Remote sensitive image fusing method based on residual error

Abstract

The invention relates to a remote sensing image fusion method based on residual error. The method acquires residual error image of multi-spectrum image and residual error image of whole-color image with residual error extracting algorithm; then the residual error images of the multi-spectrum image is interpolated with the same size to the residual error image of the whole-color image, carries on image fusion to the residual error image of the multi-spectrum image and the residual error image of the whole-color image after being interpolated, restores the high resolution residual error of the multi-spectrum image; finally the high resolution image estimation of the multi-spectrum image can be acquired through adding the interpolation image of the spectrum image and the residual error image of multi-spectrum image. The invention can enhances the space detail representing ability of the fused image, at the same time, it reserves the spectrum information of original multi-spectrum image, its structure is simple, and the effect is excellent.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a residual-based remote sensing image fusion method. Background technique [0002] Remote sensing image fusion is a technology that uses certain methods to combine the advantages of each image to generate a new image after spatial registration of different types of image data. For example, people usually want to fuse multispectral images and panchromatic images so that the fused multispectral images have high spatial detail performance capabilities while maintaining the spectral characteristics of multispectral images to obtain a more comprehensive and clear view of the surface. In order to improve the interpretation and analysis accuracy of remote sensing images. [0003] The fusion method of remote sensing images mainly includes the HIS (Hue-Intensity-Saturation) transformation fusion method. [1，2] , PCA (Principal Component Analysis) fusio...

AI Technical Summary

Problems solved by technology

The common disadvantage of these two "component replacement" methods is that the spectral information of the multispectral image will be severely damaged [1-4]

[0005] Because the wavelet transform fusion method directly discards the low-frequency components of the panchromatic image, it is prone to block effects

At the same time, the size of the decomposition order of the wavelet transform also has a great impact on the fusion effect

If the order of wavelet decomposition is selected low, although the spectral characteristics are well preserved, the ability to express the spatial details of the enhanced multispectral image is poor, and the texture of the ground objects is prone to blurring; if the order of wavelet decomposition is selected high, although The enhanced multispectral image has better performance of spatial details, but poor preservation of spectral characteristics [5-7]

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