MIHS: A Multiobjective Pan-sharpening Method for Remote Sensing Images

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6 Scopus citations

Abstract

Pan-sharpening aims to integrate the spatial details of high resolution panchromatic image (PAN) with the spectral information of the corresponding low resolution multispectral image (MS) to produce high resolution multispectral image, which is a challenge real-world task. In this paper, we propose a novel pan-sharpening method, called multiobjective Intensity-Hue-Saturation (MIHS) transformation, which combines adaptive Intensity-Hue-Saturation transformation and evolutionary multi-objective optimization techniques for remote sensing images. The basic idea is to convert the pan-sharpening problem into a mutiobjective optimization problem and deal with it by an multiobjective evolutionary algorithm. The proposed method is applied to two Quick-bird images. Experimental results demonstrate that the proposed method does markedly improve the pan-sharpening performance compared to the state-of-the-art methods and an evolutionary method with single objective in terms of both subjective visual effects and objective quality metrics.

Original languageEnglish
Title of host publication2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1068-1073
Number of pages6
ISBN (Electronic)9781728121536
DOIs
StatePublished - Jun 2019
Event2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand
Duration: 10 Jun 201913 Jun 2019

Publication series

Name2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

Conference

Conference2019 IEEE Congress on Evolutionary Computation, CEC 2019
Country/TerritoryNew Zealand
CityWellington
Period10/06/1913/06/19

Keywords

  • Intensity-Hue-Saturation
  • Multiobjective optimization
  • Multispectral images
  • Pan-sharpening
  • Panchromatic image

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