This paper presents bandwidth-efficient speech transmission systems using rate-compatible channel coders and variable bitrate embedded source coders. Rate-compatible punctured convolutional codes (RCPC) are often used...
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This paper presents bandwidth-efficient speech transmission systems using rate-compatible channel coders and variable bitrate embedded source coders. Rate-compatible punctured convolutional codes (RCPC) are often used to provide unequal error protection (UEP) via progressive bit puncturing. RCPC codes are well suited for constellations for which Euclidean and Hamming distances are equivalent (BPSK and 4-PSK). This paper introduces rate-compatible punctured trellis codes (RCPT) where rate compatibility and UEP are provided via progressive puncturing of symbols in a trellis. RCPT codes constitute a special class of codes designed to maximize residual Euclidean distances (RED) after symbol puncturing. They can be designed for any constellation, allowing for higher throughput than when restricted to using 4-PSK. We apply RCPC and RCPT to two embedded source coders: a perceptual subband coder and the ITU embedded ADPCM G.727 standard. Different operating modes with distinct source/channel bit allocation and UEP are defined. Each mode is optimal for a certain range of AWGN channel SNRs. Performance results using an 8-PSK constellation clearly illustrate the wide range of channel conditions at which the adaptive scheme using RCPT can operate. For an 8-PSK constellation, RCPT codes are compared to RCPC with bit interleaved coded modulation codes (RCPC-BICM). We also compare performance to RCPC codes used with a 4-PSK constellation.
This paper describes the embedded block coding algorithm at the heart of the JPEG 2000 image compression standard, The paper discusses key considerations which led to the development and adoption of this algorithm, an...
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This paper describes the embedded block coding algorithm at the heart of the JPEG 2000 image compression standard, The paper discusses key considerations which led to the development and adoption of this algorithm, and also investigates performance and complexity issues, The JPEG 2000 coding system achieves excellent compression performance, somewhat higher (and, in some cases, substantially higher) than that of SPIHT with arithmetic coding, a popular benchmark for comparison The algorithm utilizes the same low complexity binary arithmetic coding engine as JBIG2. Together with careful design of the bit-plane coding primitives, this enables comparable execution speed to that observed with the simpler variant of SPIHT without arithmetic coding. The coder offers additional advantages including memory locality, spatial random access and ease of geometric manipulation. (C) 2002 Elsevier Science B.V. All rights reserved.
In this paper, a new coding approach to remote sensing images is proposed according to the statistical characteristic of remote sensing images data. The approach is based on an improved embedded, zeroblock-based, imag...
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In this paper, a new coding approach to remote sensing images is proposed according to the statistical characteristic of remote sensing images data. The approach is based on an improved embedded, zeroblock-based, image wavelet transform coding algorithm. A modified quadtree algorithm and a new ordering's strategy of List of Insignificant Sets (LIS) are proposed in new algorithm. By improving in this proposal, the performance of the embedded wavelet image coder is increased and a higher computing efficiency is obtained. The proposed algorithm exhibits a lower complexity, a more efficient compression ratio and a higher PSNR than SPIHT and SPECK. Experimental results show that the proposed method increases the PSNR by about 0.3 dB over SPIHT, and beats SPIHT by 35% at the CPU time.
The method of modeling and ordering in wavelet domain is very important to design a successful algorithm of embedded image compression. In this paper, the modeling is limited to "pixel classification," the r...
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The method of modeling and ordering in wavelet domain is very important to design a successful algorithm of embedded image compression. In this paper, the modeling is limited to "pixel classification," the relationship between wavelet pixels in significance coding. Similarly, the ordering is limited to "pixel sorting," the coding order of wavelet pixels. We use pixel classification and sorting to provide a better understanding of previous works. The image pixels in wavelet domain are classified and sorted, either explicitly or implicitly, for embedded image compression. A new embedded image code is proposed based on a novel pixel classification and sorting (PCAS) scheme in wavelet domain. In PCAS, pixels to be coded are classified into several quantized contexts based on a large context template and sorted based on their estimated significance probabilities. The purpose of pixel classification is to exploit the intraband correlation in wavelet domain. Pixel sorting employs several fractional bit-plane coding passes to improve the rate-distortion performance. The proposed pixel classification and sorting technique is simple, yet effective, producing an embedded image code with excellent compression performance. In addition, our algorithm is able to provide either spatial or quality scalability with flexible complexity.
