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沈煥峰、博士生李星華等的的論文在IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING刊出
發布時間:2014-03-31 08:09:06     發布者:yz     浏覽次數:

标題:Compressed Sensing-Based Inpainting of Aqua Moderate Resolution Imaging Spectroradiometer Band 6 Using Adaptive Spectrum-Weighted Sparse Bayesian Dictionary Learning作者:Shen, Huanfeng; Li, Xinghua; Zhang, Liangpei; Tao, Dacheng; Zeng, Chao

來源出版物:IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 卷:52 期:2 頁:894-906 DOI:10.1109/TGRS.2013.2245509 出版年:FEB 2014

摘要:Because of malfunction or noise in 15 out of the 20 detectors, band 6 (1.628-1.652 mu m) of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Aqua satellite contains large areas of dead pixel stripes. Therefore, the corresponding high-level products of MODIS are corrupted by this periodic phenomenon. This paper proposes an improved Bayesian dictionary learning algorithm based on the burgeoning compressed sensing theory to solve this problem. Compared with other state-of-the-art methods, the proposed method can adaptively exploit the spectral relations of band 6 and other spectra. The performance of the proposed method is demonstrated by experiments on both simulated Terra and real Aqua images.

入藏号:WOS:000328941300009

文獻類型:Article

語種:English

作者關鍵詞:Aqua Moderate Resolution Imaging Spectroradiometer (MODIS); band 6; Bayesian dictionary learning; compressed sensing (CS); image inpainting

擴展關鍵詞:ORTHOGONAL MATCHING PURSUIT; SIGNAL RECOVERY; IMAGES; MODIS; RECONSTRUCTION; ALGORITHM; PDE

通訊作者地址:Shen, Huanfeng;Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

電子郵件地址:shenhf@whu.edu.cn; lixinghua5540@sina.com.cn; zlp62@public.wh.hb.cn; dacheng.tao@gmail.com; zengchaozc@hotmail.com

地址:

[Shen, Huanfeng; Li, Xinghua] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Zhang, Liangpei; Zeng, Chao] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.

[Tao, Dacheng] Univ Technol Sydney, Ctr Quantum Computat & Intelligent Syst, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia.

研究方向:Geochemistry & Geophysics; Engineering; Remote Sensing

ISSN:0196-2892

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