倒谱在混合模糊图像分析中的应用

降晰参数识别在模糊图像恢复过程中具有很重要的作用。在各种图像捕获系统中,有两种形式的图像模糊比较常见:一种是由光学系统散焦造成的散焦模糊;另一种是物体与照相机之间的相对运动造成的运动模糊。相对单个模糊模型的参数识别来说,混合了散焦和运动模糊的图像,其模糊参数的识别要复杂得多。许多识别方法一般都是用来分析某一特定的模糊模型的,而对两种模糊混合在一起的情况来说是很难区分的。提出了一种倒谱分析方法,在倒谱域同时对这两种模型参数进行识别。在分析过程中,仍需要利用这两种模糊模型在频域的特征,首先应用一些调整性的变换,然后再转换到倒谱域,以便更准确地评估模糊参数。

Cepstrum based analysis for blur image combining defocus and motion blur

The degraded parameters recognition is very important for the restoration of blurred images.There are two common types of blurs for most camera systems.One is the defocus blur due to the optical system's defocus phenomenon,and the other is the motion blur due to the relative movement between the objectives and the camera.Compared with the recognition for the blurred image with only one blur model,the parameter estimation for the picture combining defocus and motion blur models are a more complicated mission.A method for computer to estimate the parameters of defocus blur and motion blur in cepstrum area is proposed simultaneously.Fourier transformation plays an intermediate role in the path to cepstrum domain.An adjustment approach in the frequency domain and then converting to cepstrum field to increase the accuracy of measurement is suggested.