基于RGB颜色空间椭球模型的去雾算法研究  

Dehazing Algorithm Based on RGB Color Space Ellipsoid Model

作　　者：焦子航 范之国[1] 钱立进 庄子杰 Jiao Zihang;Fan Zhiguo;Qian Lijin;Zhuang Zijie(School of Computer Science and Information Engineering,Hefei University of Technology,Hefei,Anhui 230601,China)

机构地区：[1]合肥工业大学计算机与信息学院,安徽合肥230601

出　　处：《激光与光电子学进展》2022年第8期271-278,共8页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61571177);安徽省高等学校自然科学研究项目(KJ2018JD12)。

摘　　要：雾霾环境下拍摄的图像总是存在模糊不清的问题,为了更好地复原雾天图像,提出了一种基于RGB颜色空间椭球模型的传输函数估计算法。首先,将雾天图像的某一邻域内的像素灰度值映射至RGB颜色空间,并通过椭球模型拟合像素灰度值的聚集状态;然后,将椭球中所有向量向大气光向量上投影,以此估计每一像素位置的传输函数;最后,对传输函数进行优化,并结合大气光向量估计实现图像去雾。实验结果表明,所提基于RGB颜色空间椭球模型的传输函数估计算法可以有效地复原雾天图像。The images captured in a hazy environment are always prone to blurring.To restore the hazy images,a transmission function estimation algorithm based on the RGB color space ellipsoid model is proposed.First,the gray values of pixels in a neighborhood of a hazy image were mapped to RGB color space,and the aggregation state of pixel gray values were fitted by an ellipsoid model.Furthermore,all vectors in the ellipsoid were projected onto the atmospheric light vector to estimate the transmission function for each pixel.Finally,the transmission function is optimized and combined with atmospheric light vector estimation to restore the hazy images.Experimental results indicate that the proposed transmission function estimation algorithm,which is based on the RGB color space ellipsoid model,can effectively restore the hazy images.

关 键 词：成像系统 图像去雾 RGB颜色空间 椭球模型 传输函数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]