TV正则化的双迭代RL湍流退化图像复原算法

RL算法是湍流退化图像复原的一类重要算法,但在迭代过程中存在噪声放大或过度平滑问题.围绕湍流退化图像复原问题对RL（Richardson-Lucy）算法及其改进方法进行研究：建立了一种短曝光成像探测湍流退化模型,并给出该模型中随机相位屏的数值模拟方法;推导了RL算法的基本原理和计算公式;为更好地从湍流退化图像中恢复目标,提出了TV正则化双迭代RL图像复原算法.改进算法引入总体变分约束,并对目标图像和点扩展函数采用内外循环双重迭代,充分利用了目标图像和点扩展函数的内在联系.仿真实验表明,算法能有效地保持了图像的细节信息,复原效果明显优于传统RL算法.

Double-Circulation Iterative RL Restoration Algorithm of Turbulence-Degraded Images Using TV-Regularized Method

The RL Richardson Lucy algorithm is an important method for restoration of turbulence degraded images. However, it suffers the shortcoming of amplifying the noise and resulting in excessive smoothing in the iterative process. This paper discusses the RL algorithm and its improved methods focusing on turbulence degraded images restoration. A short exposure atmospheric turbulence degraded model is established and a numerical computing method is proposed for random phase screen. Additionally, the essential principle and computational formulas are deduced. To restore the object image effectively from the turbulence degraded image, a new double circulation iterative Richardson Lucy restoration algorithm using TV regularized method is proposed. The proposed algorithm introduces the total variation restraint and estimates the object image and the point spread function based on the inner and outer double circulation iteration, which can use the inherent relation between the object image and the point spread function adequately. Simulation experiments show that the proposed algorithm can effectively preserve the details and edges of the image and its restoration effect is obviously better than the traditional RL algorithm.