Summary
Smart Info-Media Systems in Asia
2019
Session Number:RS2
Session:
Number:RS2-6
Enhancing Image Compression by Adaptive Block Truncation Coding with Edge Quantization
Ching-Nung Yang, Yi-Cheng Chen, Yung-Chien Chou, Tao-Ku Chang, Cheonshik Kim,
pp.125-130
Publication Date:2019/9/4
Online ISSN:2188-5079
Summary:
Recently, Mathews and Nair proposed an image compression using adaptive block truncation coding based on edge quantization (ABTC-EQ). Their approach deals with an image by two types of blocks, edge blocks and no-edge blocks. Different from using bi-clustering approach on all blocks in previous BTC-like schemes, ABTC-EQ adopts tri-clustering to tackle edge blocks. The compression ratio of ABTTC-EQ is reduced, but the visual quality of reconstructed image is significant improved. However, it is observed that ABTC-EQ uses 2 bits to represent the index of three clusters in a block. We can only use an average 5/3 bits by variable-length code to represent the index of each cluster. On the other hand, there are two observations on the quantization levels in a block. The first observation is that the difference between two quantization values is often smaller than the quantization values themselves. The second observation is that more clusters may enhance the visual quality of reconstructed image. Based on variable-length coding and the above observations, we design variants of ABTCEQ to enhance the visual quality of reconstructed image and compression ratio.