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Abstract - IMDSP8

IMDSP8.1	Vector Set Partitioning with Classified Successive Refinement VQ for Embedded Wavelet Image and Video Coding D. Mukherjee, S. Mitra (University of California, Santa Barbara, USA) The Set Partitioning in Hierarchical Trees (SPIHT) approach for still image compression proposed by Said and Pearlman, is one of the most efficient embedded gray image compression schemes till date. The algorithm relies on a very efficient scanning cum bit-allocation scheme for quantizing the coefficients obtained by a wavelet decomposition of an image. In this paper, we adopt this scheme to scan vectors of wavelet coefficients, and use successive refinement VQ techniques with staggered bit-allocation to quantize several wavelet coefficients at once. The new scheme is named VSPIHT (Vector SPIHT). We present some coding results comparing VSPIHT to the scalar counterpart in the mean-squared-error sense. The method readily generalizes to color images and video where the vector-based approach makes more sense. We present the coding results on INTRA frames of QCIF sequences as compared against H.263.
IMDSP8.2	Transcoder Architectures for Video Coding N. Björk, C. Christopoulos (Ericsson Telecom AB, Sweden) Two different models for transcoding of H.263-based video streams are examined: rate reduction and resolution reduction. Results show that the computational complexity of the basic transcoding model can be reduced for each model by an average of 39% and 23% with less than 1 dB loss in quality for sequences with high motion. Comparisons with scalable video coding model are also presented.
IMDSP8.3	Efficient Coding of DCT Coefficients by Joint Position-Dependent Encoding E. Reed, J. Lim (MIT, USA) In a typical MC-DCT encoding scheme, a large portion of the bit rate is used to encode the location and amplitude information of the nonzero quantized DCT coefficients. Therefore efficient encoding of the DCT coefficients is extremely important. In this paper we describe the Joint Position-Dependent Encoding (PDE) approach to encode the DCT coefficients. Joint PDE exploits the variations in statistical properties of the runlengths and amplitudes as a function of position by introducing a set of 2-D codebooks in which each DCT coefficient is assigned to one codebook in the set based on its location. Utilizing an MPEG-2 codec, we compare the bit rates using the joint PDE variable length codes (VLC's) with the bit rates produced by the MPEG-2 VLC's. We also examine how performance is affected by the number of codebooks.
IMDSP8.4	Efficient SNR-Scalability in Predictive Video Coding K. Rose, P. Wu, S. Regunathan (University of California, Santa Barbara, USA) A new method is proposed for efficient SNR scalability in predictive video coding. It is of low complexity, and it is applicable to standard DCT-based video compression with motion compensation. Information that is only available to the enhancement layers is exploited to improve the quality of their frame prediction without compromising the usefulness of the compressed data provided by the base layer(s). More specifically, the next frame prediction for use by an enhancement-layer decoder is obtained by combining, or switching between transform coefficients from: i) the reconstructed base-layer frame; and ii) the predicted enhancement-layer frame. The combining rule depends on the compressed residual of the base layer, and on the parameters used for this compression. The method is applied to standard DCT-based predictive video coding, and preliminary simulation shows consistent, substantial improvement in the performance of enhancement layers. The proposed method may be easily combined with known temporal scalability methods to provide further improvement of the performance of enhancement layers over a wide range of bit rates.
IMDSP8.5	MPEG-2 Video Coding with Image Partitioning E. Barzykina, P. Nasiopoulos, R. Ward (University of British Columbia, Canada) We present an original motion compensation strategy based on frame partitioning. The proposed method uses different temporal resolutions within a single frame to improve compression. We present a new bit allocation and rate control algorithm complementing our motion compensation technique. Our approach to bit allocation ensures the consistency of quality throughout a frame and a GOP. For the same picture quality, frame partitioning alone yields an additional increase of up to 20 percent or more in the encoding efficiency, while our bit allocation algorithm eliminates fluctuation in visual quality.
