A New Super-Resolution Method for Monochrome Camera Array Imaging

被引:0
作者
Long, Xin [1 ]
Liu, Yan [1 ]
Zeng, Xiangrong [1 ]
Zhang, Maojun [1 ]
机构
[1] Natl Univ Def Technol, Coll Syst Engn, Changsha, Peoples R China
来源
ELEVENTH INTERNATIONAL CONFERENCE ON GRAPHICS AND IMAGE PROCESSING (ICGIP 2019) | 2020年 / 11373卷
关键词
super-resolution; monochrome camera; color filter array; cross-channel prior; RECOVERY;
D O I
10.1117/12.2557364
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Multi-view super-resolution refers to the process of reconstructing a high-resolution image from a set of low-resolution images captured from different viewpoints typically by different cameras. These multi-view images are usually obtained by an array of the same color cameras. However, the color cameras have color filter array to acquire color information, which reduces the quality of obtained images. To avoid color camera, and obtain higher resolution color images, we do research on a camera array which consists of interlaced different monochrome cameras and propose a new super-resolution method based on the camera array. Given that MVSR is an ill-posed problem and is typically computationally costly, we super-resolve multi-view monochrome images of the original scene via solve a regularization optimization problem consisting of a data-fitting term and three regularization terms on image, blur and cross-channel priors. The resulting optimization problems with respect to the desired image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multiplier. Corresponding experimental results, conducted on a series of datasets captured by our own camera array system, demonstrate the effectiveness of the proposed method.
引用
收藏
页数:5
相关论文
共 20 条
[1]   An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems [J].
Afonso, Manya V. ;
Bioucas-Dias, Jose M. ;
Figueiredo, Mario A. T. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2011, 20 (03) :681-695
[2]   Fast Image Recovery Using Variable Splitting and Constrained Optimization [J].
Afonso, Manya V. ;
Bioucas-Dias, Jose M. ;
Figueiredo, Mario A. T. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (09) :2345-2356
[3]   Deconvolving Images With Unknown Boundaries Using the Alternating Direction Method of Multipliers [J].
Almeida, Mariana S. C. ;
Figueiredo, Mario A. T. .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (08) :3074-3086
[4]  
[Anonymous], ACM T GRAPHICS
[5]   Distributed optimization and statistical learning via the alternating direction method of multipliers [J].
Boyd S. ;
Parikh N. ;
Chu E. ;
Peleato B. ;
Eckstein J. .
Foundations and Trends in Machine Learning, 2010, 3 (01) :1-122
[6]   Super-resolution imaging using a camera array [J].
Carles, Guillem ;
Downing, James ;
Harvey, Andrew R. .
OPTICS LETTERS, 2014, 39 (07) :1889-1892
[7]   Signal recovery by proximal forward-backward splitting [J].
Combettes, PL ;
Wajs, VR .
MULTISCALE MODELING & SIMULATION, 2005, 4 (04) :1168-1200
[8]  
Duchi John C., 2008, P 25 INT C MACH LEAR, V307, P272
[9]  
Gabay D., 1976, Computers & Mathematics with Applications, V2, P17, DOI 10.1016/0898-1221(76)90003-1
[10]  
Guillem C., COMPACT MULTIAPERTUR