用于Landsat ETM+和ERS-2 SAR圖像融合對(duì)城區(qū)地物特征分類的BP-ANN/GA混合算法
A Hybrid BP-ANN/GA Algorithm for Classification of Urban Terrain Surfaces Using Fused Images of Landsat ETM+ and ERS-2 SAR
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摘要: 該文建立了反向傳播人工神經(jīng)網(wǎng)絡(luò) (Back Propagation Artificial Neural Network, BP-ANN)和遺傳算法 (Genetic Algorithm, GA)的BP-ANN/GA混合算法。利用GA算法的全局優(yōu)化能力優(yōu)化BP-ANN的初始權(quán)值,克服了傳統(tǒng)BP-ANN收斂速度慢,容易陷入局部最小的缺點(diǎn)。BP-ANN/GA混合算法對(duì)Landsat ETM+4, 5, 7三波段紅外圖像和ERS-2 SAR雷達(dá)圖像的融合數(shù)據(jù)進(jìn)行了城市多類地物特征分類。結(jié)果表明:BP-ANN/GA算法不僅提高多源遙感圖像自動(dòng)分類的速度,而且提高了各類特征分類的精度。該文對(duì)上海浦東地區(qū)的Landsat ETM+和ERS-2 SAR數(shù)據(jù)作了融合分類試驗(yàn)與驗(yàn)證。
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關(guān)鍵詞:
- 圖像融合;BP-ANN/GA;地表分類
Abstract: A hybrid algorithm of the BP-ANN/GA (Back Propagation Artificial Neural Network and Genetic Algorithm) is developed to optimize the initial weights and make fast convergence of the BP-ANN. This algorithm is applied to classification of urban terrain surfaces with fused data of Landsat ETM+ and ERS-2 SAR. An example of the Shanghai Pudong area using both the Landsat ETM+ and ERS-2 SAR image data well demonstrates the classification speed and accuracy of the algorithm. -
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