IMDSP8.6	Significance-Linked Wavelet Video Coder J. Vass (University of Missouri-Columbia, USA); B. Chai (Sarnoff Corporation, USA); X. Zhuang (University of Missouri-Columbia, USA) Perhaps, Sarnoff Corporation's zerotree entropy (ZTE) coder is the most successful wavelet video coder published so far which exploits the statistical properties of wavelet-transformed images by utilizing novel data representation and organization strategies. In this paper, a high performance hybrid video coding algorithm termed video significance-linked connected component analysis (VSLCCA) is developed. It is quite encouraging that, at least empirically convinced, the wavelet transform with aids of those recently published innovative data representation and organization methods can be an invaluable asset in video coding if motion-compensated error frames are coherent. In VSLCCA, time domain motion estimation followed by exhaustive overlapped block motion compensation is utilized to ensure coherency, and then wavelet transform is applied to each error frame with significant wavelet coefficients being encoded by highly efficient SLCCA technique. Experimental results on standard MPEG-4 test sequences show that VSLCCA is superior to H.263 and ZTE by 0.48 dB and 0.77 dB on average, respectively.
IMDSP8.7	Novel Error Concealment Techniques for Images in ATM Environments M. Hasan, A. Sharaf, F. Marvasti (King's College London, UK) Images transmitted via ATM networks suffer from quality degradation due to buffer overflow or cell header errors which cause ATM cells to be lost. This paper presents a new approach to conceal the errors in the received images by the application of novel error recovery techniques to the decomposed DCT-coefficient subimages of the corrupted image. These techniques were developed to recover images corrupted by impulsive noise. Since decomposing the corrupted image into the DCT-coefficient subimages generates low resolution images corrupted by impulsive noise, all the techniques used to recover images corrupted by impulsive noise can be used to recover the subimages and hence the corrupted image. In this paper, we study the performance of new techniques to recover the corrupted subimages. The quality of the recovered image using these techniques is better than the quality obtained by many classical error concealment techniques.
IMDSP8.8	Detail Selection Incorporating Subjective Factors for Very Low Bit-Rate Image Coding Y. Zeng (Imperial College, UK) This paper is concerned with the subjective selection of image details for very low bit-rate coding scheme. An approach is proposed for extracting and ranking the details in the order of perceptual significance to the Human Visual System (HVS). A new perceptual ranking model has been established based on multivariate regression analysis. This ranking model provides better results in detail selection than that by an empirical ranking formula proposed in a previous study in terms of the correlation between the objective ranking and subjective ranking of perceptual significance. Segmented strong contours and selected details are combined and coded to illustrate the efficiency of coding meaningful details. Compared with the pure segmented images, the addition of the selected details shows better subjective image quality at lower bit rates.
IMDSP8.9	An Adaptive Quantization Algorithm for MPEG-2 Video Coding L. Luo, C. Zou, Z. He (Southeast University, P R China); I. Shirakawa (Osaka University, Japan) An adaptive quantization algorithm for MPEG-2 video coding using neural network is presented in this paper. The proposed algorithm uses a BP neural network to divide the macroblock activity into one of four categories: flat, edge, texture, fine-texture, and thus the macroblock can be quantized adaptively according to the human vision system (HVS) sensitivity. Experiment results show that this method can reduce blocky artifacts of flat area and distortion at edge effectively. Meanwhile, the picture subjective quality and objective quality of each frame are improved.
IMDSP8.10	A Novel Similarity Measure for Compression and Classification Y. Ozturk, H. Abut (San Diego State University, USA) In this study we propose a new architecture for texture classification based on pair-wise pixel associations as an extension of the recently developed Multivalued Recursive Network (MAREN) architecture. Maybe more critically we propose a novel similarity measure and classification algorithm to be used with this network. The proposed fidelity criterion has been observed to be tightly coupled with the ubiquitous mean-square error (MSE) distance measure. Both SOAR and MAREN structures can be considered as extensions of the associative memory concept frequently used in neural networks. Our proposed similarity measure is based on the principle of directional divergence of interpixel relationships in a given texture and promises a number of advantages over the MSE measure. In this paper, SOAR will be discussed within the framework of a texture classification problem, but we believe it would be very easy to extend to other applications where interpixel relationship is the primary focus.

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