New Centre/Surround Retinex-like Method for Low-Count Image Reconstruction

V. Antsiperov

2023

Abstract

The work is devoted to the issues of synthesizing a new method for low-count images reconstruction based on a realistic distortion model associated with quantum (Poisson) noise. The proposed approach to the synthesis of the reconstruction methods is based on the principles and concepts of statistical learning, understood as input learning (cf. adaptive smoothing). The synthesis is focused on a special representation of images using sample of counts of controlled size (sampling representation). Based on the specifics of this representation, a generative model of an ideal image is formulated, which is then concretized to a probabilistic parametric model in the form of a system of receptive fields. This model allows for a very simple procedure for estimating the count probability density, which in turn is an estimate of the normalized intensity of the registered radiation. With the help of the latter, similarly to the scheme of wavelet thresholding algorithms, a procedure for extracting contrast in the image is built. From the perception point of view, the contrast carries the main information about the reconstructed image, so such a procedure would provide a high image perception quality. The contrast extraction is carried out by comparing the number of counts in the centre and in the concentric surround of ON/OFF receptive fields and turns out to be very similar to wavelet thresholding.

Paper Citation

in Harvard Style

Antsiperov V. (2023). New Centre/Surround Retinex-like Method for Low-Count Image Reconstruction. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 517-528. DOI: 10.5220/0011792800003411

in Bibtex Style

@conference{icpram23,
author={V. Antsiperov},
title={New Centre/Surround Retinex-like Method for Low-Count Image Reconstruction},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={517-528},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011792800003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - New Centre/Surround Retinex-like Method for Low-Count Image Reconstruction
SN - 978-989-758-626-2
AU - Antsiperov V.
PY - 2023
SP - 517
EP - 528
DO - 10.5220/0011792800003411