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Proceedings Paper

Reconstruction method of compressed sensing for remote sensing images cooperating with energy compensation
Author(s): Jinping He; Ningjuan Ruan; Haibo Zhao; Yuchen Liu
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Paper Abstract

Remote sensing features are varied and complicated. There is no comprehensive coverage dictionary for reconstruction. The reconstruction precision is not guaranteed. Aiming at the above problems, a novel reconstruction method with multiple compressed sensing data based on energy compensation is proposed in this paper. The multiple measured data and multiple coding matrices compose the reconstruction equation. It is locally solved through the Orthogonal Matching Pursuit (OMP) algorithm. Then the initial reconstruction image is obtained. Further assuming the local image patches have the same compensation gray value, the mathematical model of compensation value is constructed by minimizing the error of multiple estimated measured values and actual measured values. After solving the minimization, the compensation values are added to the initial reconstruction image. Then the final energy compensation image is obtained. The experiments prove that the energy compensation method is superior to those without compensation. Our method is more suitable for remote sensing features.

Paper Details

Date Published: 21 October 2016
PDF: 11 pages
Proc. SPIE 9988, Electro-Optical Remote Sensing X, 99880A (21 October 2016); doi: 10.1117/12.2241340
Show Author Affiliations
Jinping He, Beijing Institute of Space Mechanics and Electricity (China)
Ningjuan Ruan, Beijing Institute of Space Mechanics and Electricity (China)
Haibo Zhao, Beijing Institute of Space Mechanics and Electricity (China)
Yuchen Liu, Beijing Institute of Space Mechanics and Electricity (China)


Published in SPIE Proceedings Vol. 9988:
Electro-Optical Remote Sensing X
Gary Kamerman; Ove Steinvall, Editor(s)

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