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IEEE Conference on Vehicular Technology (VTC)

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Variable resolution-adaptive sampling approach to image coding

Variable resolution-adaptive sampling approach to image codi...

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IEEE Southeastcon

作者： S. Liu M. Hayes School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA

Since the local characteristics of an image usually change from region to region, adaptive coding techniques are necessary to achieve high compression rates. An effective coding scheme is based on the principle of variable resolution image representation, where compression is generally achieved by adaptive sampling or subsampling. Various adaptive sampling schemes that are effective for image compression are developed and evaluated. The main focus is the design of the nonuniform sampling patterns associated with the sample selection process. Two different design procedures, based on nonrecursive and recursive image decomposition, are investigated. Simulation results indicate that some of the sampling schemes proposed here attain higher compression rates than other reported coders of this nature.< >

关键词： Image resolution Image sampling Image coding Nonuniform sampling Digital images Image reconstruction Bandwidth Degradation adaptive coding Focusing

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adaptive COMPRESSED SENSING - A NEW CLASS OF SELF-ORGANIZING coding MODELS FOR NEUROSCIENCE

ADAPTIVE COMPRESSED SENSING - A NEW CLASS OF SELF-ORGANIZING...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： William K. Coulter Christopher J. Hillar Guy Isley Friedrich T. Sommer University of California Berkeley 156 Stanley Hall MC 3220 Berkeley CA 94720-3220 Mathematical Sciences Research Institute 17 Gauss Way Berkeley CA 94120

ISBN: (纸本)9781424442959

Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. However, conventional sparse coding models require that the coding circuit can fully sample the sensory data in a one-to-one fashion, a requirement not supported by experimental data from the thalamo-cortical projection. To relieve these strict wiring requirements, we propose a sparse coding network constructed by introducing synaptic learning in the framework of compressed sensing. We demonstrate a new model that evolves biologically realistic, spatially smooth receptive fields despite the fact that the feedforward connectivity subsamples the input and thus the learning must rely on an impoverished and distorted account of the original visual data. Further, we demonstrate that the model could form a general scheme of cortical communication: it can form meaningful representations in a secondary sensory area, which receives input from the primary sensory area through a "compressing" cortico-cortical projection. Finally, we prove that our model belongs to a new class of sparse coding algorithms in which recurrent connections are essential in forming the spatial receptive fields.

关键词： adaptive coding biological system modeling random codes image coding nonlinear circuits Biological system modeling random codes adaptive coding Nonlinear circuits image coding Neurosciences Sparse coding Neurophysiology COMPRESSED

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adaptive Scheduling for Multicasting Hard Deadline Constrained Prioritized Data via Network coding

Adaptive Scheduling for Multicasting Hard Deadline Constrain...

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IEEE Global Communications Conference

作者： Tuan T. Tran Hongxiang Li Weiyao Lin Lingjia Liu Samee U. Khan Department of Electrical and Computer Engineering J.B. Speed School of Engineering University of Louisville Institute of Image Communication and Information Processing Shanghai Jiaotong University Department of Electrical Engineering and Computer Science The University of Kansas Department of Electrical and Computer Engineering North Dakota State University

ISBN: (纸本)9781467309202

Network coding offers a promising platform for multicast transmission by approaching its min-cut capacity. However, pushing the network throughput toward this upper bound comes with a sacrifice in delivery delay due to the decoding procedure that requires performing batch of coded packets. Further, in some transmission scenarios where the receivers experience deep fading or unable to collect a full set of the transmitted data, no useful information is recovered. The effect is more severe in the networks where the transmitted information has priority structure with hard deadline constraint due to the limited delivery time and data interdependencies. In this paper, we consider single-hop wireless networks where the transmitter wishes to multicast hard deadline constrained prioritized data to many receivers over lossy channels. We first study the network performance of a variety of transmission techniques, depending on how the transmitter schedules transmission in each time slot. We then propose an adaptive encoding and scheduling technique to maximize the network throughput. To find the optimal transmission scheduling at the presence of the network dynamics, we cast the problem in the framework of Markov Decision Processes (MDP) and use backward induction method to find an optimal solution. We further propose simulation-based algorithm and greedy scheduling technique that obtain high performance with much lower time complexity. Both analytical and simulation results have been provided to corroborate the effectiveness of the proposed techniques.

