Fried deconvolution

TL;DR

This paper introduces a new deconvolution method for atmospheric turbulence blur in long-range imaging, utilizing the Fried kernel and framelet algorithms, with a novel parameter estimation technique from blurred images.

Contribution

It presents an analytical Fried kernel-based deconvolution approach and a method to estimate the refractive index structure parameter directly from blurred images.

Findings

Effective deblurring on simulated images

Good performance on real images

Easy to implement algorithms

Abstract

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.