FlatCam: Replacing Lenses with Masks and Computation

被引:25
作者
Asif, M. Salman [1 ]
Ayremlou, Ali [1 ]
Veeraraghavan, Ashok [1 ]
Baraniuk, Richard [1 ]
Sankaranarayanan, Aswin [2 ]
机构
[1] Rice Univ, Houston, TX 77251 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
来源
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOP (ICCVW) | 2015年
基金
美国国家科学基金会;
关键词
D O I
10.1109/ICCVW.2015.89
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a thin form-factor lensless camera, FlatCam, that consists of a coded mask placed on top of a bare, conventional sensor array. FlatCam is an instance of a coded aperture imaging system in which each pixel records a linear combination of light from multiple scene elements. A computational algorithm is then used to demultiplex the recorded measurements and reconstruct an image of the scene. In contrast with vast majority of coded aperture systems, we place the coded mask extremely close to the image sensor that can enable a thin system. We use a separable mask to ensure that both calibration and image reconstruction are scalable in terms of memory requirements and computational complexity. We demonstrate the potential of our design using a prototype camera built using commercially available sensor and mask.
引用
收藏
页码:663 / 666
页数:4
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