Computational Photography: Epsilon to Coded Photography

被引:0
|
作者
Raskar, Ramesh [1 ]
机构
[1] MIT, Media Lab, Cambridge, MA 02139 USA
来源
关键词
Digital photography; Fourier transform; Fourier optics; Optical heterodyning; Coded aperture imaging; digital refocusing; plenoptic camera;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Computational photography combines plentiful computing, digital sensors, modern optics, actuators, and smart lights to escape the limitations of traditional cameras, enables novel imaging applications and simplifies many computer vision tasks. However, a majority of current Computational photography methods involves taking multiple sequential photos by changing scene parameters and fusing the photos to create a richer representation. Epsilon photography is concerned with synthesizing omnipictures and proceeds by multiple capture single image paradigm (MCSI). The goal of Coded computational photography is to modify the optics, illumination or sensors at the time of capture so that the scene properties are encoded in a single (or a few) photographs. We describe several applications of coding exposure, aperture, illumination and sensing and describe emerging techniques to recover scene parameters from coded photographs.
引用
收藏
页码:238 / 253
页数:16
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