Exploring aligned complementary image pair for blind motion deblurring

Camera shake during long exposure is ineluctable in light-limited situations, and results in a blurry observation. Recovering the blur kernel and the latent image from the blurred image is an inherently ill-posed problem. In this paper, we analyze the image acquisition model to capture two blurred images simultaneously with different blur kernels. The image pair is well-aligned and the kernels have a certain relationship. Such strategy overcomes the challenge of blurry image alignment and reduces the ambiguity of blind deblurring. Thanks to the aided hardware, the algorithm based on such image pair can give high-quality kernel estimation and image restoration. The experiments on both synthetic and real images demonstrate the effectiveness of our image capture strategy, and show that the kernel estimation is accurate enough to restore superior latent image, which contains more details and fewer ringing artifacts.