A Fast Algorithm for the Demosaicing Problem Concerning the Bayer Pattern



Antonio Boccuto, Ivan Gerace*, Valentina Giorgetti, Matteo Rinaldi
Dipartimento di Matematica e Informatica, Laboratorio di Matematica Computazionale “Sauro Tulipani”, Università degli Studi di Perugia via Vanvitelli, 1 I-06123 Perugia, Italy

Abstract

Introduction:

In this paper, we deal with the demosaicing problem when the Bayer pattern is used. We propose a fast heuristic algorithm, consisting of three parts.

Methods:

In the first one, we initialize the green channel by means of an edge-directed and weighted average technique. In the second part, the red and blue channels are updated, thanks to an equality constraint on the second derivatives. The third part consists of a constant-hue-based interpolation.

Results:

We show experimentally how the proposed algorithm gives in mean better reconstructions than more computationally expensive algorithms.

Keywords: Demosaicing, Sparse data problem, Inverse problem, Edge-preserving image reconstruction, Local filtering, Bayer pattern.


Abstract Information


Identifiers and Pagination:

Year: 2018
Volume: 06
Publisher Item Identifier: EA-TOSIGPJ-2018-1

Article History:

Received Date: 29/6/2018
Revision Received Date: 6/12/2018
Acceptance Date: 18/12/2018
Electronic publication date: 31/12/2018
Collection year: 2018

© 2019 Boccuto et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Correspondence: Address correspondence to this author at the Dipartimento di Matematica e Informatica, Laboratorio di Matematica Computazionale “Sauro Tulipani”, Università degli Studi di Perugia via Vanvitelli, 1 I-06123 Perugia, Italy; Tel: +39 075 5855001; E-mail: ivan.gerace@unipg.it