, 20:1 and 36.6:1, respectively. Four objective measurements were carried out to examine and compare the image degradation between original and compressed images. Receiver operating characteristic (ROC) analysis was also introduced for subjective assessment. Five experienced and qualified radiologists as reviewers blinded to corresponding pathological findings, analysed paired 400 randomly ordered images with two 17-inch thin film transistor/liquid crystal display (TFT/LCD) monitors. At ROC analysis, the average area under curve (Az) for US abdominal image was 0.874 at the ratio of 36.6:1. The compressed image size was only 2.7% for US original at this ratio. The objective parameters showed the higher the mean squared error (MSE) or root mean squared error (RMSE) values, the poorer the image quality. The higher signal-to-noise ratio (SNR) or peak signal-to-noise ratio (PSNR) values indicated better image quality. The average RMSE, PSNR at 36.6:1 for US were 4.84 ± 0.14, 35.45 dB, respectively. This finding suggests that, on the basis of the patient sample, wavelet compression of abdominal US to a ratio of 36.6:1 did not adversely affect diagnostic performance or evaluation error for radiologists' interpretation so as to risk affecting diagnosis

Scalable video on demand adaptive Internet-based distribution

CERN Document Server

Zink, Michael

2013-01-01

In recent years, the proliferation of available video content and the popularity of the Internet have encouraged service providers to develop new ways of distributing content to clients. Increasing video scaling ratios and advanced digital signal processing techniques have led to Internet Video-on-Demand applications, but these currently lack efficiency and quality. Scalable Video on Demand: Adaptive Internet-based Distribution examines how current video compression and streaming can be used to deliver high-quality applications over the Internet. In addition to analysing the problems

High bit depth infrared image compression via low bit depth codecs

Science.gov (United States)

Belyaev, Evgeny; Mantel, Claire; Forchhammer, Søren

2017-08-01

Future infrared remote sensing systems, such as monitoring of the Earth's environment by satellites, infrastructure inspection by unmanned airborne vehicles etc., will require 16 bit depth infrared images to be compressed and stored or transmitted for further analysis. Such systems are equipped with low power embedded platforms where image or video data is compressed by a hardware block called the video processing unit (VPU). However, in many cases using two 8-bit VPUs can provide advantages compared with using higher bit depth image compression directly. We propose to compress 16 bit depth images via 8 bit depth codecs in the following way. First, an input 16 bit depth image is mapped into 8 bit depth images, e.g., the first image contains only the most significant bytes (MSB image) and the second one contains only the least significant bytes (LSB image). Then each image is compressed by an image or video codec with 8 bits per pixel input format. We analyze how the compression parameters for both MSB and LSB images should be chosen to provide the maximum objective quality for a given compression ratio. Finally, we apply the proposed infrared image compression method utilizing JPEG and H.264/AVC codecs, which are usually available in efficient implementations, and compare their rate-distortion performance with JPEG2000, JPEG-XT and H.265/HEVC codecs supporting direct compression of infrared images in 16 bit depth format. A preliminary result shows that two 8 bit H.264/AVC codecs can achieve similar result as 16 bit HEVC codec.

Medical image compression and its application to TDIS-FILE equipment

International Nuclear Information System (INIS)

Tsubura, Shin-ichi; Nishihara, Eitaro; Iwai, Shunsuke

1990-01-01

In order to compress medical images for filing and communication, we have developed a compression algorithm which compresses images with remarkable quality using a high-pass filtering method. Hardware for this compression algorithm was also developed and applied to TDIS (total digital imaging system)-FILE equipment. In the future, hardware based on this algorithm will be developed for various types of diagnostic equipment and PACS. This technique has the following characteristics: (1) significant reduction of artifacts; (2) acceptable quality for clinical evaluation at 15:1 to 20:1 compression ratio; and (3) high-speed processing and compact hardware. (author)

Video Toroid Cavity Imager

Energy Technology Data Exchange (ETDEWEB)

Gerald, Rex E. II; Sanchez, Jairo; Rathke, Jerome W.

