Local low-visibility image enhancement method

An image enhancement and visibility technology, applied in the field of computer vision, can solve problems that have not been explored, achieve the effect of vivid and natural colors, eliminate artifacts, and compensate for the loss of saturation

Pending Publication Date: 2022-03-04
KUNMING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

Not only lighting should be considered and estimated in low-quality lighting image enhancemen

Method used

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  • Local low-visibility image enhancement method
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  • Local low-visibility image enhancement method

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Embodiment Construction

[0066] The present invention will be further described below on the basis of the description in conjunction with the accompanying drawings and specific embodiments.

[0067] Such as figure 1 As shown, a local low-visibility image enhancement method, first convert the image to HSV color space, separate the intensity component to enhance it, obtain the enhancement result, take the saturation component to compensate it, and use the proposed algorithm to compare it with the original saturation Adaptive fusion is performed to purify the area that needs to be purified in color, while other areas have no obvious changes; in the intensity component enhancement, the closed operation of limited expansion and small kernel is used to estimate the illumination intensity distribution and illumination edge distribution of the image respectively; Then, the intensity and edge of the two previously estimated illumination images are fused by using the guided filter; finally, the intensity component

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Abstract

The invention relates to a local low-visibility image enhancement method, and belongs to the technical field of computer vision. According to the method, firstly, the brightness of the image is balanced and visualized to obtain the high-visibility image, then the saturation of the high-visibility image is compensated to improve the color purity, and finally, the high-visibility image with bright color is obtained. According to the method, detail information of a dark area can be highly seen again, gradient consistency is greatly reserved, meanwhile, colors are brighter and more natural, and more importantly, compared with other algorithms of the same type, the algorithm has higher efficiency.

Description

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Claims

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Application Information

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Owner KUNMING UNIV OF SCI & TECH
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