Maximum likelihood estimation for disk image parameters
Image and Video Processing
2020-09-03 v2 Instrumentation and Methods for Astrophysics
Computer Vision and Pattern Recognition
Abstract
We present a novel technique for estimating disk parameters (the centre and the radius) from its 2D image. It is based on the maximal likelihood approach utilising both edge pixels coordinates and the image intensity gradients. We emphasise the following advantages of our likelihood model. It has closed-form formulae for parameter estimating, requiring less computational resources than iterative algorithms therefore. The likelihood model naturally distinguishes the outer and inner annulus edges. The proposed technique was evaluated on both synthetic and real data.
Cite
@article{arxiv.1907.10557,
title = {Maximum likelihood estimation for disk image parameters},
author = {Matwey V. Kornilov},
journal= {arXiv preprint arXiv:1907.10557},
year = {2020}
}
Comments
13 pages, 4 figures. in IEEE Signal Processing Letters