An adaptive image enhancement method and terminal

By converting a color image from RGB space to YUV space, generating a histogram, and calculating the slope of the brightness segment, the problem of low adaptability in existing technologies is solved, achieving an adaptive image enhancement effect that is suitable for brightness enhancement of color images.

CN116563180BActive Publication Date: 2026-06-30FUJIAN XINTU PHOTOELECTRIC CO LTD
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Patent Information

Application Number
CN202310525842.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2018-12-06
Publication Date
2026-06-30
Estimated Expiration
2038-12-06

AI Technical Summary

Technical Problem

Existing histogram-based image enhancement methods have low adaptability, poor enhancement effects, and cannot effectively highlight image details.

Method used

By converting a color image from RGB space to YUV space, obtaining brightness information to generate a histogram, determining the pixel number threshold and its corresponding preset slope, calculating the slope of each brightness segment using linear interpolation or curve fitting methods, determining the image transformation relationship based on the slope, and performing normalization processing, the image is finally converted from YUV space back to RGB space.

Benefits of technology

It achieves adaptive image enhancement, highlighting image details and avoiding the problems of images being too dark or too bright. The enhancement effect is good and it is suitable for brightness enhancement of color images.

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Abstract

This invention provides an adaptive image enhancement method and terminal. It determines a threshold number of pixels corresponding to brightness in the image to be enhanced based on a histogram, and maps this threshold to a preset slope. The slope of each segment in the histogram is calculated based on the threshold and the preset slope. The transformation relationship for image enhancement is then calculated based on the slope of each segment. The image brightness is then transformed according to this transformation relationship. This method does not simply scale a few grayscale intervals directly based on preset parameters. Instead, it first determines the slope of each segment based on the number of segments in the histogram, and then determines the transformation relationship for each segment based on the slope of each segment. This results in an image with synchronized brightness enhancement for each segment. The method exhibits strong adaptability and good enhancement effect, achieving the goal of enhancing image contrast and highlighting image details, thus providing an effective guarantee for subsequent image observation, processing, and recognition.
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