摘要
相机响应函数(CRF)存在于照片的形成过程中,是辐照度到图像强度的映射。由于CRF是非线性的,在模糊图像去模糊的过程中有一定的影响,但目前的运动模糊去除算法并未考虑它的影响。为此,研究基于单幅运动模糊图像的CRF估计算法,给出运动模糊模型与CRF相结合的模糊模型,该模型能准确描述实际运动模糊图的形成过程,并在该模型的基础上提出一种灵活选取边界求解CRF的方法。实验结果证明,与传统方法相比,该方法在求解CRF方法上具有较高的准确性。
Camera Response Function（ CRF） appears in the formation of a photo,mapping the irradiance to the image intensity. CRF is nonlinear,thus it has effects on deblurring blurred image. But many current deblurring algorithms do not consider the influence of camera response function. Therefore,this paper discusses the algorithm of deblurring based on a single image with considering the influence of CRF, and presents a model combining the motion blur model with the CRF. This model can describe the forming process of a real blurred image accurately. Further more,it presents a flexible edge selection CRF estimation method based on the motion model. Experimental results prove that the method has advantage in solving CRF method and removes the influence of CRF on deblurring.
出处
《计算机工程》
CAS
CSCD
2014年第10期232-238,共7页
Computer Engineering
基金
国家自然科学基金资助项目(61003131)
关键词
相机响应函数
辐照度
非线性
运动模糊
去模糊
边界选取
Camera Response Function （CRF）
irradiance
nonlinear
motion blurred
deblurring
edge selection
