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利用0-1矩陣分解集成的極化SAR圖像分類

陳博 王爽 焦李成 劉芳 毛莎莎 張爽

陳博, 王爽, 焦李成, 劉芳, 毛莎莎, 張爽. 利用0-1矩陣分解集成的極化SAR圖像分類[J]. 電子與信息學(xué)報, 2015, 37(6): 1495-1501. doi: 10.11999/JEIT141059
引用本文: 陳博, 王爽, 焦李成, 劉芳, 毛莎莎, 張爽. 利用0-1矩陣分解集成的極化SAR圖像分類[J]. 電子與信息學(xué)報, 2015, 37(6): 1495-1501. doi: 10.11999/JEIT141059
Chen Bo, Wang Shuang, Jiao Li-cheng, Liu Fang, Mao Sha-sha, Zhang Shuang. Polarimetric SAR Image Classification via Weighted Ensemble Based on 0-1 Matrix Decomposition[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1495-1501. doi: 10.11999/JEIT141059
Citation: Chen Bo, Wang Shuang, Jiao Li-cheng, Liu Fang, Mao Sha-sha, Zhang Shuang. Polarimetric SAR Image Classification via Weighted Ensemble Based on 0-1 Matrix Decomposition[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1495-1501. doi: 10.11999/JEIT141059

利用0-1矩陣分解集成的極化SAR圖像分類

doi: 10.11999/JEIT141059
基金項目: 

國家973計劃項目(2013CB329402),國家自然科學(xué)基金(61271302, 61272282, 61202176, 61271298)和國家教育部博士點基金(20100203120005)資助課題

Polarimetric SAR Image Classification via Weighted Ensemble Based on 0-1 Matrix Decomposition

  • 摘要: 全極化合成孔徑雷達(PolSAR)圖像蘊含更豐富的散射信息,具有更多的可用特征。如何使用這些特征是極化SAR圖像分類中非常重要的一步,但是目前尚未對此提出非常明確的準(zhǔn)則。為了能夠有效地解決上述問題,該文提出一種基于特征加權(quán)集成的極化SAR圖像分類算法。該算法采用0-1矩陣分解集成方法對包括不同特征的數(shù)據(jù)集進行學(xué)習(xí)獲得相應(yīng)加權(quán)系數(shù),并通過對每個特征集獲得的預(yù)測結(jié)果進行加權(quán)集成來提高極化SAR圖像分類性能。首先,輸入極化SAR數(shù)據(jù),獲得極化特征作為原始特征集,并對其進行隨機抽取獲得不同的特征子集;然后,使用0-1矩陣集成算法得到每個特征值相對應(yīng)的加權(quán)系數(shù);最后,通過對各個特征子集的預(yù)測結(jié)果進行集成得到最終極化SAR圖像分類結(jié)果。實測L波段和C波段極化數(shù)據(jù)的實驗結(jié)果表明,該算法可以有效地提高極化SAR圖像分類的準(zhǔn)確度。
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出版歷程
  • 收稿日期:  2014-08-11
  • 修回日期:  2014-10-22
  • 刊出日期:  2015-06-19

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