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.