2004-08-10

A video toroid cavity imager for in situ measurement of electrochemical properties of an electrolytic material sample includes a cylindrical toroid cavity resonator containing the sample and employs NMR and video imaging for providing high-resolution spectral and visual information of molecular characteristics of the sample on a real-time basis. A large magnetic field is applied to the sample under controlled temperature and pressure conditions to simultaneously provide NMR spectroscopy and video imaging capabilities for investigating electrochemical transformations of materials or the evolution of long-range molecular aggregation during cooling of hydrocarbon melts. The video toroid cavity imager includes a miniature commercial video camera with an adjustable lens, a modified compression coin cell imager with a fiat circular principal detector element, and a sample mounted on a transparent circular glass disk, and provides NMR information as well as a video image of a sample, such as a polymer film, with micrometer resolution.

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

Discrete cosine and sine transforms general properties, fast algorithms and integer approximations

CERN Document Server

Britanak, Vladimir; Rao, K R; Rao, K R

2006-01-01

The Discrete Cosine Transform (DCT) is used in many applications by the scientific, engineering and research communities and in data compression in particular. Fast algorithms and applications of the DCT Type II (DCT-II) have become the heart of many established international image/video coding standards. Since then other forms of the DCT and Discrete Sine Transform (DST) have been investigated in detail. This new edition presents the complete set of DCT and DST discrete trigonometric transforms, including their definitions, general mathematical properties, and relations to the optimal Karhune

Effect of JPEG2000 mammogram compression on microcalcifications segmentation

International Nuclear Information System (INIS)

Georgiev, V.; Arikidis, N.; Karahaliou, A.; Skiadopoulos, S.; Costaridou, L.

2012-01-01

The purpose of this study is to investigate the effect of mammographic image compression on the automated segmentation of individual microcalcifications. The dataset consisted of individual microcalcifications of 105 clusters originating from mammograms of the Digital Database for Screening Mammography. A JPEG2000 wavelet-based compression algorithm was used for compressing mammograms at 7 compression ratios (CRs): 10:1, 20:1, 30:1, 40:1, 50:1, 70:1 and 100:1. A gradient-based active contours segmentation algorithm was employed for segmentation of microcalcifications as depicted on original and compressed mammograms. The performance of the microcalcification segmentation algorithm on original and compressed mammograms was evaluated by means of the area overlap measure (AOM) and distance differentiation metrics (d mean and d max ) by comparing automatically derived microcalcification borders to manually defined ones by an expert radiologist. The AOM monotonically decreased as CR increased, while d mean and d max metrics monotonically increased with CR increase. The performance of the segmentation algorithm on original mammograms was (mean±standard deviation): AOM=0.91±0.08, d mean =0.06±0.05 and d max =0.45±0.20, while on 40:1 compressed images the algorithm's performance was: AOM=0.69±0.15, d mean =0.23±0.13 and d max =0.92±0.39. Mammographic image compression deteriorates the performance of the segmentation algorithm, influencing the quantification of individual microcalcification morphological properties and subsequently affecting computer aided diagnosis of microcalcification clusters. (authors)

Compressing an Ensemble with Statistical Models: An Algorithm for Global 3D Spatio-Temporal Temperature

KAUST Repository

Castruccio, Stefano; Genton, Marc G.

2015-01-01

One of the main challenges when working with modern climate model ensembles is the increasingly larger size of the data produced, and the consequent difficulty in storing large amounts of spatio-temporally resolved information. Many compression algorithms can be used to mitigate this problem, but since they are designed to compress generic scientific data sets, they do not account for the nature of climate model output and they compress only individual simulations. In this work, we propose a different, statistics-based approach that explicitly accounts for the space-time dependence of the data for annual global three-dimensional temperature fields in an initial condition ensemble. The set of estimated parameters is small (compared to the data size) and can be regarded as a summary of the essential structure of the ensemble output; therefore, it can be used to instantaneously reproduce the temperature fields in an ensemble with a substantial saving in storage and time. The statistical model exploits the gridded geometry of the data and parallelization across processors. It is therefore computationally convenient and allows to fit a non-trivial model to a data set of one billion data points with a covariance matrix comprising of 10^18 entries.

