Presentation + Paper
21 October 2016 Reconstruction method of compressed sensing for remote sensing images cooperating with energy compensation
Author Affiliations +
Proceedings Volume 9988, Electro-Optical Remote Sensing X; 99880A (2016) https://doi.org/10.1117/12.2241340
Event: SPIE Security + Defence, 2016, Edinburgh, United Kingdom
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.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jinping He, Ningjuan Ruan, Haibo Zhao, and Yuchen Liu "Reconstruction method of compressed sensing for remote sensing images cooperating with energy compensation", Proc. SPIE 9988, Electro-Optical Remote Sensing X, 99880A (21 October 2016); https://doi.org/10.1117/12.2241340
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KEYWORDS
Associative arrays

Sensors

Reconstruction algorithms

Image resolution

Remote sensing

Compressed sensing

Chemical species

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