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.
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 (Presented at SPIE Security + Defence: September 26, 2016; Published: 21 October 2016); https://doi.org/10.1117/12.2241340.
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