光学精密工程2023，Vol.31Issue(24)：3630-3639,10.DOI:10.37188/OPE.20233124.3630
多聚焦图像离焦模糊区域的SIFT特征提取
SIFT feature extraction method for the defocused blurred area of multi-focus images
摘要
Abstract
Conventional SIFT image feature extraction methods have difficulty in extracting features from the defocused blurred area of multi-focus images.As a result,common features between images are local and few,leading to poor accuracy in multi-focus image registration,which seriously affects the quality of subsequent image fusion and 3D reconstruction.Based on analyzing the uncertainty of feature extraction from the defocused blurred areas of images,a feature extraction method is proposed for the defocused blurred area of multi-focus images.First,features are extracted from the focused clear area of multi-focus images.Subsequently,the features in the corresponding defocused blurred area are extracted using optical flow tracking,thereby avoiding the uncertainty of directly extracting features from the defocused blurred ar-ea.Experimental results show that the proposed method displays good feature extraction ability and accura-cy in the defocused blurred area,significantly increasing the number of features matches.Feature extrac-tion error ranges between 0.03-0.39 pixels,which is better than the 0.21-1.71 pixels of existing meth-ods.This indicates a reduction in the uncertainty of feature extraction from the defocused blurred area,making it suitable for multi-focus image registration.关键词
多聚焦图像/尺度不变特征变换(SIFT)特征提取/离焦模糊区域/光流跟踪Key words
multi-focus images/Scale-Invariant Feature Transform(SIFT)feature extraction/defocused blurred area/optical flow tracking分类
计算机与自动化引用本文复制引用
夏晓华,赵倩,向华涛,秦绪芳,岳鹏举..多聚焦图像离焦模糊区域的SIFT特征提取[J].光学精密工程,2023,31(24):3630-3639,10.基金项目
国家自然科学基金资助项目(No.61901056) （No.61901056）
中国博士后科学基金资助项目(No.2020M683631XB) （No.2020M683631XB）
机器人技术与系统国家重点实验室开放基金资助项目(No.SKLRS-2021-KF-10) （No.SKLRS-2021-KF-10）
