基于改进引导滤波器的多光谱去马赛克方法  

Multispectral demosaicing method based on an improved guided filter

作　　者：齐海超 宋延嵩[1,2] 张博 梁宗林[1] 闫纲琦 薛佳音 张轶群 任斌 xQI Hai-chao;SONG Yan-song;ZHANG Bo;LIANG Zong-lin;YAN Gang-qi;XUE Jia-yin;ZHANG Yi-qun;REN Bin(Institute of Space Photoelectric Technology,School of Opto-Electronic Engineering,Changchun University of Science and Technology,Changchun 130022,China;Peng Cheng Laboratory,Shenzhen 518052,China;Xi’an Branch of China Academy of Space Technology,Xi’an 710212,China)

机构地区：[1]长春理工大学光电工程学院空间光电技术研究所,长春130022 [2]鹏城实验室,深圳518052 [3]中国空间技术研究院西安分院,西安710212

出　　处：《中国光学（中英文）》2023年第5期1056-1065,共10页Chinese Optics

基　　金：国家重点研发计划资助项目(No.2022YFB3902500);国家自然科学基金资助项目(No.U2141231);吉林省自然科学基金(No.202002036JC);鹏城实验室重大攻关项目(No.PCL2021A03-1)。

摘　　要：为了更好地保留多光谱去马赛克图像中的高频信息,本文提出了一种基于改进引导滤波器的多光谱图像去马赛克方法。首先,基于自回归模型对相邻像素点间的强相关性进行建模,在每个像素处渐进估计其模型参数,通过最小化局部窗口内的估计误差,得到最优估计值来插值采样密集波段G,并生成高质量的引导图像;然后,引入加窗固有变分系数到惩罚因子中,得到具有边缘感知能力的加权引导滤波器并重建其余稀疏采样波段。最后,使用CAVE数据集和TokyoTech数据集进行仿真。实验结果表明:相较于主流的5波段多光谱图像去马赛克方法,本方法重建图像的峰值信噪比和结构相似度在CAVE数据集和TokyoTech数据集上分别提高了3.40%,2.02%,1.34%,0.30%和6.11%,5.95%,2.28%,1.42%,且更好地保留了原始图像的局部结构和颜色信息,减少了边缘伪影和噪声现象的出现。In order to better preserve high-frequency information in demosaicing multispectral images,we propose a new demosaicing method for multispectral images based on an improved guided filter.Firstly,the strong correlation between adjacent pixels based on the autoregressive model is constructed,gradually estimates the model parameters at each pixel,and the optimal estimation value is obtained by minimizing the estimation error in the local window,interpolates the sampling dense band G,and generates high-quality guide images.The windowed intrinsic variation coefficient is then introduced into the penalty factor to obtain a weighted guide filter with edge sensing ability and to reconstruct the remaining sparse sampling bands.Fi-nally,the CAVE dataset and the TokyoTech dataset are used for simulation.The experimental results show that compared with the mainstream five-band multispectral image demosaicing method,the peak signal-to-noise ratio and structure similarity of the reconstructed image in the CAVE dataset and the TokyoTech data-set are improved by 3.40%,2.02%,1.34%,0.30%and 6.11%,5.95%,2.28%,1.42%,respectively.The local structure and color information of the original image are also better preserved,and the edge artifacts and noise are reduced.

关 键 词：计算成像 多光谱滤光片阵列 多光谱去马赛克方法 自回归模型 加权引导滤波器 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]