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引用次数: 3
摘要
之前,我们提出了一种非常简单的零树编码算法,称为listless zero - tree coding (LZC),其编码内存需求明显低于SPIHT。与SPIHT一样,LZC执行递归树搜索,当比特率较低时,可能会丢弃一些重要的系数。因此,我们提出了一种新的LZC算法,该算法使用栅格树搜索来最小化重要信息的丢失。零树结构嵌入到递归树搜索中,但对于栅格树搜索,零树结构需要存储在缓冲内存中。新的LZC利用一个标志位图来存储矩阵范围的零树结构,这种结构通常由其他栅格树搜索零树算法存储在坐标列表中。因此,新的LZC不仅具有极低的编码内存需求,而且具有非常低的编码复杂度。
Previously, we have proposed a very simple zerotree coding algorithm called listless zerotree coding (LZC) whose coding memory requirement is significantly lower than that of SPIHT. In common with SPIHT, LZC performs a recursive tree search that is likely to discard some important coefficients when the bit rate is low. Therefore, we propose a new LZC algorithm that uses a raster tree search to minimize important information loss. The zerotree structure is embedded into the recursive tree search but for the raster tree search the zerotree structure will need to be stored in the buffer memory. The new LZC utilizes a flag bitmap to store the matrix-wide zerotree structure that is conventionally stored in coordinate lists by other raster tree search zerotree algorithms. Consequently, the new LZC exhibits not only a dramatically low coding memory requirement but also a very low coding complexity.