Edge-Based Image Compression with Homogeneous Diffusion

被引:0
|
作者
Mainberger, Markus [1 ]
Weickert, Joachim [1 ]
机构
[1] Univ Saarland, Fac Math & Comp Sci, Math Image Anal Grp, D-66041 Saarbrucken, Germany
来源
COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS | 2009年 / 5702卷
关键词
image compression; partial differential equations (PDEs); Laplace equation; contour coding; ZERO CROSSINGS; CONTOUR;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is well-known that edges contain semantically important image information. In this paper we present a lossy compression method for cartoon-like images that exploits information at image: edges. These edges are extracted with the Marr-Hildreth operator followed by hysteresis thresholding. Their locations are stored in a lossless way using JBIG. Moreover, we encode the grey or colour values at both sides of each edge by applying quantisation, subsampling and PAQ coding. In the decoding step; information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. Our experiments show that the suggested method outperforms the widely-used JPEG standard and can even beat the advanced JPEG2000 standard for cartoon-like images.
引用
收藏
页码:476 / 483
页数:8
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