The Optimum Frequency Band Partition Based on Kullback–Leibler Divergence in Subband Image Coding
Haruhiko Miyazaki, Masashi Kameda · 2014
In order to improve the coding performance of subband image coding, the optimum frequency band partition (OFBP) based on the parameters of subband signal such as signal power or kurtosis has been proposed. However, the superiority of coding performances for both results using the above parameters is dependent with the contents of input image and the coding rate. In this paper, it is clarified that the similarity between the probability density functions (PDFs) in subband signals is closely related to the improvement of coding performance of the OFBP. We propose a new method to determine the optimum partition pattern on the 2-dimensional frequency domain using the Kullback–Leibler divergence (KLD) which is known as a similarity measurement between given two PDFs. It is seen in the experimental results that the PSNR of the proposed method is at most 3.0[dB] larger than the previous method in OFBP and JPEG at the same coding rate.