Three-dimension deblurring algorithm for multiple observed images of moving object

For the problem of deblurring of multiple observed images of moving objects with different blur kernels, a joint three-dimension deblurring method for multiple observed images was proposed. Unlike existing deblurring methods to remove 2D blur for single observed image without considering relationship of blur kernels in multiple observed images, the relationship of different PSF paths of multiple observed images was explored. The movement in three-dimension space was projected into each observed image planes, hence, the inherent relationship between the two PSF paths of two observed images can be set up. At first, motion blur kernels of two view images were estimated using single observed image debluring method and the blur kernels with one pixel width was refined. When having estimated two PSF paths, the other PSF paths could be calculated and optimized by using the relationship of PSF paths in multiple observed images. Then 3D blur of the observed images could be removed by using the proposed method. The experiment results for multiple observed images demonstrate that the proposed approach is efficient and effective in removing 3D blur and reconstruction.