A Residual Convolutional Neural Network for Pan-Shaprening

作者：Rao, Yizhou^*; He, Lin; Zhu, Jiawei

来源：International Workshop on Remote Sensing with Intelligent Processing (RSIP), Shanghai, 2017-05-18 To 2017-05-21.

DOI：10.1109/RSIP.2017.7958807

• Residuals
• pan-sharpening
• CNN
• spectral distortion

Pan-sharpening has become an important tool in remote sensing, which normally aims at fusing a multi-spectral image with high spectral resolution and a panchromatic image with high spatial resolution. However, some problems, such as spectral distortion, are facing pan-sharpening methods. Inspired by the applications of convolutional neural network (CNN) in many areas, we adopt an effective CNN model to fulfill pansharpening. In our method, only the sparse residuals between the interpolated MS and the pan-sharpened image are learned, which achieves fast convergence and high pan-sharpening quality. The experimental results on real-world data validate the effectiveness of the method.

• 出版日期2017
• 单位华南理工大学