Compressing an Ensemble with Statistical Models: An Algorithm for Global 3D Spatio-Temporal Temperature

KAUST Repository

Castruccio, Stefano

2015-04-02

One of the main challenges when working with modern climate model ensembles is the increasingly larger size of the data produced, and the consequent difficulty in storing large amounts of spatio-temporally resolved information. Many compression algorithms can be used to mitigate this problem, but since they are designed to compress generic scientific data sets, they do not account for the nature of climate model output and they compress only individual simulations. In this work, we propose a different, statistics-based approach that explicitly accounts for the space-time dependence of the data for annual global three-dimensional temperature fields in an initial condition ensemble. The set of estimated parameters is small (compared to the data size) and can be regarded as a summary of the essential structure of the ensemble output; therefore, it can be used to instantaneously reproduce the temperature fields in an ensemble with a substantial saving in storage and time. The statistical model exploits the gridded geometry of the data and parallelization across processors. It is therefore computationally convenient and allows to fit a non-trivial model to a data set of one billion data points with a covariance matrix comprising of 10^18 entries.

Impulsive noise removal from color video with morphological filtering

Science.gov (United States)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper deals with impulse noise removal from color video. The proposed noise removal algorithm employs a switching filtering for denoising of color video; that is, detection of corrupted pixels by means of a novel morphological filtering followed by removal of the detected pixels on the base of estimation of uncorrupted pixels in the previous scenes. With the help of computer simulation we show that the proposed algorithm is able to well remove impulse noise in color video. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

Video processing for human perceptual visual quality-oriented video coding.

Science.gov (United States)

Oh, Hyungsuk; Kim, Wonha

2013-04-01

We have developed a video processing method that achieves human perceptual visual quality-oriented video coding. The patterns of moving objects are modeled by considering the limited human capacity for spatial-temporal resolution and the visual sensory memory together, and an online moving pattern classifier is devised by using the Hedge algorithm. The moving pattern classifier is embedded in the existing visual saliency with the purpose of providing a human perceptual video quality saliency model. In order to apply the developed saliency model to video coding, the conventional foveation filtering method is extended. The proposed foveation filter can smooth and enhance the video signals locally, in conformance with the developed saliency model, without causing any artifacts. The performance evaluation results confirm that the proposed video processing method shows reliable improvements in the perceptual quality for various sequences and at various bandwidths, compared to existing saliency-based video coding methods.

A checkpoint compression study for high-performance computing systems

Energy Technology Data Exchange (ETDEWEB)

Ibtesham, Dewan [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science; Ferreira, Kurt B. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States). Scalable System Software Dept.; Arnold, Dorian [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Computer Science

2015-02-17

As high-performance computing systems continue to increase in size and complexity, higher failure rates and increased overheads for checkpoint/restart (CR) protocols have raised concerns about the practical viability of CR protocols for future systems. Previously, compression has proven to be a viable approach for reducing checkpoint data volumes and, thereby, reducing CR protocol overhead leading to improved application performance. In this article, we further explore compression-based CR optimization by exploring its baseline performance and scaling properties, evaluating whether improved compression algorithms might lead to even better application performance and comparing checkpoint compression against and alongside other software- and hardware-based optimizations. Our results highlights are: (1) compression is a very viable CR optimization; (2) generic, text-based compression algorithms appear to perform near optimally for checkpoint data compression and faster compression algorithms will not lead to better application performance; (3) compression-based optimizations fare well against and alongside other software-based optimizations; and (4) while hardware-based optimizations outperform software-based ones, they are not as cost effective.

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.

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.

Reduced bandwidth video for remote vehicle operations

Energy Technology Data Exchange (ETDEWEB)

Noell, T.E.; DePiero, F.W.

1993-08-01

Oak Ridge National Laboratory staff have developed a video compression system for low-bandwidth remote operations. The objective is to provide real-time video at data rates comparable to available tactical radio links, typically 16 to 64 thousand bits per second (kbps), while maintaining sufficient quality to achieve mission objectives. The system supports both continuous lossy transmission of black and white (gray scale) video for remote driving and progressive lossless transmission of black and white images for remote automatic target acquisition. The average data rate of the resulting bit stream is 64 kbps. This system has been demonstrated to provide video of sufficient quality to allow remote driving of a High-Mobility Multipurpose Wheeled Vehicle at speeds up to 15 mph (24.1 kph) on a moguled dirt track. The nominal driving configuration provides a frame rate of 4 Hz, a compression per frame of 125:1, and a resulting latency of {approximately}1s. This paper reviews the system approach and implementation, and further describes some of our experiences when using the system to support remote driving.

