Adaptive infrared image enhancement method based on visual contrast resolution

Abstract

The invention requests to protect an adaptive infrared image enhancement method based on a visual contrast resolution model. Based on the fact that the resolution of human eye vision differs obviouslyin different grayscale ranges, the grayscale value of an image is divided into three stages which correspond to the dark vision, the middle vision and the bright vision of the human eyes respectively, and then, corresponding human eye visual contrast resolution models are established. According to the obtained grayscale difference between an image target and background and the models, the image target is adaptively mapped to a human eye sensitive area and the image background is mapped to a human eye insensitive area, and simulation and verification are carried out through an actual infraredimage. The method of the invention has the advantages of simple implementation process, small amount of computation and obvious image enhancement effect, and has application and popularization values.

Description

technical field [0001] The invention belongs to the technical field of image enhancement, in particular to an adaptive infrared image enhancement process based on a visual bionic human vision contrast resolution model. Background technique [0002] According to the grayscale statistical characteristics of infrared images, most of the grayscales of infrared images are concentrated in the adjacent grayscale range, and the sense of layering is poor, which is not conducive to the human eye to find the target. If it is mainly distributed in low grayscales, the image overall It is dark, so it needs to be enhanced. Traditional infrared enhancement methods, such as histogram equalization, grayscale transformation, and local contrast enhancement, etc. enhance the image contrast, but also amplify the background noise, the image layering is not strong, and the visual effect is poor. Since the image is finally observed by the human eye, the unique visual characteristics of the human ey...

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at processing infrared images in the prior art, a large number of traditional algorithms are not combined with visual bionic knowledge, which cannot make infrared images have good visual effects, and a small number of image enhancement algorithms combined with visual bionics do not combine the characteristics of infrared images with bionic models. Precisely, a human visual contrast resolution model based on three visual conditions is proposed. This model combines the characteristics of the gray distribution of infrared images, fully considers the ability of human eyes to distinguish different visual states of infrared image gray, and then adapts Map infrared image targets and backgrounds to achieve enhanced image effects

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