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How to measure arithmetic complexity of compression algorithms: a simple solution

机译:如何测量压缩算法的算术复杂度:一个简单的解决方案

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Image compression techniques appear to have matured during the past few years. Differences between the compression performance of different algorithms are very small. The key differences are now features such as embedded coding, regions of interest coding, bitstream manipulation or error resilience. However, there is one major difference present but only rarely discussed: algorithmic complexity. It can correspond to the number of arithmetic operations, memory demands and bandwidth or simply the difficulty of implementation. The performance of image compression algorithms are generally presented in terms of PSNR relative to the possible bitrates. It is interesting to consider a similar relationship in terms of complexity. Unfortunately the term complexity itself is not well defined. In this paper a methodology to measure arithmetic complexity (and eventually other types of complexity) of a complete compression algorithm is presented. The model is then applied to the ISO standard JPEG encoder.
机译:在过去的几年中,图像压缩技术似乎已经成熟。不同算法的压缩性能之间的差异很小。现在的主要区别在于功能,例如嵌入式编码,感兴趣区域编码,比特流操作或错误恢复能力。但是,存在一个主要区别,但很少讨论:算法复杂度。它可以对应于算术运算的数量,存储器需求和带宽,也可以仅对应于实现难度。图像压缩算法的性能通常以相对于可能的比特率的PSNR表示。考虑到复杂性方面的相似关系很有趣。不幸的是,术语“复杂性”本身并没有得到很好的定义。在本文中,提出了一种用于测量完整压缩算法的算术复杂度(以及最终的其他类型的复杂度)的方法。然后将模型应用于ISO标准JPEG编码器。

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