雙波段全極化SAR圖像非監(jiān)督分類方法及實(shí)驗(yàn)研究
Unsupervised Classification Methods and Experimental Research of Dual-frequency Fully Polarimetric SAR Images
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摘要: 該文首先采用H/分類對(duì)像素進(jìn)行了初始猜測(cè)，然后進(jìn)一步采用Bayes最大似然估計(jì)(ML）分類法對(duì)像素進(jìn)行重新歸類．不同波段電磁波對(duì)地物散射具有不同的屬性，因而我們采用雙波段全極化SAR數(shù)據(jù)結(jié)合的分類方法，得到了更好的分類結(jié)果．SAR圖像的相干斑會(huì)影響圖像的分類準(zhǔn)確度和精度．在進(jìn)行分類處理前，對(duì)雙波段全極化SAR圖像相干斑進(jìn)行矢量濾波處理．該文使用NASA/JPL實(shí)驗(yàn)室在天山地區(qū)的實(shí)測(cè)數(shù)據(jù)對(duì)這些分類算法進(jìn)行了實(shí)驗(yàn)研究．給出了單波段以及雙波段全極化SAR分類結(jié)果的偽彩色圖．其中雙波段全極化SAR濾波后數(shù)據(jù)具有相對(duì)最優(yōu)的分類結(jié)果．
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關(guān)鍵詞:
- 全極化SAR;非監(jiān)督分類;相干斑;矢量濾波
Abstract: In this paper, initial assumption of SAR pixel distribution is derived from H/a classifier. Then a Maximum Likelihood (ML) method is introduced to improve the classifi-cation.. The backscattering properties of a natural medium, that varies with the observation frequency, dual-frequency SAR images are combined to get further improved classification. Speckle in SAR images will disturb classification accuracy. Vector filter of speckle is used to dual-frequency images before classification. Experiments are done on data got by NASA/JPL lab near Tien Mountains, and pseudo-colored classification results of both single and dual frequency POLSAR image are submitted. Results show that filtered dual-frequency fully polarimetric SAR data obtain the best classification result. -
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