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A study of vector transform coding of subband-decomposed images

机译:子带分解图像的矢量变换编码研究

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Studies vector transform coding (VTC), a new image coding scheme, on subband-decomposed images. It is shown that vector transformation (VT) reduces the inter-vector correlation, although not as much as the discrete cosine transform (DCT). However, it is also shown that VT preserves the intra-vector correlation much better than the DCT so that vector quantization (VQ) in the VT domain can be made more efficient. VTC of subband-decomposed images introduces another dimension of adaptivity, in which coding parameters, bit allocation, and VQ codebooks can be adapted to each level of the subband pyramid as well as to each vector in the VT domain. The new subband/VTC scheme is compared with VQ of original images, VQ of subband-decomposed images, DCT-based transform coding, and subband/DCT/VQ schemes. Simulation results indicate that the new scheme achieves 1 to 3dB improvement over the other schemes in terms of peak signal-to-noise ratio. This improvement is also supported by subjective evaluations.
机译:在子带分解图像上研究矢量变换编码(VTC)(一种新的图像编码方案)。结果表明,向量变换(VT)减少了向量间相关性,尽管不如离散余弦变换(DCT)那样多。但是,还显示出VT比DCT保留的向量内相关性要好得多,因此可以使VT域中的向量量化(VQ)更有效。子带分解图像的VTC引入了适应性的另一个维度,其中,编码参数,位分配和VQ码本可以适应子带金字塔的每个级别以及VT域中的每个向量。将新的子带/ VTC方案与原始图像的VQ,子带分解图像的VQ,基于DCT的变换编码以及子带/ DCT / VQ方案进行比较。仿真结果表明,新方案在峰值信噪比方面比其他方案提高了1至3dB。主观评估也支持这种改进。

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