Method and device for performing histogram equalization processing on images

Abstract

Embodiments of the present invention provide a method and device for performing histogram equalization processing on an image. The method mainly includes: calculating the distance between each pixel point in the image and the central pixel point; calculating the histogram statistical weight of each pixel point in the image according to the distance between each pixel point in the image and the central pixel point; Based on the statistical weight of the histogram of each pixel in the image, carry out the weighted gray histogram statistics of each gray level of the image; according to the statistical results of the weighted gray histogram of each gray level of the image, perform the histogram of the image Balanced processing. In the embodiment of the present invention, by using the spatial distribution position of the pixels in the image, different statistical weights are used for each pixel, so that the processed image can highlight the area of ​​people's visual concern (that is, the central area of ​​the image), and realize the accuracy of the image. Differential contrast enhancement processing is performed on different regions, which effectively enhances the contrast of people's visually concerned regions in the image.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method and device for performing histogram equalization processing on images. Background technique [0002] Histogram equalization is a commonly used image enhancement method, and histogram statistics is an important step in histogram equalization. The process of histogram statistics mainly includes: according to the gray level of the input image, the whole image with the same gray value The number of pixels is accumulated one by one, and the histogram statistical result obtained after accumulation is the gray distribution of the input image, which objectively reflects the contrast of the input image. Histogram equalization calculates the ratio of the number of pixels of each effective gray value to the total number of pixels based on the statistical results of the above histogram, and then maps the gray range of the input image to improve the overall contrast ...

AI Technical Summary

Problems solved by technology

[0003] At present, the existing histogram equalization schemes are aimed at the entire image to improve the overall contrast of the image. However, for real-time image acquisition and processing systems such as infrared or low-light night vision devices, the detail areas that human vision is most concerned about are generally in the entire image. The center position of the image, the above-mentioned existing histogram equalization scheme cannot realize the contrast enhancement processing of different regions of the image.

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