标题:Adaptive Norm Selection for Regularized Image Restoration and Super-Resolution
作者:Shen, Huanfeng; Peng, Li; Yue, Linwei; Yuan, Qiangqiang; Zhang, Liangpei
来源出版物:IEEE TRANSACTIONS ON CYBERNETICS 卷:46 期:6 页码:1388-1399 DOI: 10.1109/TCYB.2015.2446755 出版年:JUN 2016
摘要:In the commonly employed regularization models of image restoration and super-resolution (SR), the norm determination is often challenging. This paper proposes a method to adaptively determine the optimal norms for both fidelity term and regularization term in the (SR) restoration model. Inspired by a generalized likelihood ratio test, a piecewise function is proposed to solve the norm of the fidelity term. This function can find the stable norm value in a certain number of iterations, regardless of whether the noise type is Gaussian, impulse, or mixed. For the regularization norm, the main advantage of the proposed method is that it is locally adaptive. Specifically, it assigns different norms for different pixel locations, according to the local activity measured by a structure tensor metric. The proposed method was tested using different types of images. The experimental results and error analyses verify the efficacy of the method.
入藏号:WOS:000376110100012
文献类型:Article
语种:English
作者关键词:Adaptive norm selection, image restoration, super-resolution (SR)
扩展关键词:REMOTE-SENSING IMAGES; SUPER RESOLUTION; MIXED NOISE; RECONSTRUCTION; MINIMIZATION; RECOGNITION; FRAME
通讯作者地址:Shen, HF; Peng, L, Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.Yue, LW;
Zhang, LP, Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.
Yuan, QQ, Wuhan Univ*, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China.
电子邮件地址:shenhf@whu.edu.cn; jiuguik@126.com; yuelinwei2008@126.com; qqyuan@sgg.whu.edu.cn; zlp62@whu.edu.cn
地址:
[Shen, Huanfeng; Peng, Li] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
[Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei] Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Peoples R China.
[Yue, Linwei; Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.
[Yuan, Qiangqiang] Wuhan Univ, Sch Geodesy & Geomat, Wuhan 430079, Peoples R China.
研究方向:Computer Science
ISSN:2168-2267
eISSN: 2168-2275
影响因子(2014):3.469
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