分区自适应伽马校正的非均匀光照图像增强

Adaptive Gamma Correction of Subregion for Non-Uniform Illumination Image Enhancement

针对非均匀光照图像在被增强处理中的过度增强问题,提出一种将光照分量和目标均值结合的自适应二维伽马函数的图像增强算法。首先,将图像转到HSV空间并提取V通道分量;对V通道分量进行并行的两种处理,一种是基于光照-反射模型,利用边缘保持性好的引导滤波器估计光照分量,另一种是将V通道分量IV的区域划分为亮区和暗区,并建立不同调整系数的目标均值函数;然后,再将光照分量和目标均值共同作为二维伽马函数的参数,对图像进行自适应伽马校正;再利用自适应直方图均衡对校正后图像进行进一步调整;最后,将调整后的V通道分量与原图像的H、S通道分量合并后转换回RGB色彩空间并输出。对DICM、LIME两个数据集中的非均匀光照图像进行增强处理的实验结果表明:相比其他4种典型增强算法,所提算法可以将原图像的信息熵(entropy)、平均梯度(MG)、信噪比(SNR)分别平均提高10.6%、97.5%、77.8%,平均运行时间为0.32 s;经所提算法增强处理后,图像中光照更自然、细节更清晰、色彩保持性更好。所提图像增强算法可以将非均匀光照图像处理为色彩真实自然、亮度均匀、细节清晰的图像,视觉效果好,并有效避免图像过度增强问题。且所提算法处理快速,有利于机器视觉等研究工作的开展。

This paper proposes an improved adaptive twodimensional gamma correction method based on the illumination component and target mean value to address the issue of overenhancement in nonuniformly illuminated images.The process begins with the conversion of images to the HSV space,from which the Vchannel image is extracted for processing.Utilizing the illuminationreflection model,the illumination component is estimated through a guided image filter with good edge retention.Concurrently,the Vchannel image region is segmented into bright and dark regions,and a target mean function with varying adjustment coefficients is established.The illumination component and adaptive target mean value are used to act on the gamma function for twodimensional gamma correction,and histogram equalization is subsequently performed.The final output is obtained by merging Vchannel component with the H and S channels and converting it back to the RGB space.Experimental evaluations on DICM and LIME datasets reveal that in comparison to four typical enhancement algorithms,the proposed algorithm achieves an average increase of 10.6%in information entropy,97.5%in mean gradient(MG),and 77.8%in signaltonoise ratio(SNR),with an average processing time of 0.32 s.These enhancements significantly improve the visual quality of images,making them more suitable for machine vision research.The proposed algorithm offers advantages in terms of high realtime performance and simplicity and produces output images with more natural colors, uniform brightness, clearer details, and an overall enhanced visual effect.