Complex Contourlet-CNN for polarimetric SAR image classification
作者:
Highlights:
• A novel complex CNN is constructed, in which the operation rules of convolutional layer, subsampling layer, normalization layer, fully-connected layer and activation function are redefined in complex field.
• Based on the proposed complex CNN, the multiscale deep Contourlet filter banks are constructed in order to extract robust discriminative features with multidirection, multiscale, and multiresolution properties.
• The proposed complex Contourlet-CNN is successfully applied for PolSAR image classification.
摘要
•A novel complex CNN is constructed, in which the operation rules of convolutional layer, subsampling layer, normalization layer, fully-connected layer and activation function are redefined in complex field.•Based on the proposed complex CNN, the multiscale deep Contourlet filter banks are constructed in order to extract robust discriminative features with multidirection, multiscale, and multiresolution properties.•The proposed complex Contourlet-CNN is successfully applied for PolSAR image classification.
论文关键词:Complex Contourlet-CNN,Multiscale deep Contourlet filter banks,Polarimetric SARimage classification
论文评审过程:Received 16 January 2019, Revised 25 September 2019, Accepted 13 November 2019, Available online 11 December 2019, Version of Record 13 May 2020.
论文官网地址:https://doi.org/10.1016/j.patcog.2019.107110