Universal perceptual weighted zerotree coding for image and videocompression

A universal representation for the perceptual weighted zerotree coding algorithm is developed, in which the perceptual weighted zerotree coding is decomposed into two separate parts, i.e. visual weighting and zerotree representation, which can be realised independently. Prior to zerotree processing, the extracted full-tree is weighted by using a visual weighting matrix. Any zerotree algorithm like EZW, SPIHT and zerotree space-frequency quantisation can be used to encode the weighted coefficients of the wavelet transform. In other words, any previous algorithm without perceptual weighting can be easily extended to form a new perceptual coder using the proposed framework. Several examples of visual weighting matrices are given to show the effect of the new method     

Joint source/channel coding for variable length codes

When using entropy coding over a noisy channel, it is customary to protect the highly vulnerable bitstream with an error correcting code. In this paper, we propose a technique which utilizes the residual redundancy at the output of the source coder to provide error protection for entropy coded systems     

Near-capacity irregular variable length coding and irregular unity rate coding

In this contribution we introduce an EXtrinsic Information Transfer (EXIT) chart matching technique for the design of two serially concatenated irregular codecs, each constituted by a variety of component codes. This approach facilitates a higher degree of design freedom than matching the EXIT function of an irregular codec to that of a regular codec, comprising only a single component code. As a result, a narrower EXIT chart tunnel can be created, facilitating operation at E_b/N₀ values that are closer to the channel?s capacity bound. This is demonstrated for a serial concatenation of iteratively decoded Irregular Variable Length Coding (IrVLC) and Irregular Unity Rate Coding (IrURC), which is favourably compared with an IrVLC and regular Unity Rate Coding (URC) based benchmarker. Finally, we show that the iterative decoding complexity of our IrVLCIrURC scheme can be reduced by about 25% upon employing a method of jointly performing EXIT chart matching, while seeking a reduced iterative decoding complexity.     

An integrated framework for adaptive subband image coding

Previous work on filter banks and related expansions has revealed an interesting insight: different filter bank trees can be regarded as different ways of constructing orthonormal bases for linear signal expansion. In particular, fast algorithms for finding best bases in an operational rate-distortion (R/D) sense have been successfully used in image coding. Independently of this work, other research has also explored the design of filter banks that optimize energy compaction for a single signal or a class of signals. In this paper, we integrate these two different but complementary approaches to best-basis design and propose a coding paradigm in which subband filters, tree structure, and quantizers are chosen to optimize the R/D performance. These coder attributes represent side information. They are selected from a codebook designed off-line from training data, using R/D as the design criterion. This approach provides a rational framework in which to explore alternatives to empirical design of filter banks, quantizers, and other coding parameters. The on-line coding algorithm is a relatively simple extension of current R/D-optimal coding algorithms that operate with fixed filter banks and empirically designed quantizer codebooks. In particular, it is shown that selection of the best adapted filter bank from the codebook is computationally elementary     

Fast variable run-length coding for embedded progressivewavelet-based image compression

Run-length coding has attracted much attention in wavelet-based image compression because of its simplicity and potentially low complexity. The main drawback is the inferior RD-performance compared to the state-of-the-art-coder SPIHT. In this paper, we concentrate on the embedded progressive run-length code of Tian and Wells (1996, 1998). We consider significance sequences drawn from the scan in the dominant pass. It turns out that self-similar curves for scanning the dominant pass increase the compression efficiency significantly. This is a consequence of the correlation of direct neighbors in the wavelet domain. This dependence can be better exploited by using groups of coefficients, similar to the SPIHT algorithm. This results in a new and very fast coding algorithm, which shows performance similar to the state-of-the-art coder SPIHT, but with lower complexity and small and fixed memory overhead.     

