基于频谱预处理与改进霍夫变换的离焦模糊盲复原算法

为了提高离焦模糊图像复原清晰度，提出一种基于频谱预处理与改进霍夫变换的 离焦模糊盲复原算法。首先改进模糊图像频谱预处理策略，降低了噪声对零点暗圆检测的影响。 然后改进霍夫变换圆检测算法，在降低算法复杂度的同时，增强了模糊半径估计的准确性。最 后利用混合特性正则化复原图像模型对模糊图像进行迭代复原，使复原图像的边缘细节更加清 晰。实验结果表明，提出的模糊半径估计方法较其他方法平均误差更小，改进的频谱预处理策 略更有利于零点暗圆检测，改进的霍夫变换圆检测算法模糊半径估计精度更高，所提算法对已 知相机失焦的小型无人机拍摄的离焦模糊图像具有更好的复原效果。针对离焦模糊图像复原， 通过理论分析和实验验证了改进的模糊半径估计方法的鲁棒性强，所提算法的复原效果较好。

Blind Restoration of Focus Blur Based on Spectrum Preprocessing and Improved Hough Transform

To improve the resolution of defocused blurred images, the paper presents a blind restoration algorithm of focus blur based on spectrum preprocessing and improved Hough transform. Firstly, the spectrum preprocessing strategy is improved to deal with the blur image spectrum map, and the impacts of noise on the detection of zero point dark circle is reduced. Then the algorithm of Hough transform circle detection is improved to reduce its complexity, meanwhile the accuracy of the estimation of the blur radius is enhanced. Finally, the authors take advantage of the mixed characteristic regularized restoration image model to restore the blur image iteratively, which makes the edge details of the restored image more focused. The experimental results show that the proposed method of blur radius estimation has less average error than other methods. The improved spectrum preprocessing strategy is more advantageous to the detection of zero dark circles. The improved algorithm of the Hough transformation circle detection algorithm has higher accuracy of the blur radius estimation. The proposed algorithm has a better recovery effect on defocused images taken by a small UAV out of focus on the camera. As for the blind restoration of focus blur images, the theoretical analysis and experiment validate the good robustness of the improved blur radius estimation method in this paper.