Blocking artifacts reduction for DCT-based image compression using neurofuzzy driven anisotropic diffusion

被引:0
|
作者
Yao, SS [1 ]
Lu, ZK [1 ]
Lin, WS [1 ]
Ong, EP [1 ]
Yang, XK [1 ]
机构
[1] Inst Infocomm Res, Singapore 119613, Singapore
关键词
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a new deblocking method for DCT-based compressed images using anisotropic diffusion. An adaptive anisotropic coefficient derived from neuro-fuzzy network is introduced. The optimal diffusion parameters are estimated using a stochastic optimization technique, which ensures that heavy diffusion performs across the block boundaries and in flat regions while image edges are well preserved. Experimental results have shown that the proposed adaptive diffusion method can significantly suppress coding artifacts and improve the visual quality of the compressed image.
引用
收藏
页码:518 / 521
页数:4
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