A remote sensing image fusion method based on difference image sparse representation

Abstract

The invention discloses a remote sensing image fusion method based on difference image sparse representation and mainly resolves a problem of spectrum distortion in a conventional remote sensing image fusion method. The implementation steps of the method comprise: inputting an image set and performing block acquisition in order to acquire an image block data set; constructing a high-low resolution image training set according to the image block data set; training the high-low resolution image training set with a semi-symmetric dictionary training method in order to obtain a training dictionary; inputting a low-resolution multispectral image to be fused and a high-resolution full-color image and calculating a low-resolution difference image to be fused; and performing super-resolution processing on the low-resolution difference image to be fused with a semi-symmetric dictionary image super-resolution method in order to obtain a high-resolution difference image and performing inverse transformation on the high-resolution difference image in order to obtain a high-resolution multispectral image. Compared with a classic remote sensing image fusion method, the remote sensing image fusion method based on difference image sparse representation reduces spectrum distortion because of the use of a fusion model based on difference images and can be used in object identification.

Description

technical field [0001] The invention belongs to the technical field of image processing and relates to a remote sensing image fusion method, which can be used for subsequent image interpretation, target detection, target recognition and the like of remote sensing images. Background technique [0002] Optical remote sensing sensors can obtain a variety of surface pictures to provide useful information for agricultural production, earth observation, weather forecasting, etc. However, most optical remote sensing sensors do not provide both spatial and spectral high-resolution images. For example: the images obtained by Ikonos remote sensing sensor and Quickbird remote sensing sensor are low-resolution multispectral images and high-resolution panchromatic images. The purpose of remote sensing image fusion technology is to obtain high-resolution multispectral images in order to provide more accurate and comprehensive information for subsequent understanding and interpretation. C...

AI Technical Summary

Problems solved by technology

When this method is applied to remote sensing image fusion, due to the difference between the gray scale of the high-resolution panchromatic image and the gray scale of the high-resolution multispectral image, the spectral distortion after fusion is relatively serious.

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