Motion Blur Identification Based on Differently Exposed Images

In this paper we introduce a new method of motion blur identification that relies on the availability of two, differently exposed, image shots of the same scene. The proposed approach exploits the difference in the degradation models of the two images in order to identify the point spread function (PSF) corresponding to the motion blur, that may affect the longer exposed image shot. The algorithm is demonstrated through a series of experiments that reveal its ability to identify the motion blur PSF even in the presence of heavy degradations of the two observed images.

[1]  A. R. Rao,et al.  A Taxonomy for Texture Description and Identification , 1990, Springer Series in Perception Engineering.

[2]  Abbas El Gamal,et al.  Synthesis of high dynamic range motion blur free image from multiple captures , 2003 .

[3]  Tony F. Chan,et al.  Total variation blind deconvolution , 1998, IEEE Trans. Image Process..

[4]  Ying Zhang,et al.  Estimation of motion parameters from blurred images , 2000, Pattern Recognit. Lett..

[5]  Junichi Nakamura,et al.  Image Sensors and Signal Processing for Digital Still Cameras , 2005 .

[6]  Marius Tico,et al.  Method of Motion Estimation for Image Stabilization , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[7]  Shree K. Nayar,et al.  Motion-based motion deblurring , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Mostafa Kaveh,et al.  A regularization approach to joint blur identification and image restoration , 1996, IEEE Trans. Image Process..