@inproceedings{693ed53a07ed4421b6d1128310f4f135,
title = "Study on Scaling and Rotation invariance of IWSVR",
abstract = "inspire by human vision, imaging with space-variant resolution (IWSVR) has the characteristic of invariance to rotation and scaling, but the match between the center of the field of view (FOV) and target centroid is very strict. To quantify this invariance in IWSVR, a novel evaluation function is proposed in this paper. the proposed function when compared with two existing methods of scale-invariant feature transform (SIFT) and biaxial projection similarity analysis, shows reduced error within a five-pixel range of eccentricity. the results motivate the application of rotation and scale invariance property of IWSVR in different applications.",
keywords = "LPT, rotation, scaling, space-variant",
author = "Mingyuan Tang and Jie Cao and Huan Cui and Saad Rizvi and Qun Hao and Changhao Chu",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Symposium on Autonomous Systems, ISAS 2020 ; Conference date: 06-12-2020 Through 08-12-2020",
year = "2020",
month = dec,
day = "6",
doi = "10.1109/ISAS49493.2020.9378870",
language = "English",
series = "2020 International Symposium on Autonomous Systems, ISAS 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "192--195",
booktitle = "2020 International Symposium on Autonomous Systems, ISAS 2020",
address = "United States",
}