%0 Journal Article
%T A Log-WT Based Super-resolution Algorithm<br>基于Log-WT的人脸图像超分辨率重建
%A Qiao Jian-ping Liu Ju Yan Hua Sun Jian-de
%A <br>乔建苹
%A 刘琚
%A 闫华
%A 孙建德
%J 电子与信息学报
%D 2008
%I 
%X Most learning-based super-resolution algorithms neglect the illumination problem. In this paper, a new image representation called Logarithmic-Wavelet Transform (Log-WT) is developed for the elimination of the lighting effect in the image. Meanwhile, a Log-WT based method is proposed to combine super-resolution and shadow removing into a single operation. In this method first intrinsic, illumination invariant features of the image are extracted with exploiting logarithmic-wavelet transform. Then an initial estimation of high resolution image is obtained based on the assumption that small patches in low resolution space and patches in high resolution space share the similar local manifold structure. Finally the target high resolution image is reconstructed by applying the special face constraints in pixel domain. Experimental results demonstrate that the proposed method simultaneously achieves single-image super-resolution and image enhancement especially shadow removing. After that, reconstruction results are used for face recognition which improves the recognition rate.
%K Face super-resolution
%K Logarithmic-Wavelet Transform (Log-WT)
%K Manifold learning
%K Shadow removal<br>人脸超分辨率
%K Log-WT变换
%K 流形学习
%K 阴影消除
%K 人脸识别
%K 图像超分辨率
%K 重建
%K Algorithm
%K 识别率
%K 应用
%K 明显效果
%K 阴影效应
%K 图像分辨率
%K 影响
%K 因素
%K 光照无关
%K 算法
%K 仿真结果
%K 图像增强
%K 先验约束
%K 人脸图像
%K 关系
%K 高分辨率图像
%K 建模
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=61F500FD7F315729D83B600EBA3B351E&yid=67289AFF6305E306&vid=340AC2BF8E7AB4FD&iid=B31275AF3241DB2D&sid=C700F38C49C581D7&eid=B9CA56463DAD3251&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=1&reference_num=10