Self-adaptive low-illuminance or non-uniform-brightness image enhancement method

Abstract

The invention relates to a self-adaptive low-illuminance or non-uniform-brightness image enhancement method. The method comprises the following steps: 1), preprocessing is performed on a low-illuminance and non-uniform-brightness image, wherein the preprocessing includes brightness preprocessing on the low-illuminance and non-uniform-brightness image, and edge enhancement is performed on the image after brightness preprocessing, so that the preprocessed image is obtained; 2), region segmentation is performed according to the brightness of the preprocessed image, corresponding mapping functions are selected according to the different characteristics of all segmented regions and corresponding self-adaptive brightness enhancement is performed; 3), saturation enhancement processing is performed on the image subjected to self-adaptive brightness enhancement segment by segment through the change characteristics of initial saturation and brightness. According to the invention, the steps are adopted to process the image, therefore, the color saturation of the image is improved, the image is enabled to be bright in color and have a better visual effect. The self-adaptive image enhancement method can be widely popularized in the fields of biomedicine, real-time monitoring, satellite remote sensing and the like.

Description

technical field [0001] The invention relates to an image enhancement method, in particular to an adaptive image enhancement method for images with low illumination or uneven brightness. Background technique [0002] In image processing applications, when the illumination of the ambient light source is low or uneven, image details are often unclear, information is lost, or image quality is severely degraded. At this time, image enhancement technology is required to improve image quality for subsequent image processing. Image enhancement technology refers to the application of a given image, purposefully emphasizing the overall or local characteristics of the image, making the original unclear image clear, or emphasizing some interesting features while suppressing uninteresting features, expanding The difference between the characteristics of different objects in the image can improve the image quality, enrich the amount of information, strengthen the image interpretation and...

AI Technical Summary

Problems solved by technology

[0008] The disadvantages of the above method are as follows: ①This technology uses fixed brightness segmentation parameters, so it is not suitable for images with extremely uneven brightness distribution and large brightness fluctuations; ②This technology involves convolution when calculating brightness distribution information Calculation, the amount of calculation is large; ③It can enhance the brightness of the image, but it cannot effectively maintain the vividness of the color, which affects the visual effect of the image

[0009] To sum up, there are still problems such as insufficient self-adaptability, large amount of calculation, and insufficient color in the image enhancement method using common adaptive parameter adjustment.

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