Mobile Computational Photography: A Tour

被引:15
|
作者
Delbracio, Mauricio [1 ]
Kelly, Damien [1 ]
Brown, Michael S. [2 ]
Milanfar, Peyman [1 ]
机构
[1] Google Res, Mountain View, CA 94043 USA
[2] York Univ, EECS Dept, Toronto, ON M6E 3N1, Canada
关键词
computational photography; mobile camera; noise reduction; burst processing; super-resolution; low-light imaging; zoom; camera pipeline; KERNEL REGRESSION; DIFFUSION; IMAGES;
D O I
10.1146/annurev-vision-093019-115521
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The first mobile camera phone was sold only 20 years ago, when taking pictures with one's phone was an oddity, and sharing pictures online was unheard of. Today, the smartphone is more camera than phone. How did this happen? This transformation was enabled by advances in computational photography-the science and engineering of making great images from small-form-factor, mobile cameras. Modern algorithmic and computing advances, including machine learning, have changed the rules of photography, bringing to it new modes of capture, postprocessing, storage, and sharing. In this review, we give a brief history of mobile computational photography and describe some of the key technological components, including burst photography, noise reduction, and super-resolution. At each step, we can draw naive parallels to the human visual system.
引用
收藏
页码:571 / 604
页数:34
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