Geometry-based PSF estimation and deblurring of defocused images with depth information

We propose in this paper an algorithm to recover the blurred details of an image caused by defocusing during the photo-taking. Our algorithm takes one RGB image as well as its depth map as the input. We build up a model in which each captured image pixel is regarded as a light-emitting source that goes through a synthetic camera system. Thanks to the depth map, we have the geometrical information of the scene so that the point spread function (PSF) can be derived for each pixel more accurately as compared to conventional approaches where only RGB images are involved. Then, we make use of the derived PSFs to solve an optimization so as to reconstruct an all-in-focus image. The reconstructed results are evaluated by comparison with the original all-in-focus images. Compared to other methods for the deblurring of defocused images, our method shows a better recovery of image details.