Textural adaptive learning-based super resolution for human face images - 文章详情页

作者：

Yang, Cao (Yang, Cao.) | Xiaoguang, Li (Xiaoguang, Li.) | Li, Zhuo (Li, Zhuo.) | Lansun, Shen (Lansun, Shen.)

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EI Scopus

摘要：

A　low-resolution　face　image　is　segmented　into　detailed　regions　and　flat　regions.　The　detailed　regions　are　super　resolved　using　classified　predictors　according　to　the　local　textural　structures,　while,　the　flat　regions　are　magnified　using　bilinear　interpolation.　Experimental　results　show　that　both　the　visual　quality　and　the　computational　cost　are　improved.　©2009　IEEE.

关键词：

Optical resolving power Image processing

作者机构：

[ 1 ] [Yang, Cao]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China
[ 2 ] [Xiaoguang, Li]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China
[ 3 ] [Li, Zhuo]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China
[ 4 ] [Lansun, Shen]Signal and Information Processing Lab., Beijing University of Technology, Beijing, China

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