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

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.