二维网格编码矢量量化及其在静止图像量化中的应用

该文提出了在二维码书空间中，在矢量量化（VQ）的基础上，应用网格编码量化（TCQ）的思想来实现量化的新方法－－二维网格编码矢量量化（2D－TCVQ）。该方法首先把小码书扩展成大的虚码书，然后用网格编码矢量量化（TCVQ）的方法在扩大的二维码书空间中用维物比算法来寻找最佳量化路径。码书扩大造成第一子集最小失真减小从提高了量化性能。由于二维TCVQ采用的码书尺寸较小，因而可以应用到低存贮、低功耗的编解码环境。仿真结果表明，同一码书尺寸下，二维TCVQ比TCVQ好0．5dB左右。同时，该方法具有计算量适中，解码简单以及对误差扩散不敏感的优点。

Still image quantization using two-dimension trellis coded vector quantization

A method called Two Dimension Trellis Coded Vector Quantization(2D-TCVQ) which applies the method of TCQ after VQ is implemented is proposed. This method first expands the small codebook to larger virtual codebook, then uses Viterbi algorithm in two dimension to search the minimal distortion quantized route. The expansion of codebook min-ishes the minimal distortion in every subset and improves the quantization performance. By using small size codebook 2D-TCVQ can be applied in many low-power encode/decode condition. Simulation states the method has advantage of 0.5dB nearly over TCVQ.The method also has capability that it has only modest encoding complexity with simple decoding and it is insensitive to channel errors.