A quantitative evaluation of fixed-pattern noise reduction methods in imaging systems

Pablo Meza, César San Martin, ESTEBAN MAURICIO VERA ROJAS, Sergio Torres

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Fixed-pattern noise is a common feature in several uncalibrated imaging systems, and it typically appears as striping and grid-like nonuniformity artifacts in hyperspectral and infrared cameras. In this work, we present a quantitative and comparative analysis of fixed-pattern noise reduction, or calibrating techniques, by using several image quality indexes. A special emphasis is made in demonstrating the correspondence between the reference-free (blind) image quality indexes and the typical reference-based metrics, specially when using online calibration procedures where reference data is not available. We evaluate the performance of several classic scene-based calibrating algorithms applied to: multispectral images with simulated striping noise; and infrared image sequences with simulated nonuniformity. The results show that most of the tested reference-free indexes are useful indicators for tracking some of the real degradation of the calibrated or even uncalibrated imagery, but they are far from perfect to match an error or similarity measure if the clean or reference data is available.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010, Proceedings
Pages285-294
Number of pages10
DOIs
StatePublished - 15 Dec 2010
Event15th Iberoamerican Congress on Pattern Recognition, CIARP 2010 - Sao Paulo, Brazil
Duration: 8 Nov 201011 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6419 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Iberoamerican Congress on Pattern Recognition, CIARP 2010
CountryBrazil
CitySao Paulo
Period8/11/1011/11/10

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