A Pansharpening Method Based on Deep Convolutional Auto-Encode
Since the MS image has high spectral resolution and the PAN image has high spatial resolu-tion,attempts are made to fuse the MS image and the PAN image to obtain a fused image with high spec-tral and spatial resolution,a process known as Pansharpening.For the current Pansharpening process in deep learning research,it is prone to overfitting,as well as the generalization ability decreases,informa-tion loss and insufficient network performance.A deep Pansharpening method based on convolutional CAE is proposed in this paper,using the HSV transform,to generate fused images through the process of encoding and decoding the hue channel,which makes the fused image enhanced.Combine the advanta-ges of convolutional neural network to overcome the problems of insufficient detail and texture capture and high noise sensitivity in traditional Pansharpening methods,and effectively extract the local and global features of the image.
万方数据
维普
