Image enhancing method based on self-adaptive block channel stretching

Abstract

The invention discloses an image enhancing method based on self-adaptive block channel stretching. The method mainly solves two important problems of image defogging and exposure adjustment in image enhancement. In the prior art, many methods provide solution schemes for the two problems, but the methods have the defect that a plurality of thresholds for image adjustment are needed, and this kind of methods requires user interaction operation and fail to process a plurality of images at one time; in addition, in the prior art, fogged images and dark light images are taken as two kinds of image enhancing problems which are solved respectively, and a unified framework is lacked. Aimed at the defects of the existing methods, statistic learning is carried out on various kinds of images in a real world, a self-adaptive threshold of problem image adjustment is obtained, the manual interaction operation of a user is reduced, and the processing efficiency is improved; in addition, stretching conversion is simultaneously carried out on a highlight channel and a shadow channel of an image block, and the problem images including the fogged images and the dark light images can be enhanced under the same framework.

Description

technical field [0001] The invention belongs to the field of image enhancement, and in particular relates to a method for selecting an adaptive threshold from an input image and performing defogging and exposure adjustment on the input image. Background technique [0002] Image enhancement refers to the process of sharpening or adjusting the exposure of images captured by digital cameras according to certain needs of users. Due to the limitation of the ability of photosensitive elements, digital cameras are not sensitive to dim light, and the contrast of pictures taken under poor light conditions is low, and local details are not prominent, resulting in poor subjective visual effects of images. Therefore, enhancing image contrast by software method is an indispensable digital image processing technology. The enhanced image has improved visibility and can better realize image-based applications such as video surveillance and image recognition. [0003] In recent years, with...

AI Technical Summary

Problems solved by technology

First of all, the existing methods solve the fog image and dark light image as two kinds of image enhancement problems separately, lacking a unified framework

Secondly, most of the existing methods perform enhanced saturation operations in the HSV color space, which is prone to problems such as color cast and distortion.

Thirdly, most of the existing image defogging methods use the image dark channel for processing. Since the pixel neighborhood size used to calculate the dark channel in the algorithm is a fixed value, the enhanced image is prone to significant halos.

To avoid the halo problem, the user must manually reduce the neighborhood size, which weakens the effect of image enhancement

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