On Image Registration and Subpixel Estimation

Fuente: arXiv
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1. Verfasser: Savari, Serap A.
Format: Preprint
Veröffentlicht: 2024
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author Savari, Serap A.
author_facet Savari, Serap A.
contents Image registration is a classical problem in machine vision which seeks methods to align discrete images of the same scene to subpixel accuracy in general situations. As with all estimation problems, the underlying difficulty is the partial information available about the ground truth. We consider a basic and idealized one-dimensional image registration problem motivated by questions about measurement and about quantization, and we demonstrate that the extent to which subinterval/subpixel inferences can be made in this setting depends on a type of complexity associated with the function of interest, the relationship between the function and the pixel size, and the number of distinct sampling count observations available.
format Preprint
id arxiv_https___arxiv_org_abs_2405_12927
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On Image Registration and Subpixel Estimation
Savari, Serap A.
Computer Vision and Pattern Recognition
Image registration is a classical problem in machine vision which seeks methods to align discrete images of the same scene to subpixel accuracy in general situations. As with all estimation problems, the underlying difficulty is the partial information available about the ground truth. We consider a basic and idealized one-dimensional image registration problem motivated by questions about measurement and about quantization, and we demonstrate that the extent to which subinterval/subpixel inferences can be made in this setting depends on a type of complexity associated with the function of interest, the relationship between the function and the pixel size, and the number of distinct sampling count observations available.
title On Image Registration and Subpixel Estimation
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2405.12927