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Parameter Estimation for Blur Image Combining Defocus and Motion Blur using Cepstrum Analysis
  • 时间:0
  • 分类:TP391.41[自动化与计算机技术—计算机应用技术;自动化与计算机技术—计算机科学与技术]
  • 作者机构:[1]Inst. of Medical Precision Eng. & Intelligent System Shanghai Jiaotong Univ., [2]Inst. of Medical Precision Eng. & Intelligent System Shanghai Jiaotong Univ., [3]Shanghai 200240 China
  • 相关基金:The National Natural Science Foundation of China (No 30570485)
  • 相关项目:胃肠道动力和生理参数无创检测技术及胃肠功能数字化研究
中文摘要:

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 is a more complicated mission. A method was proposed for computer to estimate the parameters of defocus blur and motion blur in cepstrum area simultaneously. According to characters of both blur models in the frequency domain, an adjustment approach was suggested in the frequency area and then convert to the cepstrum field to increase the accuracy of measurement.

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