嵌入式小波比特流的低复杂度高阶上下文建模

Xiaolin Wu
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引用次数: 10

摘要

在过去三年左右的时间里,特别是在去年启动的JPEG 2000标准化过程中,嵌入式小波比特流的统计上下文建模受到了图像压缩社区的大量关注。高阶上下文建模已被证明是小波图像编码器实现高率失真性能的必要条件。然而,如果在算法设计和实现中不注意,高阶建模上下文的形成可能会占用CPU和内存,从而给小波编码系统带来计算瓶颈。本文重点研究了高阶统计上下文建模的操作方面,并介绍了一些快速算法技术,可以大大降低小波域高阶上下文建模的时间和空间复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low complexity high-order context modeling of embedded wavelet bit streams
In the past three or so years, particularly during the JPEG 2000 standardization process that was launched last year, statistical context modeling of embedded wavelet bit streams has received a lot of attention from the image compression community. High-order context modeling has been proven to be indispensable for high rate-distortion performance of wavelet image coders. However, if care is not taken in algorithm design and implementation, the formation of high-order modeling contexts can be both CPU and memory greedy, creating a computation bottleneck for wavelet coding systems. In this paper we focus on the operational aspect of high-order statistical context modeling, and introduce some fast algorithm techniques that can drastically reduce both time and space complexities of high-order context modeling in the wavelet domain.
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