Scene-adaptive coded aperture imaging

Xuehui Wang, Feng Dai, Yike Ma, Ke Gao, Yongdong Zhang

Abstract: Coded aperture imaging systems have recently shown great success in recovering scene depth and extending the depth-of-field. Tremendous efforts have been focused on designing good coded patterns. The ideal pattern, however, would have to serve two conflicting purposes: 1) it should be broadband to ensure robust deconvolution and 2) it should have sufficient zero-crossings for a high depth discrepancy. This paper presents a simple but effective scene-adaptive coded aperture solution to bridge this gap. We observe that natural scenes often exhibit a dominant edge direction that can be caused by structure, texture, shading, etc. We therefore apply depth-discriminative codes along the dominant direction and broadband codes along its orthogonal direction. To physically implement this scheme, we adopt a two-shot scheme. Firstly, we capture a scene image with a pinhole aperture and analyze image content to determine the dominant direction. Secondly, we apply the proposed coding scheme using the programmable Liquid Crystal on Silicon (LCoS). Experiments on a broad range of synthetic and real scenes show that our technique is able to combine advantages of the state-of-the-art patterns for recovering better quality depth map and all-focus images.