Color image contrast enhancement method based on self-adaptive gamma correction

Abstract

The invention discloses a color image contrast enhancement method based on self-adaptive gamma correction. The method comprises the following steps: 1, carrying out lightness image calculation on an input image to be enhanced; 2, calculating a probability density function and a weight distribution function by using the lightness image; 3, calculating a cumulative distribution function of the weight distribution function; 4, constructing a self-adaptive gamma parameter, and performing self-adaptive gamma correction on the lightness image; and 5, converting the corrected image back to the RGB color space to obtain an enhanced result image. According to the invention, the enhancement of the contrast of the image can be adaptive to the pixel intensity, the enhanced image is more natural, and the local contrast of the image can be enhanced.

Description

technical field [0001] The invention relates to an image contrast enhancement method, in particular to an adaptive gamma correction color image contrast enhancement method. Background technique [0002] Unideal shooting environment, such as rainy weather, insufficient indoor light, etc., will lead to a decrease in the contrast of the images captured by people, and some details of the scenes and objects in the images cannot be clearly presented, resulting in poor visual effects. If such images are directly applied to vision-based applications such as target detection and target tracking, the detection or tracking results will be inaccurate. [0003] Image contrast enhancement methods mainly include transformation-based methods and histogram-based methods. The transformation-based method adjusts the pixel intensity of the output image by doing some mathematical transformation on the image, such as exponential transformation, so as to achieve the purpose of improving the image...

AI Technical Summary

Problems solved by technology

The histogram-based method improves the image contrast by adjusting the histogram distribution of the original image. However, this kind of method adjusts the image contrast as a whole, which often brings some unnatural artifacts.

Shih-Chia Huang et al proposed a method based on adaptive gamma correction contrast enhancement (Shih-Chia Huang, Fan-Chieh Cheng, Yi-Sheng Chiu, Efficient contrast enhancement using adaptive gamma correction with weighting distribution, IEEE Transactions on Image Processing, vol.22, no.3, pp.1032-1041, 2013), combining the transformation-based method and the histogram-based method to perform adaptive gamma correction on the original image to enhance image contrast, but bright areas often appear The phenomenon of over-enhancement, and ignores the enhancement of local area contrast

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