Multi-strategy image fusion method under compressed sensing framework

Abstract

The invention discloses a multi-strategy image fusion method under a compressed sensing framework, mainly solving the problems of large calculated amount, high time complexity and large storage space of the traditional image fusion method. The multi-strategy image fusion method comprises the following implementation processes: inputting original images A and B and dividing the original images A and B into local images X1 and X2 of C*C in size; respectively carrying out Fourier transformation on X1 an X2 to obtain coefficient matrixes y1 and y2; observing y1 and y2 respectively by adopting a Fourier coefficient low-frequency full variable-density observing model to obtain observation vectors f1 and f2; calculating harmonic coefficients H1 and H2 and frequency-spectrum matching degree S according to f1 and f2; selecting a threshold T and calculating a weighting coefficient; comparing the weighting coefficient, the threshold and the frequency-spectrum matching degree to calculate a fused observation vector f; and iterating the observation vector f for twenty times by using a Split Bregman reconfiguration algorithm to finally obtain a required fused image. Compared with the traditional fusion method, the multi-strategy image fusion method provided by the invention has the advantages of low calculation complexity and good fusion effect, and can be used for video tracking, target recognition and computer vision.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to image fusion, which can be used for video tracking, target recognition and computer vision. Background technique [0002] Image fusion is an information processing technology that processes multiple images to obtain an improved new image. Image fusion technology is a comprehensive image information processing technology that studies how to process and collaboratively utilize multiple images, and make different image information complement each other to obtain a more objective and essential understanding of the same thing or target. Due to the limited focus range of the visible light imaging system and the differences in sensors, in the same scene, a well-focused object can present a clear image, and all objects at a certain distance in front of and behind the object will present varying degrees of blur. An image where all targets are clear; due to differences in image r...

AI Technical Summary

Problems solved by technology

[0005] (1) The amount of data in the fusion image is large, which leads to a large space for image storage, which is not conducive to image compression and transmission;

[0006] (2) The computational complexity of data in image fusion is high, which makes the image fusion process take a long time

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