Remote sensing image super-resolution method based on multi-scale feature adaptive fusion network

Abstract

The invention relates to a remote sensing image super-resolution method based on a multi-scale feature adaptive fusion network, and the method comprises: 1) carrying out the convolution operation of an originally inputted low-resolution remote sensing image through a filter, and extracting an original feature map; 2) extracting self-adaptive multi-scale features of the original feature map throughn cascaded multi-scale feature extraction modules AMFE to obtain a self-adaptive multi-scale feature map; 3) superposing the original feature map and the adaptive multi-scale feature map, and performing convolution operation on the superposed map by using a filter to realize feature dimension reduction and fusion; and 4) by adopting a sub-pixel convolution method, obtaining a final remote sensingimage after super-resolution reconstruction. The invention provides the remote sensing image super-resolution method based on the multi-scale feature self-adaptive fusion network, which can realize self-adaptive fusion of multi-scale feature information of the remote sensing image, can realize efficient reconstruction of high-resolution detail information of the remote sensing image and can improve the image super-resolution reconstruction effect.

Description

Technical field [0001] The invention belongs to the field of surveying and mapping science and technology, and relates to a remote sensing image super-resolution method, in particular to a remote sensing image super-resolution method based on a multi-scale feature adaptive fusion network. Background technique [0002] Image super-resolution (SR) technology is mainly to reconstruct visually pleasing high-resolution (HR) images from low-resolution (LR) images. In computer vision The field is a classic but challenging problem. Compared with low-resolution remote sensing images, high-resolution remote sensing images can provide richer and more accurate information and have a wider range of uses. The super-resolution reconstruction of remote sensing images is an effective method to obtain high-resolution remote sensing images at low cost and has important practical significance. [0003] Single image super-resolution reconstruction (Single Image Super-Resolution, SISR) technology is m...

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Problems solved by technology

[0005] However, the complex network structure cannot guarantee the full use of feature information. On the contrary, redundant feature information will not only cause a sharp drop in computational efficiency, but also cause the truly useful feature information to be "submerged" by useless information, thereby deteriorating the image quality. The reconstruction effect of

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