Sch. of Electr. Eng. and Comput. Sci., Washington State Univ., Pullman, WA.
IEEE Trans Image Process. 1997;6(11):1473-86. doi: 10.1109/83.641409.
This paper investigates various classification techniques, applied to subband coding of images, as a way of exploiting the nonstationary nature of image subbands. The advantages of subband classification are characterized in a rate-distortion framework in terms of "classification gain" and overall "subband classification gain." Two algorithms, maximum classification gain and equal mean-normalized standard deviation classification, which allow unequal number of blocks in each class, are presented. The dependence between the classification maps from different subbands is exploited either directly while encoding the classification maps or indirectly by constraining the classification maps. The trade-off between the classification gain and the amount of side information is explored. Coding results for a subband image coder based on classification are presented. The simulation results demonstrate the value of classification in subband coding.
本文研究了各种分类技术，应用于图像的子带编码，以利用图像子带的非平稳性。在率失真框架中，从“分类增益”和整体“子带分类增益”两个方面对带分类的优点进行了描述。本文提出了两种算法，即最大分类增益和等均值归一化标准差分类，这两种算法允许每个类中的块数不相等。本文还利用了不同子带的分类图之间的依赖性，要么在编码分类图时直接利用，要么通过约束分类图来间接利用。此外，本文还探讨了分类增益和附加信息量之间的权衡关系。本文还给出了基于分类的子带图像编码器的编码结果。仿真结果表明了分类在子带编码中的价值。
