Image fusion method and apparatus based on latent low rank representation and structure tensor

Abstract

An image fusion method and apparatus based on potentially low rank representations and structural tensors, Aiming at the shortcomings of the existing dual-channel PCNN model in solving the problem ofinfrared and visible image fusion, The LSR operator based on LatLRR algorithm is used as the external stimulation of PCNN model, to solve the large difference between the infrared image and the visible image, and the TSV operator based on structural tensor singular value decomposition is used as the link strength, Characterization of the image feature changes, to some extent, can solve the infrared image and visible image spectral differences resulting in lower contrast of the fusion image, while retaining a relatively complete wealth of texture information and detail information, and image transition naturally.

Description

technical field [0001] The invention relates to the field of image fusion, in particular to an image fusion method and device based on latent low-rank representation and structure tensor. Background technique [0002] With the continuous development of digital image processing technology and data fusion technology, the research on infrared (IR) and visible light (VI) image fusion technology has gradually become a research hotspot. The fusion of infrared and visible light images is to combine the salient features of infrared images with the gradient texture features of visible light images, which is conducive to faster and more accurate detection of targets in the case of concealment, camouflage and confusion. Since the fused image can combine the advantages of the source images, this technology has been widely used in military reconnaissance, computer vision, security monitoring and other fields. [0003] For the fusion between IR and VI images, there are currently two main...

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Problems solved by technology

[0004] The embodiment of the present invention provides an image fusion method and device based on latent low-rank representation and structural tensor, which solves the problems of low contrast and large black artifacts in the fusion image due to the large spectral difference between infrared images and visible light images. , which can better express the characteristics of the image, perfectly combine the texture information of visible light with the salient features of the infrared image, and finally achieve a better fusion effect

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