A Rudin-Osher-Fatemi model-based pansharpening approach using RKHS and AHF representation

Jun Liu; Liang Jian Deng; Faming Fang; Tieyong Zeng

doi:10.4208/eajam.150818.061118

A Rudin-Osher-Fatemi model-based pansharpening approach using RKHS and AHF representation

Jun Liu
, Liang Jian Deng^*
, Faming Fang
, Tieyong Zeng

^*Corresponding author for this work

School of Computer Science and Technology

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

A pansharpening method based on the Rudin-Osher-Fatemi model and using a reproducing kernel Hilbert space along with the approximated Heaviside function is developed. The corresponding minimisation problem is solved by the alternating direction method of multipliers. Numerous numerical experiments with Pléiades and IKONOS satellite datasets demonstrate the efficiency of the method in preserving spectral and spatial information and show its superiority to other approaches.

Original language	English
Pages (from-to)	13-27
Number of pages	15
Journal	East Asian Journal on Applied Mathematics
Volume	9
Issue number	1
DOIs	https://doi.org/10.4208/eajam.150818.061118
State	Published - Feb 2019

Keywords

Approximated Heaviside function
Multi-spectral image
Pansharpening
Reproducing kernel Hilbert space

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10.4208/eajam.150818.061118

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abstract = "A pansharpening method based on the Rudin-Osher-Fatemi model and using a reproducing kernel Hilbert space along with the approximated Heaviside function is developed. The corresponding minimisation problem is solved by the alternating direction method of multipliers. Numerous numerical experiments with Pl{\'e}iades and IKONOS satellite datasets demonstrate the efficiency of the method in preserving spectral and spatial information and show its superiority to other approaches.",

keywords = "Approximated Heaviside function, Multi-spectral image, Pansharpening, Reproducing kernel Hilbert space",

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PY - 2019/2

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AB - A pansharpening method based on the Rudin-Osher-Fatemi model and using a reproducing kernel Hilbert space along with the approximated Heaviside function is developed. The corresponding minimisation problem is solved by the alternating direction method of multipliers. Numerous numerical experiments with Pléiades and IKONOS satellite datasets demonstrate the efficiency of the method in preserving spectral and spatial information and show its superiority to other approaches.

KW - Approximated Heaviside function

KW - Multi-spectral image

KW - Pansharpening

KW - Reproducing kernel Hilbert space

UR - https://www.scopus.com/pages/publications/85074305613

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ER -

A Rudin-Osher-Fatemi model-based pansharpening approach using RKHS and AHF representation

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Keywords

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