Super resolution of multispectral images using TV image models

Miguel Vega*, Javier Mateos, Rafael Molina, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this paper we propose a novel algorithm for the pansharpening of multispectral images based on the use of a Total Variation (TV) image prior. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images, and uses the sensor characteristics to model the observation process of both panchromatic and multispectral images. Using real and synthetic data, the pansharpened multispectral images are compared with the images obtained by other pansharpening methods and their quality is assessed both qualitatively and quantitatively.

Original languageEnglish (US)
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 12th International Conference, KES 2008, Proceedings
PublisherSpringer Verlag
Pages408-415
Number of pages8
EditionPART 3
ISBN (Print)3540855661, 9783540855668
DOIs
StatePublished - 2008
Event12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008 - Zagreb, Croatia
Duration: Sep 3 2008Sep 5 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume5179 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2008
CountryCroatia
CityZagreb
Period9/3/089/5/08

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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