Generalized unequal length lapped orthogonal transform for subband image coding

Generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOTs) are considered. The length of each basis of the proposed GULLOT can be different from each other, whereas all the bases of the conventional GenLOT are of equal length. In general, for image coding application, the long basis for a low-frequency band and the short basis for a high-frequency one are desirable to reduce the blocking and the ringing artifact simultaneously. Therefore, the GULLOT is suitable especially for a subband image coding. In order to apply the GULLOT to a subband image coding, we also investigate the size-limited structure to process the finite length signal, which is important in practice. Finally, some design and image coding examples are shown to confirm the validity of the proposed GULLOT.     

一种可变长码在视频编码中的应用

本文所讨论的一种可逆的可变长码，其码长分布与Golomb-Rice和exp-Golomb编码相同。其编码数据格式能够很好地应用于图像和视频的统计编码中，在保持编码效率的同时，很大程度地提高编码在信道传输中的纠错能力。     

Buffer overflow in variable length coding of fixed rate sources

In this paper, we develop and analyze an easily instrumentable scheme for variable length encoding of discrete memoryless fixed-rate sources in which buffer overflows result in codeword erasures at locations that are perfectly specified to the user. Thus, no loss of synchronism ever occurs. We find optimal (i.e., minimizing the probability of buffer overflow) code-wold length requirements under the Kraft inequality constraint, relative to various constant transmission ratesR, and show that these do not result in the minimal average code-word length. The corresponding bounds on the probability of buffer overflow provide a linkup between source coding and Rényi's generalized source entropy. We show, further, that codes having optimal word lengths can be constructed by the method of Elias, and we develop corresponding sequentially instrumented encoders and decoders. We show that the complexity of these encoders and decoders grows only linearly with the encoded message block lengthk, provided the sizedof the coder alphabet is a power of2, and otherwise grows no worse than quadratically withk.     

Smooth side-match weighted vector quantiser with variable block size for image coding

Although side-match vector quantisation (SMVQ) reduces the bit rate, the quality of image coding using SMVQ generally degenerates as the grey level transition across the boundaries of neighbouring blocks increases or decreases. The author proposes a smooth side-match weighted method to yield a state codebook according to the smoothness of the grey levels between neighbouring blocks. When a block is encoded, a corresponding weight is assigned to each neighbouring block to represent its relative importance. This smooth side-match weighted vector quantisation (SSMWVQ) achieves a higher PSNR than SMVQ at the same bit rate. Also, each block can be pre-encoded in an image, allowing each encoded block to use all neighbouring blocks to yield the state codebook in SSMWVQ, rather than using only two neighbouring blocks, as in SMVQ. Moreover, SSMWVQ selects many high-detail blocks as basic blocks to enhance the coding quality, and merges many low-detail blocks into a larger one to reduce further the bit rate. Experimental results reveal that SSMWVQ has a higher PSNR and lower bit rate than other methods.     

Information loss recovery for block-based image coding techniques-afuzzy logic approach

A new technique to recover the information loss in a block-based image coding system is developed in this paper. The proposed scheme is based on fuzzy logic reasoning and can be divided into three main steps: (1) hierarchical compass interpolation/extrapolation (HCIE) in the spatial domain for initial recovery of lost blocks that mainly contain low-frequency information such as smooth background (2) coarse spectra interpretation by fuzzy logic reasoning for recovery of lost blocks that contain high-frequency information such as complex textures and fine features (3) sliding window iteration (SWI), which is performed in both spatial and spectral domains to efficiently integrate the results obtained in steps (1) and (2) such that the optimal result can be achieved in terms of surface continuity on block boundaries and a set of fuzzy inference rules. The proposed method, which is suitable for recovering both isolated and contiguous block losses, provides a new approach for error concealment of block-based image coding systems such as the JPEG coding standard and vector quantization-based coding algorithms. The principle of the proposed scheme can also be applied to block-based video compression schemes such as the H.261, MPEG, and HDTV standards. Simulation results are presented to illustrate the effectiveness of the proposed method.     

