A Super Resolution Algorithm for Atmospherically Degraded Images Using Lucky Regions and MAP-uHMT

Zhiying Wen, Feng Li, D. Fraser, A. Lambert, X. Jia
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引用次数: 2

Abstract

This paper demonstrates the possibility of super resolved image reconstruction for images affected by atmospheric turbulence. A lucky region method using bicoherence is proposed to select image tiles with superior quality or “lucky image regions” from a large number of short exposure images. A super resolved image is then reconstructed by a MAP method based on a Universal Hidden Markov Tree model from the lucky regions. Performance is demonstrated with real data.
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基于幸运区域和MAP-uHMT的大气退化图像超分辨率算法
本文论证了对受大气湍流影响的图像进行超分辨图像重建的可能性。提出了一种利用双相干的幸运区域方法,从大量短曝光图像中选择质量较好的图像块或“幸运图像区域”。然后利用基于通用隐马尔可夫树模型的MAP方法从幸运区域重构出超分辨图像。用实际数据演示了性能。
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