低照度条件下基于优化自适应校正算法的数字图像增强研究  

Digital Image Enhancement Based on Optimized Adaptive Correction Algorithm Under Low Illumination

作　　者：付志荣 FU Zhi-rong(Fujian Vocational College of Art,Fuzhou 350100,China)

机构地区：[1]福建艺术职业学院,福建福州350100

出　　处：《长春师范大学学报》2021年第8期13-20,共8页Journal of Changchun Normal University

基　　金：中国纺织工业联合会职业教育教学改革研究项目“SPOC对高职服装与服饰设计专业学生自主学习促进作用的研究”(2020ZJJGLX020)。

摘　　要：针对低照度条件下传统图像增强算法存在的局部细节丢失、清晰度下降等问题,提出基于优化自适应校正的图像增强算法。利用小波阈值函数降低原始图像的噪声干扰,对经典伽马校正算法进行优化,将亮度分量区分块,并使滑动窗口具备中心位置自适应移动和半径可调功能;将原始图像的RGB模式转换为HSV模式以改善图像总体视觉舒适度;通过实时滑动调整窗口的位置及半径范围,使伽马值控制在最优范围,兼顾图像边缘和细节的增强,保留数字图像的局部信息。实验结果显示,本文算法的图像总体处理效果和局部细节增强效果良好,均值、信息熵和PSNR指标值优于传统算法。In order to solve the problems of local detail loss and definition degradation existing in traditional image enhancement algorithms under low illumination conditions,an image enhancement algorithm based on optimized adaptive correction was proposed.Firstly,the wavelet threshold function was used to reduce the noise interference of the original image,and the classical gamma correction algorithm was optimized.The brightness component was divided into blocks,and the sliding window had the function of center position adaptive movement and radius adjustable;the RGB mode of the original image was converted to HSV mode to improve the overall visual comfort of the image;the position and radius range of the window were adjusted by real-time sliding,so that the image quality was improved,the gamma value was controlled in the optimal range,the enhancement of image edge and detail was considered,and the local information of digital image was retained.The experimental results showed that the overall image processing effect and local detail enhancement effect of the proposed algorithm were good,and the average value,information entropy and PSNR index value were better than the traditional algorithm.

关 键 词：低照度 自适应校正 数字图像 滑动窗口 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]