为了快速准确地估计直线运动模糊图像中的模糊参数，分析了直线运动模糊参数的长度和方向在频率域图像和倒谱图像中的表现形式，提出了一种基于主成分分析的运动模糊参数估计方法。首先，基于高斯建模对模糊图像中的倒谱图像进行二值化分割，得到倒谱图像中的亮线区域。然后，基于主成分分析提取亮线区域的主成分分量，主成分分量的方向即为模糊角度; 依据估计的模糊角度，计算模糊图像傅里叶频率域图像相应角度的Radon变换，进行滤波去“毛刺”处理。最后，通过计算极小值之间的间距，估计模糊长度。实验结果表明：估计的模糊角度和模糊长度平均误差分别为0.138 4°和0.273 9 pixel，在同精度条件下，速度是传统的Radon变换方法的10倍左右，表明该方法能快速、准确地估计直线运动模糊参数。

To estimate the blur parameter of a linear motion blur image accurately and quickly, this paper analyses how the blur length and direction show in a frequency image and a cepstrum image, respectively, and proposes a motion blur parameter estimation method based on the Principal Component analysis (PCA). Firstly, the cepstrum image of the blur image was segmented in a binaryzation based on the Gaussian distribution modeling, and the highlight line region in the cepstrum image was obtained. Then, the principal component of the highlight line was extracted based on the PCA, and the direction of the principal component was the blur direction. After the blur direction was estimated, the Radon transform of frequency image for the blur image under the estimated direction was calculated, then the result of Radon transform was smoothed to reduce some artifacts. Finally, the blur length was estimated via calculating the interval between the two local-minimas of the Radon transform. Experiment results indicate that the errors of the estimated blur direction and length are 0.138 4°and 0.273 9 pixel, respectively, and the calculation speed is nearly 10 times faster than that of the traditional estimated method based on Radon method with the same accuracy. It concludes that the proposed method can estimate the blur parameter accurately and rapidly.