A Multi-view Super-Resolution Method with Joint-optimization of Image Fusion and Blind Deblurring

作者：Fan, Jun^*; Wu, Yue; Zeng, Xiangrong; Huangpeng, Qizi; Liu, Yan; Long, Xin; Zhou, Jinglun

来源：KSII Transactions on Internet and Information Systems, 2018, 12(5): 2366-2395.

DOI：10.3837/tiis.2018.05.025

• Multi-view super-resolution
• Multi-channel blind deblurring
• Alternating direction method of multipliers

Multi-view super-resolution (MVSR) refers to the process of reconstructing a high-resolution (HR) image from a set of low-resolution (LR) images captured from different viewpoints typically by different cameras. These multi-view images are usually obtained by a camera array. In our previous work [I], we super-resolved multi-view LR images via image fusion (IF) and blind deblurring (BD). In this paper, we present a new MVSR method that jointly realizes IF and BD based on an integrated energy function optimization. First, we reformulate the MVSR problem into a multi-channel blind deblurring (MCBD) problem which is easier to be solved than the former. Then the depth map of the desired HR image is calculated. Finally, we solve the MCBD problem, in which the optimization problems with respect to the desired HR image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM). Experiments on the Multi-view Image Database' of the University of Tsukuba and images captured by our own camera array system demonstrate the effectiveness of the proposed method.

• 出版日期2018-5-31
• 单位中国人民解放军国防科学技术大学