The authors thoroughly investigate the performance of multistage scalar quantization and investigate three encoding strategies: concatenated coding, conditional entropy coding, and conditional uniform quantization. It...
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The authors thoroughly investigate the performance of multistage scalar quantization and investigate three encoding strategies: concatenated coding, conditional entropy coding, and conditional uniform quantization. It is shown that the coding performance of a multistage quantized subband is inferior to that of direct (i.e., single stage) quantization. Conditional entropy coding and conditional uniform quantization partly eliminate this loss.< >
Efforts to build high-speed hardware for many different entropy coders are limited by fundamental feedback loops. A method that allows for parallel compression in hardware is described. This parallelism results in ext...
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Efforts to build high-speed hardware for many different entropy coders are limited by fundamental feedback loops. A method that allows for parallel compression in hardware is described. This parallelism results in extremely high rates, 100 million symbols/second or higher. The system is generalizable to any lossless or lossy system with deterministic decompression. Prototype hardware that divides the data into multiple streams that feed parallel coders is presented. The problem of efficient transmission of multiple streams of variable-length coded data is solved by a unique coded data interleave method.< >
Many modern analog media coders employ some form of entropy coding (EC). Usually, a simple per-letter EC is used to keep the coder's complexity and price low. In some coders, individual symbols are grouped into sm...
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Many modern analog media coders employ some form of entropy coding (EC). Usually, a simple per-letter EC is used to keep the coder's complexity and price low. In some coders, individual symbols are grouped into small fixed-size vectors before EC is applied. We extend this approach to form variable-size vector EC (VSVEC) in which vector sizes may be from 1 to several hundreds. The method is, however, complexity-constrained in the sense that the vector size is always as large as allowed by a pre-set complexity limit. The idea is studied in the framework of a modified discrete cosine transform (MDCT) coder. It is shown experimentally, using diverse audio material, that a rate reduction of about 37% can be achieved. The method is, however, not specific to MDCT coding but can be incorporated in various speech, audio, image and video coders.
In this paper we study the problem of context modeling and entropy coding of the symbol streams generated by the well-known EZW image coder (embedded image coding using zerotrees of wavelet coefficients). We present s...
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ISBN:
(纸本)0818679190
In this paper we study the problem of context modeling and entropy coding of the symbol streams generated by the well-known EZW image coder (embedded image coding using zerotrees of wavelet coefficients). We present some simple context modeling techniques that can squeeze out more statistical redundancy in the wavelet coefficients of EZW-type image coders and hence lead to improved coding efficiency.
We present a pattern recognizer to classify a variety of objects and their pose on a table from real world images. Learning of weights in a linear discriminant is based on estimating the relative information contribut...
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We present a pattern recognizer to classify a variety of objects and their pose on a table from real world images. Learning of weights in a linear discriminant is based on estimating the relative information contributed by a set of features to the final decision. Evaluation of the discriminant is very fast, allowing for about three decisions per second on datasets without segmentation difficulties like the COIL-100 database. Experiments on that database yield high recognition rates and good generalisation over pose.
In hybrid video coding, an entropy coding scheme transmits the quantized transform coefficients, resulting from block-based transformation and quantization of the difference between the prediction signal and the origi...
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In hybrid video coding, an entropy coding scheme transmits the quantized transform coefficients, resulting from block-based transformation and quantization of the difference between the prediction signal and the original signal, and additional side information. The state-of-the-art hybrid video coding standard H.264/AVC defines two different entropy coding schemes with different complexity-performance tradeoff. As a result, the support for two different entropy coding schemes has to be maintained and introduces several problems. To overcome these issues, a unified solution is proposed, which is based on the PIPE/V2V coding concept. It achieves the same complexity-performance trade-offs as the existing entropy coding schemes by scalability. The advantage of the proposed scheme over the existing concept is the usage of the same set of tools for all configurations. Simulation results and complexity analysis on hardware show the efficiency of the proposed scheme.
This paper proposes a variable block-size transform and context-based entropy coding techniques for the enhancement layer of FGS (fine granularity scalable) video coding. First, the variable block-size transform is in...
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ISBN:
(纸本)0780385543
This paper proposes a variable block-size transform and context-based entropy coding techniques for the enhancement layer of FGS (fine granularity scalable) video coding. First, the variable block-size transform is introduced into the enhancement layer to improve the performance of FGS in terms of both visual quality and PSNR. Different from that used in the traditional single layer coding, an R-D selection algorithm is proposed to optimally decide the transform size of each block, under consideration of consistent performance at a range of bit rates. Furthermore, to fully take advantage of the characteristics and correlations of symbols coded in the FGS enhancement layer, different context models are designed for the arithmetic coding according to symbol type and transform size. Experimental results show that the coding efficiency of FGS can be increased by 0.2-0.90 dB with the proposed techniques.
Summary form only given. In this paper, we take a different approach from the coding community. Instead of taking the usual route of quantization plus Slepian-Wolf coding, we do not perform any Slepian-Wolf coding on ...
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ISBN:
(纸本)9781467360371
Summary form only given. In this paper, we take a different approach from the coding community. Instead of taking the usual route of quantization plus Slepian-Wolf coding, we do not perform any Slepian-Wolf coding on the transmitter side. We simply perform quantization on the sensor readings, compress the quantization indexes with conventional entropy coding, and send the compressed indexes to the receiver. On the decoder side, we simply perform entropy decoding and Gaussian process regression to reconstruct the joint source. To reduce the sum rate over all sensors, some sensors are censored and do not transmit anything to the decoder.
作者：
R.A. CohenJ.W. WoodsElectrical
Computer and Systems Engineering Department Rensselaer Polytechnic Institute Troy NY USA
The authors compare various options for combining linear prediction with vector quantization for purposes of image coding. A previously developed algorithm called sliding block predictive vector quantization (SBPVQ) i...
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The authors compare various options for combining linear prediction with vector quantization for purposes of image coding. A previously developed algorithm called sliding block predictive vector quantization (SBPVQ) is extended with multiple-level quantizers (i.e. n>2), and is compared to vector-predictive quantization (VPQ). The particular version considered here is termed sliding block vector predictive quantization (SBVPQ) and uses a (M,L) tree search on the encoded blocks. Arithmetic coding is used to transmit the SBPVQ and SBVPQ encoded data at rates closer to their output entropy than rates obtained with fixed-rate coding.< >
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