On-line compression of symmetrical multidimensional γ-ray spectra using adaptive orthogonal transforms

International Nuclear Information System (INIS)

Morhac, M.; Matousek, V.

2008-01-01

The efficient algorithm to compress multidimensional symmetrical γ-ray events is presented. The reduction of data volume can be achieved due to both the symmetry of the γ-ray spectra and compression capabilities of the employed adaptive orthogonal transform. Illustrative examples prove in the favor of the proposed compression algorithm. The algorithm was implemented for on-line compression of events. Acquired compressed data can be later processed in an interactive way

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.

Dependency of human target detection performance on clutter and quality of supporting image analysis algorithms in a video surveillance task

Science.gov (United States)

Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin

2017-10-01

Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.

The MUSIC algorithm for sparse objects: a compressed sensing analysis

International Nuclear Information System (INIS)

Fannjiang, Albert C

2011-01-01

The multiple signal classification (MUSIC) algorithm, and its extension for imaging sparse extended objects, with noisy data is analyzed by compressed sensing (CS) techniques. A thresholding rule is developed to augment the standard MUSIC algorithm. The notion of restricted isometry property (RIP) and an upper bound on the restricted isometry constant (RIC) are employed to establish sufficient conditions for the exact localization by MUSIC with or without noise. In the noiseless case, the sufficient condition gives an upper bound on the numbers of random sampling and incident directions necessary for exact localization. In the noisy case, the sufficient condition assumes additionally an upper bound for the noise-to-object ratio in terms of the RIC and the dynamic range of objects. This bound points to the super-resolution capability of the MUSIC algorithm. Rigorous comparison of performance between MUSIC and the CS minimization principle, basis pursuit denoising (BPDN), is given. In general, the MUSIC algorithm guarantees to recover, with high probability, s scatterers with n=O(s 2 ) random sampling and incident directions and sufficiently high frequency. For the favorable imaging geometry where the scatterers are distributed on a transverse plane MUSIC guarantees to recover, with high probability, s scatterers with a median frequency and n=O(s) random sampling/incident directions. Moreover, for the problems of spectral estimation and source localizations both BPDN and MUSIC guarantee, with high probability, to identify exactly the frequencies of random signals with the number n=O(s) of sampling times. However, in the absence of abundant realizations of signals, BPDN is the preferred method for spectral estimation. Indeed, BPDN can identify the frequencies approximately with just one realization of signals with the recovery error at worst linearly proportional to the noise level. Numerical results confirm that BPDN outperforms MUSIC in the well-resolved case while

Utilization of KSC Present Broadband Communications Data System for Digital Video Services

Science.gov (United States)

Andrawis, Alfred S.

2002-01-01

This report covers a visibility study of utilizing present KSC broadband communications data system (BCDS) for digital video services. Digital video services include compressed digital TV delivery and video-on-demand. Furthermore, the study examines the possibility of providing interactive video on demand to desktop personal computers via KSC computer network.

Adaptive live multicast video streaming of SVC with UEP FEC

Science.gov (United States)

Lev, Avram; Lasry, Amir; Loants, Maoz; Hadar, Ofer

2014-09-01

Ideally, video streaming systems should provide the best quality video a user's device can handle without compromising on downloading speed. In this article, an improved video transmission system is presented which dynamically enhances the video quality based on a user's current network state and repairs errors from data lost in the video transmission. The system incorporates three main components: Scalable Video Coding (SVC) with three layers, multicast based on Receiver Layered Multicast (RLM) and an UnEqual Forward Error Correction (FEC) algorithm. The SVC provides an efficient method for providing different levels of video quality, stored as enhancement layers. In the presented system, a proportional-integral-derivative (PID) controller was implemented to dynamically adjust the video quality, adding or subtracting quality layers as appropriate. In addition, an FEC algorithm was added to compensate for data lost in transmission. A two dimensional FEC was used. The FEC algorithm came from the Pro MPEG code of practice #3 release 2. Several bit errors scenarios were tested (step function, cosine wave) with different bandwidth size and error values were simulated. The suggested scheme which includes SVC video encoding with 3 layers over IP Multicast with Unequal FEC algorithm was investigated under different channel conditions, variable bandwidths and different bit error rates. The results indicate improvement of the video quality in terms of PSNR over previous transmission schemes.

Three dimensional range geometry and texture data compression with space-filling curves.

