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Yayın Predictive vector quantization of 3-D mesh geometry by representation of vertices in local coordinate systems(Elsevier Inc, 2007-08) Bayazıt, Uluğ; Orcay, Özgür; Konur, Umut; Gürgen, Sadık FikretIn predictive 3-D mesh geometry coding, the position of each vertex is predicted from the previously coded neighboring vertices and the resultant prediction error vectors are coded. In this work, the prediction error vectors are represented in a local coordinate system in order to cluster them around a subset of a 2-D planar subspace and thereby increase block coding efficiency. Alphabet entropy constrained vector quantization (AECVQ) of Rao and Pearlman is preferred to the previously employed minimum distortion vector quatitization (MDVQ) for block coding the prediction error vectors with high coding efficiency and low implementation complexity. Estimation and compensation of the bias in the parallelogram prediction rule and partial adaptation of the AECVQ codebook to the encoded vector source by normalization using source statistics, are the other salient features of the proposed coding system. Experimental results verify the advantage of the use of the local coordinate system over the global one. The visual error of the proposed coding system is lower than the predictive coding method of Touma and Gotsman especially at low rates, and lower than the spectral coding method of Karni and Gotsman at medium-to-high rates.Yayın Significance map pruning and other enhancements to SPIHT image coding algorithm(Elsevier Science, 2003-10) Bayazıt, UluğThis paper proposes several enhancements to the Set Partitioning in Hierarchical Trees (SPIHT) image coding algorithm without changing the original algorithm's general skeleton. First and foremost, a method for significance map pruning based on a rate-distortion criterion is introduced. Specifically, the (Type A) sets of wavelet coefficients with small ratios of estimated distortion reduction to estimated rate contribution are deemed insignificant and effectively pruned. Even though determining such sets requires the computational complexity of the encoder to increase considerably with respect to the original SPIHT encoder, the original SPIHT decoder may still be used to decode the generated bitstream with a low computational complexity. The paper also proposes three low complexity enhancements by more sophisticated use of the adaptive arithmetic coder. Simulation results demonstrate that all these enhancements yield modest compression gains at moderate to high rates.Yayın Hierarchical quantization indexing for wavelet and wavelet packet image coding(Elsevier Science BV, 2010-02) Ateş, Hasan Fehmi; Tamer, EnginIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger Subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.Yayın Postprocessing of decoded color images by adaptive linear filtering(Elsevier Science, 2003-02) Bayazıt, UluğThis paper presents an image adaptive linear filtering method for the reconstruction of the RGB (red, blue, green) color coordinates of a pixel from the lossy compressed luminance/chrominance color coordinates. In the absence of quantization noise, the RGB coordinates of a pixel can be perfectly reconstructed by employing a standard, fixed filter whose support includes only the luminance/chrominance coordinates at the spatial location of the pixel. However, in the presence of quantization noise, a filter with a larger support, that also spatially extends over the luminance/chrominance coordinate planes, is capable of exploiting the statistical dependence among the luminance/chrominance coordinate planes, and thereby yields more accurate reconstruction than the standard, fixed filter. We propose the optimal (in the minimum mean squared error sense) determination of the coefficients of this adaptive linear filter at the image encoder by solving a system of regression equations. When transmitted as side information to the image decoder, the filter coefficients need not incur significant overhead if they are quantized and compressed intelligently. Our simulation results demonstrate that the distortion of the decompressed color coordinate planes can be reduced by several tenths of a dB with negligible overhead rate by the application of our image adaptive linear filtering method.
