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方贤勇, 阚未然, 陈尚文, 郭延文, 周健, 王安, 张兴义. 面向运动过程建模的运动模糊图像摄像机响应函数估计方法[J]. 计算机辅助设计与图形学学报, 2015, 27(7): 1238-1246.
引用本文: 方贤勇, 阚未然, 陈尚文, 郭延文, 周健, 王安, 张兴义. 面向运动过程建模的运动模糊图像摄像机响应函数估计方法[J]. 计算机辅助设计与图形学学报, 2015, 27(7): 1238-1246.
Fang Xianyong, Kan Weiran, Chen Shangwen, Guo Yanwen, Zhou Jian, Wang An, Zhang Xingyi. Motion–Modeling-Oriented Camera Response Function Estimation Method for Motion Blurred Images[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(7): 1238-1246.
Citation: Fang Xianyong, Kan Weiran, Chen Shangwen, Guo Yanwen, Zhou Jian, Wang An, Zhang Xingyi. Motion–Modeling-Oriented Camera Response Function Estimation Method for Motion Blurred Images[J]. Journal of Computer-Aided Design & Computer Graphics, 2015, 27(7): 1238-1246.

面向运动过程建模的运动模糊图像摄像机响应函数估计方法

Motion–Modeling-Oriented Camera Response Function Estimation Method for Motion Blurred Images

  • 摘要: 摄像机响应函数是将图像辐照度映射到图像强度的非线性函数,目前的运动模糊去除算法并没有考虑成像过程中摄像机响应函数的影响,不可避免地存在去模糊效果不佳的现象.通过研究运动模糊图像的摄像机响应函数估计问题,提出能量累积形成模糊的运动过程和摄像机响应函数相结合的摄像机响应函数求解模型,并进一步基于该运动过程模型提出一幅或多幅运动模糊图像的摄像机响应函数求解方法.首先选择一些与局部运动方向不平行的模糊边界,然后根据这些边界的模糊形成过程简化摄像机响应函数求解模型,实现摄像机响应函数求解.该方法没有苛刻的平行边界要求,较已有方法更加灵活.摄像机响应函数的求解实验及运动模糊图像去模糊实验结果表明,文中的求解摄像机响应函数模型和方法是准确的,利用该响应函数可提高对运动模糊的去除效果.

     

    Abstract: Camera response function(CRF) is a nonlinear function which maps image irradiance to image intensity. However in the community there is no motion deblurring method considering the effect of CRF and, correspondingly, existing methods cannot effectively deblur the blurred image. In this paper we study the CRF estimation method for motion deblurring. A new CRF estimation model is proposed, which can reflect the energy accumulation during the motion process of capturing a blurred image. The CRF estimation method for one or multiple motion blurred images based on this model is then introduced. In the method, some edges non-parallel to the local motion direction are first selected, then the computation of CRF estimation model is simplified with the edges so that the optimal CRF is finally obtained. This method is more flexible than previous method which additionally needs the edges be parallel and high quality. The CRF estimation experiments and the motion deblurring experiments demonstrate the effectiveness of the proposed CRF estimation model and method.

     

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