Science.gov (United States)

Chen, Xia; Zhang, Song

2017-10-16

This paper presents a novel method to effectively store three-dimensional (3D) data and 2D texture data into a regular 24-bit image. The proposed method uses the Hilbert space-filling curve to map the normalized unwrapped phase map to two 8-bit color channels, and saves the third color channel for 2D texture storage. By further leveraging existing 2D image and video compression techniques, the proposed method can achieve high compression ratios while effectively preserving data quality. Since the encoding and decoding processes can be applied to most of the current 2D media platforms, this proposed compression method can make 3D data storage and transmission available for many electrical devices without requiring special hardware changes. Experiments demonstrate that if a lossless 2D image/video format is used, both original 3D geometry and 2D color texture can be accurately recovered; if lossy image/video compression is used, only black-and-white or grayscale texture can be properly recovered, but much higher compression ratios (e.g., 1543:1 against the ASCII OBJ format) are achieved with slight loss of 3D geometry quality.

Video Inpainting of Complex Scenes

OpenAIRE

Newson, Alasdair; Almansa, Andrés; Fradet, Matthieu; Gousseau, Yann; Pérez, Patrick

2015-01-01

We propose an automatic video inpainting algorithm which relies on the optimisation of a global, patch-based functional. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such as the correct reconstruction of dynamic textures, multiple moving objects and moving background. Furthermore, we achieve this in an order of magnitude less execution time with respect to the state-of-the-art. We are also able to achieve good quality result...

Fast Compressive Tracking.

Science.gov (United States)

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

SAD PROCESSOR FOR MULTIPLE MACROBLOCK MATCHING IN FAST SEARCH VIDEO MOTION ESTIMATION

Directory of Open Access Journals (Sweden)

Nehal N. Shah

2015-02-01

Full Text Available Motion estimation is a very important but computationally complex task in video coding. Process of determining motion vectors based on the temporal correlation of consecutive frame is used for video compression. In order to reduce the computational complexity of motion estimation and maintain the quality of encoding during motion compensation, different fast search techniques are available. These block based motion estimation algorithms use the sum of absolute difference (SAD between corresponding macroblock in current frame and all the candidate macroblocks in the reference frame to identify best match. Existing implementations can perform SAD between two blocks using sequential or pipeline approach but performing multi operand SAD in single clock cycle with optimized recourses is state of art. In this paper various parallel architectures for computation of the fixed block size SAD is evaluated and fast parallel SAD architecture is proposed with optimized resources. Further SAD processor is described with 9 processing elements which can be configured for any existing fast search block matching algorithm. Proposed SAD processor consumes 7% fewer adders compared to existing implementation for one processing elements. Using nine PE it can process 84 HD frames per second in worse case which is good outcome for real time implementation. In average case architecture process 325 HD frames per second.

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

Compressed Subsequence Matching and Packed Tree Coloring

DEFF Research Database (Denmark)

Bille, Philip; Cording, Patrick Hagge; Gørtz, Inge Li

2017-01-01

We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size n compressing a string of size N and a pattern string of size m over an alphabet of size \\(\\sigma \\), our algorithm uses \\(O(n+\\frac{n\\sigma }{w})\\) space and \\(O(n+\\frac{n\\sigma }{w}+m\\log N\\log...... w\\cdot occ)\\) or \\(O(n+\\frac{n\\sigma }{w}\\log w+m\\log N\\cdot occ)\\) time. Here w is the word size and occ is the number of minimal occurrences of the pattern. Our algorithm uses less space than previous algorithms and is also faster for \\(occ=o(\\frac{n}{\\log N})\\) occurrences. The algorithm uses...... a new data structure that allows us to efficiently find the next occurrence of a given character after a given position in a compressed string. This data structure in turn is based on a new data structure for the tree color problem, where the node colors are packed in bit strings....

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

Science.gov (United States)

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

On the data compression at filmless readout of the streamer chamber information

International Nuclear Information System (INIS)

Bajla, I.; Ososkov, G.A.; Prikhod'ko, V.I.

