运动与离焦模糊图像的复原

在运动和离焦所引起的图像模糊的情况中,本文提出了一种新的基于霍夫变换区分离焦模糊和运动模糊两类模糊的方法.该方法通过比较霍夫变换矩阵中的亮点数来区分两类模糊,不仅正确率达到100%,而且抗干扰性能好;其次通过对运动模糊图像做两次方向微分,估计其模糊方向,提高了模糊方向的估计准确度;最后利用改进的Prewiit算子和费米函数计算模糊图像的刃边函数,进而得到图像的调制传递函数,再利用维纳滤波复原图像.实验结果表明:本文算法不仅具有有效性和强抗噪音能力,而且对图像的信噪比要求可以低到20 dB;与传统算法相比,提高了图像的复原质量.

Restoration of Motion Blur Image and Defocus Blur Image

Due to the image blur caused by defocus and motion, a new method is presented to distinguish defocus blur and motion blur images robustly and accurately. Based on Hough transform and compared the number of highlights in the Hough matrix, this method has high accuracy, up to 100%. An improved approach for motion blur direction from motion blur image via two directional derivations is proposed which improves the precision estimation. And, an improved method is presented to calculate the edge spread function using improved Prewiit operator and Fermi function, then obtain the MTF and then restore image using Wiener filter. Some experiments are performed to validate the performance of the proposed method. Experimental results show that this method has effectiveness and strong resistance to the noise, and can work on noisy images with low SNR; when SNR is 20 dB, it can work robustly. And compared with the traditional image restoration method and model, the image restoration results are improved significantly using the proposed method.