Sparse unmixing with truncated weighted nuclear norm for hyperspectral data

نویسندگان

چکیده

å—ä»ªå™¨å’Œè§‚æµ‹æ¡ä»¶é™åˆ¶ï¼Œé«˜å ‰è°±æ•°æ®æ˜“å—å™ªå£°æ±¡æŸ“ï¼Œç»™æ•°æ®è§£è¯‘å¸¦æ¥æŒ‘æˆ˜ã€‚é’ˆå¯¹ä¼ ç»Ÿç¨€ç–è§£æ··æ¨¡åž‹æŠ—å™ªæ€§èƒ½å·®çš„é—®é¢˜ï¼Œæœ¬æ–‡æå‡ºä¸€ç§æˆªæ–­åŠ æƒæ ¸èŒƒæ•°ç¨€ç–è§£æ··æ–¹æ³•ï¼Œåˆ©ç”¨é«˜å ‰è°±å›¾åƒåƒå ƒä¹‹é—´çš„ç›¸å ³æ€§å‡è½»å™ªå£°å¯¹ä¸°åº¦ä¼°è®¡çš„å¹²æ‰°ã€‚è¯¥æ–¹æ³•å€ŸåŠ©ä½Žç§©è¡¨ç¤ºåœ¨æŒ–æŽ˜æ•°æ®å† åœ¨ä½Žç»´ç»“æž„æ–¹é¢çš„ä¼˜åŠ¿ï¼Œåœ¨ç¨€ç–è§£æ··ä¸­åŠ å ¥åŸºäºŽæˆªæ–­åŠ ¸èŒƒæ•°çš„ä½Žç§©çº¦æŸï¼Œå¹¶ç»“åˆåŠ æƒç¨€ç–æŠ€æœ¯ï¼Œåœ¨ç¨€ç–æ­£åˆ™é¡¹ä¸­å¼•å ¥ç©ºé—´é‚»åŸŸæƒé‡ã€‚æˆªæ–­åŠ ¸èŒƒæ•°å¯¹ä¸°åº¦çŸ©é˜µçš„å¥‡å¼‚å€¼å‘é‡åˆ†æ®µå¤„ç†ï¼Œå¯ä»¥æ›´å¥½åœ°å®žçŽ°ä¸°åº¦çŸ©é˜µçš„ä½Žç§©é€¼è¿‘ï¼Œä½¿ä¸°åº¦å›¾åƒä¿æŒç©ºé—´ä¸€è‡´æ€§å¹¶ä¿ç•™æ›´å¤šç»†èŠ‚ä¿¡æ¯ï¼Œç©ºé—´åŠ æƒç­–ç•¥åˆ™å¢žå¼ºäº†ä¸°åº¦å›¾åƒçš„ç©ºé—´è¿žç»­æ€§ã€‚æ¨¡æ‹Ÿé«˜å ‰è°±æ•°æ®ã€CupriteçŸ¿åŒºçœŸå®žæ•°æ®å’Œçº¢æ ‘æž—é«˜å ‰è°±æ•°æ®å®žéªŒè¡¨æ˜Žï¼Œä¸Žå ¶ä»–å ˆè¿›çš„ç¨€ç–è§£æ··æ–¹æ³•ç›¸æ¯”ï¼Œæ‰€ææ–¹æ³•å ·æœ‰æ›´å¥½çš„æŠ—å™ªæ€§ï¼Œèƒ½å¤Ÿæé«˜è§£æ··ç²¾åº¦ã€‚

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ℓ0-Norm Sparse Hyperspectral Unmixing Using Arctan Smoothing

Abstract: The goal of sparse linear hyperspectral unmixing is to determine a scanty subset of spectral signatures of materials contained in each mixed pixel and to estimate their fractional abundances. This turns into an `0-norm minimization, which is an NP-hard problem. In this paper, we propose a new iterative method, which starts as an `1-norm optimization that is convex, has a unique soluti...

متن کامل

Sparse Hyperspectral Unmixing

Given a set of mixed spectral vectors, spectral mixture analysis (or spectral unmixing) aims at estimating the number of reference materials, also called endmembers, their spectral signatures, and their fractional abundances. A semi-supervised approach to deal with the linear spectral unmixing problem consists in assuming that the observed spectral vectors are linear combinations of a small num...

متن کامل

Sparse Unmixing of Hyperspectral Data with Noise Level Estimation

Chang Li 1,2,3, Yong Ma 1,*, Xiaoguang Mei 1,*, Fan Fan 1, Jun Huang 1 and Jiayi Ma 1 1 Electronic Information School, Wuhan University, Wuhan 430072, China; [email protected] (C.L.); [email protected] (F.F.); [email protected] (J.H.); [email protected] (J.M.) 2 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China 3 Schoo...

متن کامل

Hyperspectral Unmixing with Robust Collaborative Sparse Regression

Chang Li 1, Yong Ma 2,∗, Xiaoguang Mei 2, Chengyin Liu 1 and Jiayi Ma 2 1 School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China; [email protected] (C.L.); [email protected] (C.L.) 2 Electronic Information School, Wuhan University, Wuhan 430072, China; [email protected] (X.M.); [email protected] (J.M.) * Corresponden...

متن کامل

Structured Sparse Method for Hyperspectral Unmixing

Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method from the following two a...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of remote sensing

سال: 2022

ISSN: ['1007-4619', '2095-9494']

DOI: https://doi.org/10.11834/jrs.20221553