1980-01-01

It is supposed that the system of filmless detecting and processing the visual information from ''RISK'' streamer chamber will comprise the effective on-line data compression algorithm. The role of the basic methodological principles of chamber image film processing in Righ Energy Physics for building up such system is analysed. On the basis of this analysis the main requirements are formulated that have to be fulfilled by the compression algorithm. The most important requirement consists in securing the possibility of the input data reprocessing, if problems in the off-line recognition occur. Using a vector system representation of primary data, the on-line data compression philosophy is proposed that embodies the following three principles: universality, parallelism and input data reconstructibility. Excluding of the recognition procedure from the on-line compression algorithm causes the compression factor reduction. The hierarchic structure of the compression algorithm consisting of (1) sorting, (2) filtering, (3) compression for an additional increasing of the compression ratio is proposed

Compressed sensing & sparse filtering

CERN Document Server

Carmi, Avishy Y; Godsill, Simon J

2013-01-01

This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related app

Fast and efficient search for MPEG-4 video using adjacent pixel intensity difference quantization histogram feature

Science.gov (United States)

Lee, Feifei; Kotani, Koji; Chen, Qiu; Ohmi, Tadahiro

2010-02-01

In this paper, a fast search algorithm for MPEG-4 video clips from video database is proposed. An adjacent pixel intensity difference quantization (APIDQ) histogram is utilized as the feature vector of VOP (video object plane), which had been reliably applied to human face recognition previously. Instead of fully decompressed video sequence, partially decoded data, namely DC sequence of the video object are extracted from the video sequence. Combined with active search, a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by total 15 hours of video contained of TV programs such as drama, talk, news, etc. to search for given 200 MPEG-4 video clips which each length is 15 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 80ms, and Equal Error Rate (ERR) of 2 % in drama and news categories are achieved, which are more accurately and robust than conventional fast video search algorithm.

Indexing Motion Detection Data for Surveillance Video

DEFF Research Database (Denmark)

Vind, Søren Juhl; Bille, Philip; Gørtz, Inge Li

2014-01-01

We show how to compactly index video data to support fast motion detection queries. A query specifies a time interval T, a area A in the video and two thresholds v and p. The answer to a query is a list of timestamps in T where ≥ p% of A has changed by ≥ v values. Our results show that by building...... a small index, we can support queries with a speedup of two to three orders of magnitude compared to motion detection without an index. For high resolution video, the index size is about 20% of the compressed video size....

COxSwAIN: Compressive Sensing for Advanced Imaging and Navigation

Science.gov (United States)

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

2015-01-01

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

General Video Game AI: Learning from Screen Capture

OpenAIRE

Kunanusont, Kamolwan; Lucas, Simon M.; Perez-Liebana, Diego

2017-01-01

General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, th...

Semantic-based surveillance video retrieval.

Science.gov (United States)

Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Visual Perception Based Rate Control Algorithm for HEVC

Science.gov (United States)

Feng, Zeqi; Liu, PengYu; Jia, Kebin

2018-01-01

For HEVC, rate control is an indispensably important video coding technology to alleviate the contradiction between video quality and the limited encoding resources during video communication. However, the rate control benchmark algorithm of HEVC ignores subjective visual perception. For key focus regions, bit allocation of LCU is not ideal and subjective quality is unsatisfied. In this paper, a visual perception based rate control algorithm for HEVC is proposed. First bit allocation weight of LCU level is optimized based on the visual perception of luminance and motion to ameliorate video subjective quality. Then λ and QP are adjusted in combination with the bit allocation weight to improve rate distortion performance. Experimental results show that the proposed algorithm reduces average 0.5% BD-BR and maximum 1.09% BD-BR at no cost in bitrate accuracy compared with HEVC (HM15.0). The proposed algorithm devotes to improving video subjective quality under various video applications.

MEDICAL IMAGE COMPRESSION USING HYBRID CODER WITH FUZZY EDGE DETECTION

Directory of Open Access Journals (Sweden)

K. Vidhya

2011-02-01

Full Text Available Medical imaging techniques produce prohibitive amounts of digitized clinical data. Compression of medical images is a must due to large memory space required for transmission and storage. This paper presents an effective algorithm to compress and to reconstruct medical images. The proposed algorithm first extracts edge information of medical images by using fuzzy edge detector. The images are decomposed using Cohen-Daubechies-Feauveau (CDF wavelet. The hybrid technique utilizes the efficient wavelet based compression algorithms such as JPEG2000 and Set Partitioning In Hierarchical Trees (SPIHT. The wavelet coefficients in the approximation sub band are encoded using tier 1 part of JPEG2000. The wavelet coefficients in the detailed sub bands are encoded using SPIHT. Consistent quality images are produced by this method at a lower bit rate compared to other standard compression algorithms. Two main approaches to assess image quality are objective testing and subjective testing. The image quality is evaluated by objective quality measures. Objective measures correlate well with the perceived image quality for the proposed compression algorithm.

