Video image fusion performance evaluation method based on structure similarity and human vision

Abstract

The invention discloses a video image fusion performance evaluation method based on structure similarity and human vision, wherein the method is mainly used for solving the problem that the evaluation result obtained by the prior art does not accord with the subjective evaluation result. The method is implemented through the following steps of: constructing a space performance evaluation index according to the structure similarity between each frame of image of a fused video and each frame of image of an input video; constructing a time performance evaluation index according to the structure similarity between each frame of difference image of the fused video and each frame of difference image of the input video; combining the space performance evaluation index and the time performance evaluation index to obtain a space-time performance evaluation index; and setting parameters required for the index by imputing video image space contrast and time motion information on the basis of human vision perception features. The video image fusion performance evaluation method has the characteristics of accurate evaluation result and accordance with human vision subjective evaluation and canbe used for evaluating the performance of a video image fusion algorithm.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a video fusion performance evaluation method, which is used to comprehensively evaluate the performance of various fusion algorithms from two aspects of spatial information extraction and time consistency and stability. technical background [0002] Image fusion technology has been widely used in machine vision, digital cameras, target recognition and other fields. However, most of the current image fusion metrics are designed for static image fusion processing, while there are few studies on multi-sensor video image fusion. In practical applications such as security surveillance and target detection and recognition in battlefield environments, video images from multiple sensors often need to be fused. Video image fusion not only needs to meet the basic requirements of general image fusion in terms of spatial performance, that is, after fusion, each frame of video image should re...

AI Technical Summary

Problems solved by technology

However, this metric is a performance evaluation metric based on gradient information and is susceptible to noise

At the same time, this index did not consider the visual perception characteristics of the human eye during the design process, and the human eye is often the final receiver of video image fusion, resulting in a large difference between the evaluation results and the subjective evaluation results

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