为了在图像轮廓处获得更好的压缩效果,在多级树集合分裂(SPIHT)算法的基础上提出了一种优先编码周围邻域中重要系数较多的系数与集合的小波图像压缩算法.在编码之前对系数或集合按照周围重要系数的个数进行排序,而且在扫描完周围有重要系数的集合后,就精细扫描已经得到的重要系数.这种编码次序是自适应确定的,不需要任何额外的存储空间,而且在到达指定压缩比时能够编码更多的重要系数.实验结果表明,对比原来的SPIHT算法,该方法能提高峰值信噪比并改善主观视觉感受.%In order to obtain better compression on image edge, an improved Set Partitioning In Hierarchical Trees (SPIHT) algorithm based on prior scanning the coefficients around which there were more significant coefficients was proposed. The coefficients or sets were sorted according to the number of surrounding significant coefficients before being coded, and the previous significant coefficients were refined as soon as the sets around which there existed any significant coefficients had been scanned. The scanning order was confirmed adaptively and did not need any extra storage. It can code more significant coefficients at a specified compression ratio. The experimental results show that the method can improve PSNR and the subjective visual experience compared with SPIHT.
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