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A Modified-set Partitioning In Hierarchical Trees Algorithm For Real-time Image Compression

机译:改进的分层树分割算法在实时图像压缩中的应用

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Among all algorithms based on wavelet transform and zerotree quantization, Said and Pearlman's set partitioning in hierarchical trees (SPIHT) algorithm is well known for its simplicity and efficiency. SPIHT's high memory requirement is a major drawback to hardware implementation. In this study, we present a modification of SPIHT named modified SPIHT (MSPIHT), which requires less execution time at a low bit rate and less working memory than SPIHT. The MSPIHT coding algorithm is modified with the use of one list to store the coordinates of wavelet coefficients instead of three lists of SPIHT; defines two terms, number of error bits and absolute zerotree; and merges the sorting pass and the refinement pass together as one scan pass. Comparison of MSPIHT with SPIHT on different test image shows that MSPIHT reduces execution time at most 7 times for coding a 512 × 512 grayscale image; reduces execution time at most 11 times at a low bit rate; saves at least 0.5625 MB of memory; and reduces minor peak signal-to noise ratio (PSNR) values, thereby making it highly promising for real-time and memory limited mobile communications.
机译:在所有基于小波变换和零树量化的算法中,赛义德和珀尔曼的分层树集划分(SPIHT)算法以其简单性和效率而闻名。 SPIHT的高内存需求是硬件实现的主要缺点。在这项研究中,我们提出了SPIHT的一种改进,称为改良SPIHT(MSPIHT),与SPIHT相比,它在低比特率和更少的工作内存上需要更少的执行时间。 MSPIHT编码算法通过使用一个列表存储小波系数的坐标而不是三个SPIHT列表进行了修改;定义两个术语,错误位数和绝对零树;并将排序过程和优化过程合并为一个扫描过程。将MSPIHT与SPIHT在不同的测试图像上进行比较,结果表明,对于编码512×512灰度图像,MSPIHT最多可将执行时间减少7倍。低比特率最多可减少11次执行时间;至少节省0.5625 MB的内存;并降低较小的峰值信噪比(PSNR)值,从而使其对于实时和内存受限的移动通信具有巨大的希望。

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