This paper describes a new approach to fixed-rate entropy-constrained vector quantization (FEVQ) for stationary memoryless sources where the structure of codewords are derived from a variable-length scalar quantizer. ...
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This paper describes a new approach to fixed-rate entropy-constrained vector quantization (FEVQ) for stationary memoryless sources where the structure of codewords are derived from a variable-length scalar quantizer. We formulate the quantization search operation as a zero-one integer-optimization problem, and show that the resulting integer program can be closely approximated by solving a simple linear program. The result is a Lagrange formulation which adjoins the constraint on the entropy (codeword length) to the distortion. Unlike the previously known methods with a fixed Lagrange multiplier, we use an iterative algorithm to optimize the underlying objective function, while updating the Lagrange multiplier until the constraint on the overall rate is satisfied. The key feature of the new method is the substantial reduction in the number of iterations in comparison with previous related methods. In order to achieve some packing gain, we combine the process of trellis-coded quantization with that of FEVQ. This results in an iterative application of the Viterbi algorithm on the underlying trellis for selecting the Lagrange multiplier. Numerical results are presented which demonstrate substantial improvement in comparison with the alternative methods reported in the literature.
Optimal context quantizers for minimum conditional entropy can be constructed by dynamic programming in the probability simplex space. The main difficulty, operationally, is the resulting complex quantizer mapping fun...
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Optimal context quantizers for minimum conditional entropy can be constructed by dynamic programming in the probability simplex space. The main difficulty, operationally, is the resulting complex quantizer mapping function in the context space, in which the conditional entropy coding is conducted. To overcome this difficulty, we propose new algorithms for designing context quantizers in the context space based on the multiclass Fisher discriminant and the kernel Fisher discriminant (KFD). In particular, the KFD can describe linearly nonseparable quantizer cells by projecting input context vectors onto a high-dimensional curve, in which these cells become better separable. The new algorithms outperform the previous linear Fisher discriminant method for context quantization. They approach the minimum empirical conditional entropy context quantizer designed in the probability simplex space, but with a practical implementation that employs a simple scalar quantizer mapping function rather than a large lookup table.
Lossless compression of color mosaic images poses a unique and interesting problem of spectral decorrelation of spatially interleaved R, G, B samples. We investigate reversible lossless spectral-spatial transforms tha...
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Lossless compression of color mosaic images poses a unique and interesting problem of spectral decorrelation of spatially interleaved R, G, B samples. We investigate reversible lossless spectral-spatial transforms that can remove statistical redundancies in both spectral and spatial domains and discover that a particular wavelet decomposition scheme, called Mallat wavelet packet transform, is ideally suited to the task of decorrelating color mosaic data. We also propose a low-complexity adaptive context-based Golomb-Rice coding technique to compress the coefficients of Mallat wavelet packet transform. The lossless compression performance of the proposed method on color mosaic images is apparently the best so far among the existing lossless image codecs.
The H.264 video coding standard was created to support the next generation of multimedia applications. H.264 improves performance over previous video coding standards, such as MPEG-2, H.263, and MPEG-4 part 2, by app...
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The H.264 video coding standard was created to support the next generation of multimedia applications. H.264 improves performance over previous video coding standards, such as MPEG-2, H.263, and MPEG-4 part 2, by applying more sophisticated techniques for intraframe and interframe prediction, transform coding, entropy coding, and so on. The H.264 standard is unique in its broad applicability across a range of bit rates and video resolutions and is gaining momentum in its adoption by industry. Hari Kalva?s article reviews H.264, highlights its unique features, and describes its applicability to emerging applications such as IPTV.
We propose a coding algorithm called unary prefixed Huffman (UPH) coding for a family of infinite sources called quantized generalized Gaussian (GG) sources. Compared with the existing codes for these GG sources, the ...
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We propose a coding algorithm called unary prefixed Huffman (UPH) coding for a family of infinite sources called quantized generalized Gaussian (GG) sources. Compared with the existing codes for these GG sources, the UPH algorithm provides a more adaptive approach, and its coding efficiency is upper bounded by entropy +2.
An algorithm of combining LZC and arithmetic coding algorithm for image compression is presented and both theory deduction and simulation result prove the correctness and feasibility of the algorithm. According to the...
