用解析模型和小波算法，从模糊图像反推大气扰动参数并去模糊。
Fried deconvolution
- 基于弗里德核的解析模型建模大气调制传递函数
- 仅需输入模糊图像即可估计关键的折射率结构参数
- 算法简单易实现，对仿真与真实图像均有效
本文提出一种针对远距离成像中大气湍流导致模糊的新方法。该方法基于大气调制传递函数（MTF）的解析表达式——弗里德核，并结合小波框架的去卷积算法。关键参数为折射率结构常数，通常需专门测量。为此，我们提出一种仅利用输入模糊图像即可良好估计该参数的方法。最终算法实现简便，在模拟模糊与真实图像上均表现出优异去模糊效果。
原文摘要 · Abstract (English)
In this paper we present a new approach to deblur the effect of atmospheric turbulence in the case of long range imaging. Our method is based on an analytical formulation, the Fried kernel, of the atmosphere modulation transfer function (MTF) and a framelet based deconvolution algorithm. An important parameter is the refractive index structure which requires specific measurements to be known. Then we propose a method which provides a good estimation of this parameter from the input blurred image. The final algorithms are very easy to implement and show very good results on both simulated blur and real images.
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