An embedded wavelet-based coder for the compression of hyperspectral imagery is described. The proposed coder, three-dimensional (3-D) tarp, employs an explicit estimate of the probability of coefficient significance ...
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An embedded wavelet-based coder for the compression of hyperspectral imagery is described. The proposed coder, three-dimensional (3-D) tarp, employs an explicit estimate of the probability of coefficient significance to drive a nonadaptive arithmetic coder, resulting in a simple implementation suited to vectorized acceleration in single-instruction-multiple-data (SIMD) hardware. The proposed 3-D tarp coder is compared to other prominent coders for the compression of hyperspectral imagery, and state-of-the-art rate-distortion performance is observed.
A simple and efficient context modeling technique (CM-WDR) is proposed to improve the performance of the wavelet difference reduction (WDR) algorithm for image compression. The CM-WDR employs an adaptive scanning orde...
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A simple and efficient context modeling technique (CM-WDR) is proposed to improve the performance of the wavelet difference reduction (WDR) algorithm for image compression. The CM-WDR employs an adaptive scanning order by context modeling. The PSNR improvement over WDR ranges from 0.1 to 1.5 dB at various bitrates.
In this paper, we present a new embedded video coding system with local motion compensation. An invertible motion compensated 3-D subband filter bank is utilized for video analysis/synthesis. The efficient embedded im...
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In this paper, we present a new embedded video coding system with local motion compensation. An invertible motion compensated 3-D subband filter bank is utilized for video analysis/synthesis. The efficient embedded image coding scheme EZBC is extended to 3-D coding of video subbands. The coded bitstream is rate scalable and fully embedded thus meeting the increasing need for fine granular scalability in video streaming applications. Our experimental results show the new algorithm outperforms nonscalable standard MPEG-2 by 0.8-3.3 dB (luminance component) over a broad range of bitrates, while providing an embedded video bitstream. Unlike conventional SNR hybrid coders, this multirate property is achieved without a loss in compression efficiency. Comparisons are also made to two other competing embedded video coders, LZC and SD-SPIHT, both based on 3-D subband coding as well. The new coder demonstrates a significant advantage for encoding video with high local motion content, thanks to the efficient inclusion of local motion information in the temporal filter bank of our proposed system. (C) 2001 Published by Elsevier Science B.V.
Several techniques based on the three-dimensional (3-D) discrete cosine, transform, (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolu...
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Several techniques based on the three-dimensional (3-D) discrete cosine, transform, (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview, of several state-of-the-art 3-D, wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts;layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.
This paper extends the group testing for wavelets (IEEE Trans. Image Process. 11 (2002) 901) algorithm to code coefficients from the wavelet packet transform, the discrete cosine transform, and various lapped transfor...
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This paper extends the group testing for wavelets (IEEE Trans. Image Process. 11 (2002) 901) algorithm to code coefficients from the wavelet packet transform, the discrete cosine transform, and various lapped transforms. Group testing offers a noticeable improvement over zerotree coding techniques on these transforms;is inherently flexible;and can be adapted to different transforms with relative ease. The new algorithms are competitive with many recent state-of-the-art image coders that use the same transforms. (C) 2003 Elsevier Science B.V. All rights reserved.
Progressive image transmission is difficult in the presence of a noisy channel, mainly due to the propagation of errors during the decoding of a progressive bitstream. Excellent results for this problem are made possi...
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Progressive image transmission is difficult in the presence of a noisy channel, mainly due to the propagation of errors during the decoding of a progressive bitstream. Excellent results for this problem are made possible through combined source-channel coding, a method that matches the channel code to the source operational rate distortion as well as channel conditions. This paper focuses on the key component of combined source-channel coding: rate allocation. We develop a parametric methodology for rate allocation, in progressive source-channel coding. The key to this technique is an empirical model of decoded bit-error rate as a function of the channel code rate. We investigate several scenarios. In the case of the memoryless channel, we present closed-form expressions. For the fading channel and channels with feedback, where closed-form results are elusive, our analysis leads to low-complexity algorithms.. The results presented in this paper are applicable to any progressive source code, and any family of channel codes.
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