基于Retinex先验引导的低光照图像快速增强方法  

Fast Enhancement Method for Low Light Images Guided by Retinex Prior

作　　者：何磊 易遵辉 谢永芳[2] 陈超洋[1] 卢明[1] HE Lei;YI Zun-Hui;XIE Yong-Fang;CHEN Chao-Yang;LU Ming(School of Information and Electrical Engineering,Hunan University of Science and Technology,Xiangtan 411100;School of Automation,Central South University,Changsha 410000)

机构地区：[1]湖南科技大学信息与电气工程学院,湘潭411100 [2]中南大学自动化学院,长沙410000

出　　处：《自动化学报》2024年第5期1035-1046,共12页Acta Automatica Sinica

基　　金：国家重点研发计划“政府间国际创新合作”重点专项(2019YFE0118700);国家自然科学基金(62222306,61973110,62203164);湖南省教育厅科学研究项目(22A0349,21B0499)资助。

摘　　要：低光照图像增强旨在提高在低光照环境下所采集图像的视觉质量.然而,现有的低光照图像增强方法难以在计算效率与增强性能之间达到很好的平衡,为此,提出一种基于Retinex先验引导的低光照图像快速增强方法,将Retinex模型与Gamma校正相结合,快速输出具有对比度高、视觉效果好和低噪声的图像.为获取具有良好光照的图像以引导确定与输入图像尺寸大小一致的Gamma校正图,提出基于Retinex模型的先验图像生成方法.针对所提先验图像生成方法在极低光照区域中存在颜色失真的问题,提出一种基于融合的Gamma校正图估计方法,采用反正切变换恢复极低光照区域的颜色和对比度,以提升Gamma校正图在极低光照区域的增强性能.为抑制输出图像的噪声,考虑到完全平滑的Gamma校正图不会平滑细节纹理的特点,提出基于域变换递归滤波的Gamma校正图优化方法,降低输出图像噪声的同时保持颜色和对比度.实验结果表明,所提方法不仅在主客观图像质量评价上优于现有大多数主流算法,而且在计算效率上具有十分显著的优势.Low light image enhancement aims to improve the visual quality of images captured in low light environment.However,existing low light image enhancement methods are difficult to achieve a good balance between computational efficiency and enhancement performance.Therefore,a fast low light image enhancement method guided by Retinex prior is proposed.The Retinex model is combined with Gamma correction to quickly output images with high contrast,good visual effects and low noise.To obtain images with good illumination and guide the determination of Gamma correction map with the same size as the input image,a prior image generation method based on Retinex model is proposed.To solve the problem of color distortion in extremely low illumination areas,a fusionbased Gamma correction map estimation method is proposed,which uses arctangent transform to restore the color and contrast of extremely low illumination areas to improve the enhancement performance of Gamma correction map in extremely low illumination areas.To suppress the noise of the output image,considering that the completely smooth Gamma correction map cannot smooth the detail texture,an optimization method of Gamma correction map based on domain transform recursive filtering is proposed,which can reduce the noise and preserve the color and contrast of the output image.The experimental results show that the proposed method not only outperforms most of the existing mainstream algorithms in subjective and objective image quality evaluation,but also has significant advantages in computational efficiency.

关 键 词：低光照图像增强 Gamma校正图 Retinex模型 噪声抑制 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]