Arama Sonuçları

Listeleniyor 1 - 5 / 5
  • Yayın
    Classification-based macroblock layer rate control for low delay transmission of H.263 video
    (IS & T - Soc Imaging Science Technology, 2003-07) Bayazıt, Uluğ
    Puri and Aravind's method of macroblock bit count estimation for video rate control is based on the classification of the macroblock data into discrete classes and assigning a unique non-linear estimate for each class and quantization parameter pair. This method stands apart from other methods in the literature, since the model of the bit count versus the quantization parameter relation, parameterized by macroblock variance, is a discrete model generated solely from measurements, We extend their technique for low-delay video rate control (tight buffer regulation) in two ways. We propose a strategy of near-uniform quantization parameter assignments to the macroblocks of a frame that can come close to maximizing an objective spatial quality function, such as PSNR, over the entire frame. We also adaptively update the quantization parameter assignments for the yet to be coded macroblocks, after the encoding of each macroblock, to compensate for any errors in the bit count estimation of the encoded macroblock. Our experiments demonstrate that the proposed rate control method can more accurately control the number of bits expended for a frame, as well as yield a higher objective spatial quality than the method adopted by TMN8.
  • Yayın
    3-D Mesh geometry compression with set partitioning in the spectral domain
    (IEEE-INST Electrical Electronics Engineers Inc, 2010-02) Bayazıt, Uluğ; Konur, Umut; Ateş, Hasan Fehmi
    This paper explains the development of a highly efficient progressive 3-D mesh geometry coder based on the region adaptive transform in the spectral mesh compression method. A hierarchical set partitioning technique, originally proposed for the efficient compression of wavelet transform coefficients in high-performance wavelet-based image coding methods, is proposed for the efficient compression of the coefficients of this transform. Experiments confirm that the proposed coder employing such a region adaptive transform has a high compression performance rarely achieved by other state of the art 3-D mesh geometry compression algorithms. A new, high-performance fixed spectral basis method is also proposed for reducing the computational complexity of the transform. Many-to-one mappings are employed to relate the coded irregular mesh region to a regular mesh whose basis is used. To prevent loss of compression performance due to the low-pass nature of such mappings, transitions are made from transform-based coding to spatial coding on a per region basis at high coding rates. Experimental results show the performance advantage of the newly proposed fixed spectral basis method over the original fixed spectral basis method in the literature that employs one-to-one mappings.
  • 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 Fikret
    In 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, Uluğ
    This 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
    Postprocessing of decoded color images by adaptive linear filtering
    (Elsevier Science, 2003-02) Bayazıt, Uluğ
    This 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.