A multi-scale Shearlet domain image fusion processing method based on block decomposition

Abstract

The invention discloses a multi-scale Shearlet domain image fusion processing method based on block decomposition, and the method comprises the following steps: S1, carrying out the Shearlet positivetransformation of two images to be fused, and obtaining Shearlet coefficients of different scales and different directions; S2, decomposing Shearlet coefficients of different scales and different directions into a plurality of sub-blocks; S3, carrying out fusion processing on the low-scale Shearlet coefficient by utilizing a local variance algorithm; S4, carrying out fusion processing on the high-scale Shearlet coefficient by using a local energy maximum algorithm; And S5, performing Shearlet inverse transformation on the Shearlet coefficient after fusion processing to obtain a fused image. According to the method, the fusion precision is higher, the fusion effect is better, the block effect phenomenon and the blurring phenomenon can be avoided, the detail information of the image is effectively protected, the visual effect is improved, the resolution of the image is improved, and the application requirement is better met.

Description

technical field [0001] The invention relates to an image processing method, in particular to a multi-scale Shearlet domain image fusion processing method based on block decomposition. Background technique [0002] In the existing technology, image fusion is to generate a more informative image from images of the same scene acquired by different imaging mechanisms or at different times. Image fusion technology has been widely used in many fields, such as computer vision, medicine, remote sensing, meteorology And the military field has and extremely important application. The multi-focus image can make the focus of different scenes in the distance more accurate, and make the distant view and near view of the image clearer through fusion. Different sensors can acquire different features of images, such as infrared images and visible light images, radar and infrared image fusion, computed tomography CT and nuclear magnetic resonance images MRI images. By fusing images acquired...

AI Technical Summary

Problems solved by technology

In 1993, Burt and Kolczynski proposed a fusion criterion based on windows, and then a fusion method based on window selection appeared, but these methods will lead to the emergence of block effects

[0005] Although there are the above fusion processing methods, the conventional DCT method and wavelet transform method are not good enough for image sparse representation, and the multi-directional resolution effect is not good enough. In addition, the fusion method based on block decomposition will have block effect, which is not conducive to image fusion and is difficult to achieve. Meet application needs

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