Self-adaptive image enhancement method and device based on image gray level

Abstract

The invention provides a self-adaptive image enhancement method and device based on image gray levels, and relates to the technical field of image processing, and the technical scheme comprises the steps: obtaining the occurrence frequency of each gray level of a to-be-processed image, and storing the gray levels, of which the gray levels exceed a preset gray level threshold value, in a preset array; reading the gray values according to the serial numbers of the preset array in sequence, and redefining according to the corresponding relationship between the gray values and the serial numbers to obtain new gray values; and performing adaptive enhancement processing on the to-be-processed image according to the new gray value. According to the scheme, the image can be enhanced in a self-adaptive mode, the image brightness is basically unchanged, details of the excessively dark part of the image can be richer, the excessively bright part of the image can be restrained, and therefore the fidelity effect is achieved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a method for adaptive image enhancement based on image gray levels, a device for adaptive image enhancement based on image gray levels, a computer device and a non-temporary computer readable storage medium. Background technique [0002] Image enhancement technology is an image processing method that makes an unclear image clear or emphasizes some interesting features, suppresses uninteresting features, improves image quality, enriches information, and enhances image interpretation and recognition effects. [0003] At present, among the image enhancement techniques, the classic histogram enhancement technique is the most widely used, and its calculation is simple, fast, and the effect is obvious. However, the image enhanced by the classic histogram enhancement technology tends to be over-enhanced and over-brightened, and the noise is also significantly amplified...

AI Technical Summary

Problems solved by technology

However, the image enhanced by the classic histogram enhancement technology is prone to over-enhancement and over-brightness, and the noise is also significantly amplified, and the image details are seriously lost.

Therefore, the classical histogram enhancement technique is not suitable for electronic external display devices (such as flat panel displays, liquid crystal displays, etc.)

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