关键词： Multicast Hard deadline constraint Prioritized transmission adaptive scheduling Network coding adaptive scheduling Network coding Multicast Network throughput adaptive coding deep fading Transmission techniques

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adaptive-rate nonbinary LDPC coding for frequency-hop communications

Adaptive-rate nonbinary LDPC coding for frequency-hop commun...

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MILCOM, Military Communications Conference

作者： Michael B. Pursley Thomas C. Royster

We evaluate the performance of irregular low-density parity-check (LDPC) codes in slow frequency-hop spread-spectrum systems with nonbinary orthogonal modulation. We also evaluate the performance of two adaptive coding protocols for the LDPC codes. The protocols use information derived by the iterative decoder during the decoding of each packet to select the code rate for the next packet. Performance results are presented for static partial-band noise channels and for partial-band noise channels with time-varying interference bandwidth or power. The adaptive coding protocol is shown to have good performance, even on channels that cause some of the individual codes to exhibit nonmonotonic throughput.

关键词： Parity check codes Frequency Protocols adaptive coding Iterative decoding Spread spectrum communication Modulation coding Interference Bandwidth Throughput

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A new adaptive interframe transform coding using directional classification

A new adaptive interframe transform coding using directional...

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IEEE International Conference on Image Processing

作者： Yui-Lam Chan Wan-Chi Siu Department of Electronic Engineering Hong Kong Polytechnic Institute Kowloon Hong Kong China

ISBN: (纸本)0818669527

Interframe transform coding is affected not only by the statistics of spatial details within a frame, but also by the variation of the amount of movement and other temporal activities in different regions of the image sequence. Therefore, adaptive techniques have to be used in order to achieve good image quality. In this paper, we propose a new version of the adaptive interframe coding method, namely directional classification, which is based on image sequence statistics. Blocks with different perceptual features such as edges and high motion activity are categorised to different classes. Then, a new adaptive quantization, associated with appropriate scanning and Huffman coding, are employed based on the classification map. coding tests using computer simulation show this technique is indeed very efficient.< >

关键词： Transform coding Discrete cosine transforms Image sequences Statistics Image coding Quantization Computer simulation adaptive coding Frequency Bit rate

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REGION-adaptive PROBABILITY MODEL SELECTION FOR THE ARITHMETIC coding OF VIDEO TEXTURE

REGION-ADAPTIVE PROBABILITY MODEL SELECTION FOR THE ARITHMET...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： K. Vermeirsch J. Barbarien P. Lambert R. Van de Walle Department ofElectronics and Information Systems Faculty of Engineering Ghent University Belgium Department ofElectronics and Informatics (ETRO) Vrije Universiteit Brussel Belgium

ISBN: (纸本)9781457705380

In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process moves into an area with different texture. To avoid this inefficiency, we propose to replace the probability models used in the original coder with multiple switchable sets of probability models. We determine the model set to use in each spatial region in an optimal manner, taking into account the additional signaling overhead. Experimental results show that this approach, when applied to H.264/AVC's context-based adaptive binary arithmetic coder (CABAC), yields significant bit-rate savings, which are comparable to or higher than those obtained using alternative improvements to CABAC previously proposed in the literature.