Impact of Constant Rate Factor on Objective Video Quality Assessment

Directory of Open Access Journals (Sweden)

Juraj Bienik

2017-01-01

Full Text Available This paper deals with the impact of constant rate factor value on the objective video quality assessment using PSNR and SSIM metrics. Compression efficiency of H.264 and H.265 codecs defined by different Constant rate factor (CRF values was tested. The assessment was done for eight types of video sequences depending on content for High Definition (HD, Full HD (FHD and Ultra HD (UHD resolution. Finally, performance of both mentioned codecs with emphasis on compression ratio and efficiency of coding was compared.

Exploring compression techniques for ROOT IO

Science.gov (United States)

Zhang, Z.; Bockelman, B.

2017-10-01

ROOT provides an flexible format used throughout the HEP community. The number of use cases - from an archival data format to end-stage analysis - has required a number of tradeoffs to be exposed to the user. For example, a high “compression level” in the traditional DEFLATE algorithm will result in a smaller file (saving disk space) at the cost of slower decompression (costing CPU time when read). At the scale of the LHC experiment, poor design choices can result in terabytes of wasted space or wasted CPU time. We explore and attempt to quantify some of these tradeoffs. Specifically, we explore: the use of alternate compressing algorithms to optimize for read performance; an alternate method of compressing individual events to allow efficient random access; and a new approach to whole-file compression. Quantitative results are given, as well as guidance on how to make compression decisions for different use cases.

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

Science.gov (United States)

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

2017-08-01

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

Probable mode prediction for H.264 advanced video coding P slices using removable SKIP mode distortion estimation

Science.gov (United States)

You, Jongmin; Jeong, Jechang

2010-02-01

The H.264/AVC (advanced video coding) is used in a wide variety of applications including digital broadcasting and mobile applications, because of its high compression efficiency. The variable block mode scheme in H.264/AVC contributes much to its high compression efficiency but causes a selection problem. In general, rate-distortion optimization (RDO) is the optimal mode selection strategy, but it is computationally intensive. For this reason, the H.264/AVC encoder requires a fast mode selection algorithm for use in applications that require low-power and real-time processing. A probable mode prediction algorithm for the H.264/AVC encoder is proposed. To reduce the computational complexity of RDO, the proposed method selects probable modes among all allowed block modes using removable SKIP mode distortion estimation. Removable SKIP mode distortion is used to estimate whether or not a further divided block mode is appropriate for a macroblock. It is calculated using a no-motion reference block with a few computations. Then the proposed method reduces complexity by performing the RDO process only for probable modes. Experimental results show that the proposed algorithm can reduce encoding time by an average of 55.22% without significant visual quality degradation and increased bit rate.

Acquisition, compression and rendering of depth and texture for multi-view video

NARCIS (Netherlands)

Morvan, Y.

2009-01-01

Three-dimensional (3D) video and imaging technologies is an emerging trend in the development of digital video systems, as we presently witness the appearance of 3D displays, coding systems, and 3D camera setups. Three-dimensional multi-view video is typically obtained from a set of synchronized

Shadow Detection Based on Regions of Light Sources for Object Extraction in Nighttime Video

Directory of Open Access Journals (Sweden)

Gil-beom Lee

2017-03-01

Full Text Available Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground objects, interfere with ensuing processes, and finally degrade the event detection performance of the systems. Conventional studies have mostly used intensity, color, texture, and geometric information to perform shadow detection in daytime video, but these methods lack the capability of removing shadows in nighttime video. In this paper, a novel shadow detection algorithm for nighttime video is proposed; this algorithm partitions each foreground object based on the object’s vertical histogram and screens out shadow objects by validating their orientations heading toward regions of light sources. From the experimental results, it can be seen that the proposed algorithm shows more than 93.8% shadow removal and 89.9% object extraction rates for nighttime video sequences, and the algorithm outperforms conventional shadow removal algorithms designed for daytime videos.

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

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.