基于上下文的网格拓扑压缩熵编码方法

提出了一种普遍适用于网格拓扑压缩的高效熵编码方法.不同于以往的单纯利用算术编码或Huffman编码对遍历网格生成的拓扑流进行编码压缩,对这些拓扑流的每个符号先计算其Huffman编码,然后采用基于上下文(已编码序列的倒数第2个符号作为上下文)的算术编码方法来编码其Huffman值,从而实现对网格模型拓扑信息的有效压缩.实验结果表明,熵编码方法普遍适用于各种网格拓扑压缩方法得到的拓扑流的压缩,其压缩结果普遍高于拓扑流序列的熵值——绝大多数拓扑压缩算法各自最好的压缩比.

Context-Based Entropy Encoding Method for Connectivity Compression of Meshes

A general efficient algorithm for entropy encoding of the connectivity information of meshes is presented in this paper. In comparison to the previous encoding methods, which use only Huffman or arithmetic coding method to encode operator series, this coding method can efficiently compress connectivity information by first calculating Huffman code for every symbol in connectivity series, followed by encoding the Huffman code through using a context-based arithmetic coding method. Experimental results indicate that this method can be applied to almost all the connectivity compression algorithms for meshes. The compression result by using this entropy encoding method is generally higher than the entropy of the series-the best compression result that most connectivity compression algorithms of mesh can obtain respectively.