New self-adaptive image coder

J. M. Quan, Shen-Chuan Tai

Research output: Contribution to journalArticlepeer-review


In this paper, we present a compression technique which preserves edges in the compressed image and adapts itself to the local nature of the image. Inter block redundancies were seldom considered in the earlier design of compressors. We take this into account, achieve a good compression ratio and also preserve good visual quality at the same time. In this paper, the range value presented by Nosiopoulos is used to classify the image blocks into four coding techniques, respectively, which are used to compress the associated class image block. The four coding algorithms are: mean coding, 2_level MMSE quantizer for block truncation coding (BTC), hybrid BTC (HBTC) and quad-tree coding. Experimental results show that considerable improvements over the work by Nasiopoulus can be achieved. As for complex images which contain sharp edges and even single-pixel-width grey level sudden changes, their visual quality is very well-preserved. Thus, our technique is suitable for practical applications if image quality is requested.

Original languageEnglish
Pages (from-to)129-137
Number of pages9
JournalJournal of Information Science and Engineering
Issue number1
Publication statusPublished - 1994 Mar 1

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Hardware and Architecture
  • Library and Information Sciences
  • Computational Theory and Mathematics


Dive into the research topics of 'New self-adaptive image coder'. Together they form a unique fingerprint.

Cite this