A new approach to reduce the `blocking effect' of transform coding[image coding]

A combined-transform coding (CTC) scheme to reduce the blocking effect of conventional block transform coding and hence to improve the subjective performance is presented. The scheme is described, and its information-theoretic properties are discussed. Computer simulation results for a chest X-ray image are presented. The CTC scheme, the JPEG baseline scheme, and the conventional discrete Walsh-Hadamard transform (DWHT) are compared to demonstrate the performance improvement for the CTC scheme. The advantages of the CTC scheme include no ringing effect as there is no error propagation across the boundary, no additional computation, and distortion always held within a certain level     

Set theoretic compression with an application to image coding

We show that the complete information that is available after an image has been encoded is not just an approximate quantized image version, but a whole set of consistent images that contains the original image by necessity. From this starting point, we develop a set of tools to design a new class of encoders for image compression, based on a set decomposition and recombination of the image features. As an initial validation, we show the results of an experiment where these tools are used to modify the encoding process of block discrete cosine transform (DCT) coding in order to yield less blocking artifacts.     

Variable length coding over an unknown channel

Burnashev in 1976 gave an exact expression for the reliability function of a discrete memoryless channel (DMC) with noiseless feedback. A coding scheme that achieves this exponent needs, in general, to know the statistics of the channel. Suppose now that the coding scheme is designed knowing only that the channel belongs to a family Q of DMCs. Is there a coding scheme with noiseless feedback that achieves Burnashev's exponent uniformly over Q at a nontrivial rate? We answer the question in the affirmative for two families of channels (binary symmetric, and Z). For these families we show that, for any given fraction, there is a feedback coding strategy such that for any member of the family: i) guarantees this fraction of its capacity as rate, and ii) guarantees the corresponding Burnashev's exponent. Therefore, for these families, in terms of delay and error probability, the knowledge of the channel becomes asymptotically irrelevant in feedback code design: there are blind schemes that perform as well as the best coding scheme designed with the foreknowledge of the channel under use. However, a converse result shows that, in general, even for families that consist of only two channels, such blind schemes do not exist.     

Universal coding for multiple access channels

The problems of universal coding and decoding for multiple-access channels are examined. The hypothetical mutual information functions are used to prove that rate vectorsR=(R_{1},R_{2})in a subregionhat{cal C}of the capacity regioncal Care universally achievable in the sense that there exist codes of rateRthat are asymptotically optimum for all multiple-access channels with finite fixed input alphabetsX_{1},X_{2}, and output alphabetY.     

Wavelet image compression - the quadtree coding approach

Perfect reconstruction, quality scalability and region-of-interest coding are basic features needed for the image compression schemes used in telemedicine applications. This paper proposes a new wavelet-based embedded compression technique that efficiently exploits the intraband dependencies and uses a quadtree-based approach to encode the significance maps. The algorithm produces a losslessly compressed embedded data stream, supports quality scalability and permits region-of-interest coding. Moreover, experimental results obtained on various images show that the proposed algorithm provides competitive lossless/lossy compression results. The proposed technique is well-suited for telemedicine applications that require fast interactive handling of large image sets over networks with limited and/or variable bandwidth     

引入非线性变换的分形图像压缩编码

提出了一种基于非线性变换的分形图像压缩编码方法。证明了引入的非线性变换满足压缩迭代映射理论。模拟实验的结果表明 ,与传统的分形图像压缩编码方法相比 ,压缩比和峰值信噪比均有所改善。     

Wavelet image coding using variable blocksize vector quantization with optimal quadtree segmentation

In this paper, we propose an image coding scheme by using the variable blocksize vector quantization (VBVQ) to compress wavelet coefficients of an image. The scheme is capable of finding an optimal quadtree segmentation of wavelet coefficients of an image for VBVQ subject to a given bit budget, such that the total distortion of quantized wavelet coefficients is minimal. From our simulation results, we can see that our proposed coding scheme has higher performance in PSNR than other wavelet/VQ or subband/VQ coding schemes.     

Optimal progressive lossless image coding using reduced pyramids with variable decimation ratios

This article introduces a novel method for the construction of extended reduced pyramids with rational decimation ratios from stage to stage. It is shown that this construction produces more accurate interpolation, and thus more efficient lossless compression, than conventional reduced pyramids.