多視極化合成孔徑雷達(dá)圖象的分類和極化通道優(yōu)化
CLASSIFICATION OF MULTI-LOOK POLARIMETRIC SAR IMAGERY AND POLARIZATION CHANNEL OPTIMIZATION
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摘要: 本文提出一個(gè)新的最大似然(ML)分類算法對(duì)多視全極化合成孔徑雷達(dá)(SAR)圖象進(jìn)行分類,給出了應(yīng)用NASA/JPL機(jī)載L波段四視全極化SAR實(shí)測(cè)數(shù)據(jù)的試驗(yàn)結(jié)果,證明了新算法的有效性。此外,本文還將所提算法應(yīng)用于部分的多視全極化SAR數(shù)據(jù)中,實(shí)現(xiàn)了地貌類型分類的極化通道優(yōu)化。
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關(guān)鍵詞:
- 極化合成孔徑雷達(dá); 多視處理; 相干斑; 分類; 極化通道優(yōu)化
Abstract: In this paper, a new maximum likelihood (ML) classification algorithm is proposed to classify the multi-look polarimetric synthetic aperture radar (SAR) imagery. Experimental results with the NASA/JPL airborne L-band 4-look polarimetric SAR data demonstrate the effectiveness of the new algorithm. Furthermore, when using the algorithm in the classifications with subsets of the multi-look polarimetric SAR data, the polarization-channel optimization for the terrain type classification is implemented. -
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