Mutual-structure weighted guided image filtering for depth map restoration  

作　　者：LIU Zijian SONG Jian CHEN Quanmin XU Jiangtao 

机构地区：[1]Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology,School of Microelectronics,Tianjin University,Tianjin 300072,China [2]Spikesee Technology Co.,Ltd.,Beijing 100083,China

出　　处：《Optoelectronics Letters》2025年第1期51-56,共6页光电子快报(英文版)

基　　金：supported by the National Key Research and Development Program of China (No.2019YFB2204302)。

摘　　要：Although guided image filtering(GIF) is known for preserving edges and fast computation,it may produce inaccurate outputs in depth map restoration.In this paper,a novel confidence-weighted GIF called mutual-structure weighted GIF(MSWGIF) is proposed,which replaces the mean filtering strategy in GIF during handling overlapping windows.The confidence value is composed of a depth term and a mutual-structure term,where the depth term is utilized to protect the edges of the output,and the mutual-structure term helps to select accurate windows during the structure characteristics of the guidance image are transferred to the output.Experimental results show that MSWGIF reduces the root mean square error(RMSE) by an average of 12.37%,and the average growth rate of correlation(CORR) is 0.07% on average.Additionally,the average growth rate of structure similarity index measure(SSIM) is 0.34%.

关 键 词：FILTERING IMAGE mutual 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN713[自动化与计算机技术—计算机科学与技术]