基于单应性扩散约束的二步网格优化视差图像对齐  

Parallax Image Alignment With Two-stage Mesh Optimization Based on Homography Diffusion Constraints

作　　者：陈殷齐 郑慧诚[1,3,4] 严志伟 林峻宇 CHEN Yin-Qi;ZHENG Hui-Cheng;YAN Zhi-Wei;LIN Jun-Yu(School of Computer Science and Engineering,Sun Yat-sen University,Guangzhou 510006;New Display Technology and Equipment Research Center,Jihua Laboratory,Foshan,528000;Key Laboratory of Machine Intelligence and Advanced Computing,Ministry of Education,Guangzhou 510006;Guangdong Province Key Laboratory of Information Security Technology,Guangzhou 510006;School of Computer Science,Fudan University,Shanghai 200438)

机构地区：[1]中山大学计算机学院,广州510006 [2]季华实验室新型显示技术与装备研究中心,佛山528000 [3]机器智能与先进计算教育部重点实验室,广州510006 [4]广东省信息安全技术重点实验室,广州510006 [5]复旦大学计算机科学技术学院,上海200438

出　　处：《自动化学报》2024年第6期1129-1142,共14页Acta Automatica Sinica

基　　金：国家自然科学基金(61976231);广东省基础与应用基础研究基金(2019A1515011869);广州市科技计划项目(201803030029)资助。

摘　　要：目前,在带有视差场景的图像对齐中,主要难点在某些无法找到足够匹配特征的区域,这些区域称为匹配特征缺失区域.现有算法往往忽略匹配特征缺失区域的对齐建模,而只将有足够匹配特征区域中的部分单应变换系数(如相似性变换系数)传递给匹配特征缺失区域,或者采用将匹配特征缺失区域转化为有足够匹配特征区域的间接方式,因此对齐效果仍不理想.在客观事实上,位于相同平面的区域应该拥有相同的完整单应变换而非部分变换参数.由此出发,利用单应变换系数扩散的思想设计了一个二步网格优化的图像对齐算法,简称单应扩散变换(Homography diffusion warping,HDW)算法.该方法在第一步网格优化时获得有足够匹配特征区域的单应变换,再基于提出的单应性扩散约束将这些单应变换系数扩散到邻域网格,进行第二步网格优化,在保证优化任务简洁高效的前提下实现单应变换系数的传播与图像对齐.相较于现有的针对视差场景图像对齐算法,所提方法在各项指标上都获得了更好的效果.At present,the main difficulty in the image alignment with parallax scene is in the areas that cannot find sufficient matching features.We call these areas featureless regions.Cutting-edge research on parallax image alignment neglects modeling of regions without matching features.Indirect methods such as transferring partial homography of regions with matching features to featureless regions or transforming featureless regions to regions with matching features have been popularly used,which,however,do not guarantee satisfactory results.In fact,image regions belonging to the same plane should possess the same homography.In this paper,a two-stage mesh optimization algorithm,homography diffusion warping(HDW),is designed by homography diffusion.In the first stage,homography coefficients of mesh cells in the image regions with matching features are obtained.Then we propagate these homography coefficients to adjacent cells to form homography diffusion constraints,and perform the second stage optimization of the mesh by enforcing the constraints on the premise of ensuring the simplicity and efficiency of the optimization task.Compared with existing image alignment algorithms,the method proposed in this paper achieves better results on all metrics.

关 键 词：图像对齐 视差场景 网格优化 匹配特征缺失区域 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]