关键词： Video coding CABAC arithmetic cod-ing adaptivity context modeling adaptive coding CABAC Videotapes textures ENCODER Probability

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An adaptive macroblock-group coding algorithm for progressive and interlaced video

An adaptive macroblock-group coding algorithm for progressiv...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Guoping Li Yun He State Key Laboratory on Micromave and Digital Communications Department of Electronic Engineering Tsinghua University Beijing China

ISBN: (纸本)078038251X

The paper proposes a new data structure called macroblock group (MBG). The MBG structure unifies the progressive and interlaced date into one general data format, thus enables a unifying process framework to conduct the progressive and interlaced video coding. Upon the new data structure, an adaptive MBG coding (A-MBG) method undertakes two-stage coding process, and it can well use the calculated and estimated encoding cost to select the best one among the MBG types, thus can finely adapt to the local contents of the pictures. The experiments are taken in comparison with the newly finalized H.264 standard. A-MBG shows an outperforming result to that of MBAFF in coding efficiency. In addition, because of using the same structure for both progressive and interlaced video, the structure complexity of A-MBG would be lower than that of MBAFF.

关键词： Costs Data structures Encoding adaptive coding Helium Digital communication Data engineering Video coding Automatic voltage control

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Region-based image coding with multiple algorithms

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2001年第3期39卷 562-570页

作者： Petrou, M Hou, PX Kamata, S Underwood, CI Univ Surrey Sch Elect Comp & Math Guildford GU2 7XH Surrey England Kyushu Univ Grad Sch Informat Sci & Elect Engn Dept Intelligent Syst Fukuoka 81281 Japan

The wide usage of small satellite imagery, especially its commercialization, makes data-based onboard compression not only meaningful but also necessary in order to solve the bottleneck between the huge volume of data generated onboard and the very limited downlink bandwidth. In this paper, we propose a method that encodes different regions with different algorithms. We use three shape-adaptive image compression algorithms as the candidates. The first one is a JPEG-based algorithm, the second one is based on the object-based wavelet transform (OWT) method proposed by [1], and the third adopts Hilbert scanning of the regions of interest followed by one-dimensional (1-D) wavelet transform. The three algorithms are also applied to the full image so that we can compare their performance on a whole rectangular image. We use eight Landsat Th I multispectral images and another 12 small satellite single-band images as our data set. The results show that these compression algorithms have significantly different performance for different regions. For relatively smooth regions, e.g., regions that consist of a single type of vegetation or water areas etc, the 1-D wavelet method is the best. For highly textured regions, e.g., urban areas, mountain areas, and so on, the modified OWT method wins over the others. For the whole image, OWT working at whole image mode, which is just an ordinary 2-D wavelet compression, is the heat. Based on this, we propose a new data-based compression architecture that extracts particular regions according to the application of interest and then involves different algorithms to encode different regions in order to achieve better performance than traditional onboard compression schemes in which a fixed compression method is applied to the whole image no matter what the application is. This approach is most appropriate for use with images captured by microsatellites, which are commissioned for specific applications in which one knows a priori which cla

关键词： adaptive coding image coding region-based coding remote sensing

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Toward a unified framework for modeling and analysis of diversity in joint source-channel coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 2008年第1期56卷 90-101页

作者： Kwasinski, Andres Liu, K. J. Ray Texas Instruments Inc Germantown MD USA Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA

The study of Joint Source-Channel coding (JSCC) systems faces one major challenge in obtaining an analytical expression for the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve. In this paper, for certain multimedia systems using practical source and channel codes in a JSCC bit rate allocation design, the D-SNR curve is shown to be well approximated by a set of carefully selected points where the relative contribution of channel errors to end-to-end distortion is small. This approach has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation for which it is shown that the D-SNR function is approximately linear in log-log scales. A unified framework for the modeling, analysis and performance measurement of these systems is proposed by considering a view of diversity more general than its usual interpretation. This view extends that of diversity to include redundant information so coding and diversity gain are still used to characterize performance. Furthermore, the proposed approach is applied to study issues arising from using practical source and channel codes, including the effects on performance of channel codes of different strength or source codes with different compression efficiency.

关键词： adaptive coding source coding channel coding

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