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ISBN:
(纸本)0819463914
An algorithm of combining LZC and arithmetic coding algorithm for image compression is presented and both theory deduction and simulation result prove the correctness and feasibility of the algorithm. According to the characteristic of context-based adaptive binary arithmetic coding and entropy, LZC was modified to cooperate the optimized piecewise arithmetic coding, this algorithm improved the compression ratio without any additional time consumption compared to traditional method.
In this paper, we propose a novel high-throughput, ASIC architecture to realize the context-adaptive variable-length decoder (CAVLC) of H.264/AVC baseline profile. We conduct a thorough analysis of inherent parallelis...
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ISBN:
(纸本)9781424403868
In this paper, we propose a novel high-throughput, ASIC architecture to realize the context-adaptive variable-length decoder (CAVLC) of H.264/AVC baseline profile. We conduct a thorough analysis of inherent parallelism of the CAVLC algorithm and identify particular steps that will benefit from parallel computing. In particular, we adopt a bit-position VLC decoding approach to decode multiple symbols concurrently in a critical step in CAVLC. This modification leads to almost 40% reduction of clock cycles compared to a straight-forward implementation.
"Virtual Sliding Window" algorithm presented in this paper is an adaptive mechanism for estimating the probability of ones at the output of binary non-stationary sources. It is based on "Imaginary slidi...
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ISBN:
(纸本)1424402158
"Virtual Sliding Window" algorithm presented in this paper is an adaptive mechanism for estimating the probability of ones at the output of binary non-stationary sources. It is based on "Imaginary sliding window" idea proposed by ***. The proposed algorithm was used as an alternative adaptation mechanism in Context-Based Adaptive Binary Arithmetic coding (CABAC) - an entropy coding scheme of H.264/AVC standard for video compression. The "virtual sliding window" algorithm was integrated into an open-source codec supporting H.264/AVC standard. Comparison of the "virtual sliding window" algorithm with the original adaptation mechanism from CABAC is presented. Test results for standard video sequences are included. These results indicate that using the proposed algorithm improves rate-distortion performance compared to the original CABAC adaptation mechanism. Besides improvement in rate-distortion performances the "Virtual Sliding Window" algorithm has one more advantage. CABAC uses a finite state machine (FSM) for estimation of the probability of ones at the output of a binary source. Transitions for FSM are defined by a table stored in memory. The disadvantage of CABAC consists infrequent reference to this table (one time for every binary symbol encoding), which is critical for DSP implementation. The "Virtual Sliding Window" algorithm allows to avoid using the table of transitions.
In this paper, a novel VLC method based on 2nd-run-level coding and dynamic truncation is proposed to compress the DCT coefficients efficiently. In the proposed VLC, 2nd-run-level is first employed, following the trad...
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ISBN:
(纸本)0819461172
In this paper, a novel VLC method based on 2nd-run-level coding and dynamic truncation is proposed to compress the DCT coefficients efficiently. In the proposed VLC, 2nd-run-level is first employed, following the traditional run-level coding, to further reduce the considerable redundancy existing in the original level and run sequences. In order to achieve a higher degree of context adaptability and coding efficiency, dynamic truncation is introduced and employed in the sequential coding of 2D symbols without large amounts of 2D-VLC tables required, though adding extra coding complexity to some extent. Adaptive EG/GR selection is also presented and recommended since it brings extra improvement in compression efficiency without increasing any computational complexity. Experimental results show that when compared with context-based 2D-VLC, the proposed VLC method gains 0.25 dB similar to 0.79 dB in PSNR and achieves 5.30% similar to 11.58% improvement in bit rate reduction.
This paper presents a compression scheme for color images, by using Self-Organizing Feature Map (SOFM) algorithm, which is a neural network structure. In this application 1-dimensional SOFM is used to map 256-color to...
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ISBN:
(纸本)0889865566
This paper presents a compression scheme for color images, by using Self-Organizing Feature Map (SOFM) algorithm, which is a neural network structure. In this application 1-dimensional SOFM is used to map 256-color to 64-, 32- and 16-color. After the quantization process, relative coding and entropy coding are performed without any loss in the information. Obtained results encourage the use of SOFM for image compression.
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