Aiming at these disadvantages like lack of details, poor contrast and blurry edges of infrared images reconstructed by traditional controllable microscanning super-resolution reconstruction(SRR), this paper proposes a novel algorithm, which samples multiple low-resolution images(LRIs) by uncontrollable microscanning, and then uses LRIs as chromosomes of genetic algorithm(GA). After several generations of evolution, optimal LRIs are got to reconstruct the high-resolution image(HRI). The experimental results show that the average gradient of the image reconstructed by the proposed algorithm is increased to 1.5 times of that of the traditional SRR algorithm, and the amounts of information, the contrast and the visual effect of the reconstructed image are improved.
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机译:AMT-2019-95: A GPS water vapor tomography method based on a genetic algorithm, by Fei Yang, Jiming Guo, Junbo Shi, Xiaolin Meng, Yinzhi Zhao, Lv Zhou, and Di Zhang
机译:Etude de la Distribution de la sensibilite d'UN systeme Circulaire multi-Electrodes en Vue de la Reconstruction d'Images d'Impedance Bio-Electrique(多电极圆形系统灵敏度分布的研究)