Improved polar complex exponential transform for robust local image description

被引:1
|
作者
Yang, Zhanlong [1 ]
Yang, Linzhi [1 ]
Chen, Geng [2 ]
Yap, Pew-Thian [3 ,4 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian, Peoples R China
[2] Northwestern Polytech Univ, Sch Comp Sci & Engn, Natl Engn Lab Integrated Aerosp Ground Ocean Big D, Xian, Peoples R China
[3] Univ N Carolina, Dept Radiol, Chapel Hill, NC USA
[4] Univ N Carolina, Biomed Res Imaging Ctr BRIC, Chapel Hill, NC USA
基金
中国国家自然科学基金;
关键词
Image description; Local image descriptor; Polar complex exponential transform; Phase information; STEREO; SCALE;
D O I
10.1016/j.patcog.2023.109786
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image description via robust local descriptors plays a vital role in a large number of image representation and matching applications. In this paper, we propose a novel distinctive local image descriptor that is based on the phase and amplitude information of Polar Complex Exponential Transform (PCET). The proposed descriptor, called IPCET (Improved PCET), is robust to the common photometric transformations (e.g., illumination, noise, JPEG compression, and blur) and geometric transformations (e.g., scaling, rotation, translation, and significant affine distortion). We perform extensive experiments to compare our IPCET descriptor with six most cutting-edge region descriptors (i.e., SIFT, Zernike Moment, GLOH, PCA-SIFT, SURF, and ORB). Experimental results demonstrate that our IPCET descriptor outperforms cutting-edge moment-based descriptors.
引用
收藏
页数:14
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