Continuous digital zooming using local self-similarity-based super-resolution for an asymmetric dual camera system

Abstract

This paper presents a digital zooming method using a super-resolution (SR) algorithm based on the local self-similarity between the wide-and tele-view images acquired by an asymmetric dual camera system. The proposed SR algorithm consists of four steps: (i) registration of an optically zoomed image to the wide-view image, (ii) restoration of the central region of the zoomed wide-view image, (iii) restoration of the boundary region of the zoomed wideview image, and (iv) fusion of the results from steps (ii) and (iii). Since an asymmetric dual camera system acquires different-resolution images on the same scene due to the different optical specifications, the proposed method can restore the low-resolution wide-view image using the ideal high-frequency component estimated from the optically zoomed image. Experimental results demonstrate that the proposed method can provide significantly improved high-resolution wide-view images compared to existing single-image- based SR methods. (C) 2017 Optical Society of America