Feature extraction of hyperspectral remote sensing image based on optimized Discriminative Locality Alignment

نویسندگان

چکیده

ç›®å‰ï¼Œé«˜å ‰è°±é¥æ„Ÿç‰¹å¾æå–æ–¹æ³•å¾€å¾€å› å—åˆ°å™ªå£°çš„å¹²æ‰°è€Œå¯¼è‡´é™ç»´æ•ˆæžœæ¬ ä½³ã€‚è¿‘å¹´æ¥ï¼Œåˆ¤åˆ«å±€éƒ¨å¯¹é½DLA(Discriminative Locality Alignmentï¼‰ç”±äºŽå¯ä»¥å¤„ç†éžçº¿æ€§åˆ†å¸ƒæ ·æœ¬ã€ä¿ç•™å±€éƒ¨åˆ¤åˆ«ä¿¡æ¯ï¼ŒåŒæ—¶é¿å çŸ©é˜µå¥‡å¼‚æ€§é—®é¢˜ï¼Œå—åˆ°äº†å¾ˆå¤šå­¦è€ çš„å ³æ³¨ï¼›ä½†è¯¥æ–¹æ³•æ— æ³•æœ‰æ•ˆä¼°è®¡å’Œå‡å°‘å™ªå£°å¯¹é«˜å ‰è°±é¥æ„Ÿå½±åƒçš„å½±å“ã€‚é’ˆå¯¹ä»¥ä¸Šé—®é¢˜ï¼Œæœ¬æ–‡æå‡ºäº†æœ€å°å™ªå£°åˆ¤åˆ«å±€éƒ¨å¯¹é½MDLA(Minimum-noise Discriminative Alignmentï¼‰çš„çº¿æ€§ç‰¹å¾æå–æ–¹æ³•å’Œæ ¸æœ€å°å™ªå£°åˆ¤åˆ«å±€éƒ¨å¯¹é½KMDLA(Kernel Minimum-noise Alignment)的非线性特征提取方法。å 分利用最小噪声分离MNF(Minimum Noise Fraction)的去噪能力,将MNF与DLA算法结合提出了MDLAæ–¹æ³•ï¼Œè¯¥æ–¹æ³•é¦–å ˆåˆ©ç”¨MNFå¯¹é«˜å ‰è°±é¥æ„Ÿå½±åƒè¿›è¡Œé™ç»´ï¼Œå‡å°‘å›¾åƒä¸­çš„å™ªå£°ï¼Œç„¶åŽå†åœ¨å­ç©ºé—´è¿›è¡ŒDLAå˜æ¢å¾—åˆ°æœ€ç»ˆçš„æŠ•å½±æ•°æ®ã€‚ä¸ºæé«˜æ ·æœ¬åˆ†å¸ƒçš„éžçº¿æ€§åˆ¤åˆ«èƒ½åŠ›ï¼ŒåŸºäºŽKMNF与DLAç®—æ³•å°†æ ¸æ–¹æ³•å¼•å ¥MDLA,提出了KMDLAæ–¹æ³•ï¼Œè¯¥æ–¹æ³•é¦–å ˆé€šè¿‡KMNFå°†åŽŸå§‹ç©ºé—´çš„æ•°æ®æ˜ å°„åˆ°æ–°çš„ç‰¹å¾ç©ºé—´ï¼Œç„¶åŽåœ¨ç‰¹å¾ç©ºé—´ä¸­è¿›è¡ŒDLAå˜æ¢å¾—åˆ°æœ€ç»ˆçš„æŠ•å½±æ•°æ®ã€‚å®žéªŒéƒ¨åˆ†é¦–å ˆåˆ©ç”¨3ç»„é«˜å ‰è°±é¥æ„Ÿæ•°æ®å¯¹æå‡ºç®—æ³•çš„æ€§èƒ½è¿›è¡Œè¯„ä»·ï¼Œå¹¶ä¸Žç›¸å ³ç‰¹å¾æå–ç®—æ³•è¿›è¡Œäº†å¯¹æ¯”åˆ†æžï¼Œæœ€åŽåˆ†æžäº†å›¾åƒå™ªå£°å¯¹ä¸åŒé™ç»´æ–¹æ³•æ€§èƒ½çš„å½±å“ã€‚ç»“æžœè¡¨æ˜Žï¼šæå‡ºçš„ç®—æ³•å¯¹é«˜å ‰è°±é¥æ„Ÿå½±åƒç‰¹å¾æå–æ•ˆæžœè¾ƒå¥½ï¼Œä¸”å¯æœ‰æ•ˆå‡å°‘å™ªå£°å¯¹å½±åƒçš„å½±å“å¹¶æå‡å ¶åˆ†ç±»å‡†ç¡®åº¦ã€‚

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ژورنال

عنوان ژورنال: Journal of remote sensing

سال: 2021

ISSN: ['1007-4619', '2095-9494']

DOI: https://doi.org/10.11834/jrs.20219448