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Modified set partitioning in hierarchical trees algorithm based on hierarchical subbands

机译:基于层次子带的层次树算法中的改进集划分

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This paper introduces a modified set partitioning in hierarchical trees (SPIHT) algorithm that reduces the number of comparison operations and, consequently, the execution time needed to encode an image as compared to the SPIHT algorithm. The threshold of each independent subband is calculated after applying the discrete wavelet transform to the image. Scanning of the sets inside the subbands is determined by the magnitude of the thresholds that establishes a hierarchical scanning not only for the set of coefficients with larger magnitude, but also for the subbands. The algorithm uses the set partitioning technique to sort the transform coefficients. Results show that the modified SPIHT significantly reduces the number of operations and the execution time without sacrificing visual quality and the PSNR of the recovered image. (C) The Authors.
机译:本文介绍了一种改进的分层树集划分(SPIHT)算法,与SPIHT算法相比,该算法减少了比较操作的次数,因此减少了对图像进行编码所需的执行时间。在将离散小波变换应用于图像之后,计算每个独立子带的阈值。子带内部集合的扫描由阈值的大小决定,该阈值不仅建立了对幅度较大的系数集合的分层扫描,而且还建立了子带的分层扫描。该算法使用集合划分技术对变换系数进行排序。结果表明,改进的SPIHT可以显着减少操作次数和执行时间,而不会牺牲视觉质量和恢复图像的PSNR。 (C)作者。

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