A new method to accelerate depth extraction for aperture-coded camera

Depth extraction, or the retrieval of three-dimensional information of the captured scene from camera, is an important problem in computer vision and image processing. The aperture-coded camera has certain advantages in depth extraction. However, such calculation will cost huge time as it contains weighted iterative deconvolution. In order to solve the problem, this paper proposes an improved algorithm in which the image is firstly segmented and then the small image regions are sampled for deconvolution and depth judgment. Experimental results prove that the proposed method can greatly reduce time consumption and save computer memory. On this basis, by using the characteristics of aperture-coded camera obtaining image and depth, we propose a framework to handle the application of stitching the images of occluded scene, and then carry out experiments.