Open AccessA Rate-Distortion-Based Merging Algorithm for Compressed Image Segmentation
Author(s) -
Ying-Shen Juang,
HsiChin Hsin,
TzeYun Sung,
Yaw-Shih Shieh,
Carlo Cattani
Publication year - 2012
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2012/648320
Subject(s) - jpeg 2000 , computer science , encoder , data compression , algorithm , image compression , segmentation , distortion (music) , computer vision , artificial intelligence , code (set theory) , probabilistic logic , domain (mathematical analysis) , computation , image (mathematics) , binary number , boundary (topology) , image processing , mathematics , arithmetic , amplifier , computer network , mathematical analysis , set (abstract data type) , bandwidth (computing) , programming language , operating system
Original images are often compressed for the communication applications. In order to avoid the burden of decompressing computations, it is thus desirable to segment images in the compressed domain directly. This paper presents a simple rate-distortion-based scheme to segment images in the JPEG2000 domain. It is based on a binary arithmetic code table used in the JPEG2000 standard, which is available at both encoder and decoder; thus, there is no need to transmit the segmentation result. Experimental results on the Berkeley image database show that the proposed algorithm is preferable in terms of the running time and the quantitative measures: probabilistic Rand index (PRI) and boundary displacement error (BDE).
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