Coefficient Statistic Based Modified SPIHT Image Compression Algorithm

نویسندگان

  • Jianjun Wang
  • Ying Cui
چکیده

Among all wavelet transform and zero-tree quantization based image coding algorithms, set partitioning in hierarchical trees (SPIHT) is well known for its simplicity and efficiency. But theoretical analysis and experimental results have shown there are still some key points need to be further improved. This paper proposes a coefficient Statistic based Modified SPIHT Lossless Image Compression Algorithm (MSPIHT-ICA). Through adding a new judgment to type A sets, MSPIHT-ICA effectively optimized the compression algorithm’ outputted bit stream. Experiment results further show, compared with SPIHT algorithm, with the same bite rates, MSPIHT-ICA gains higher Peak Signal to Noise Ration (PSNR).

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تاریخ انتشار 2012