A hybrid camera for motion deblurring and depth map super-resolution

被引:0
|
作者
Li, Feng [1 ]
Yu, Jingyi [1 ]
Chai, Jinxiang [2 ]
机构
[1] Univ Delaware, Dept Comp & Informat Sci, Newark, DE 19716 USA
[2] Texas A&M Univ, Dept Comp Sci, College Stn, TX 77843 USA
基金
美国国家科学基金会;
关键词
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
We present a hybrid camera that combines the advantages of a high resolution camera and a high speed camera. Our hybrid camera consists of a pair of low-resolution high-speed (LRHS) cameras and a single high-resolution low-speed (HRLS) camera. The LRHS cameras are able to capture fast-motion with little motion blur They also form a stereo pair and provide a low-resolution depth map. The HRLS camera provides a high spatial resolution but also introduces severe motion blur when capturing fast moving objects. We develop efficient algorithms to simultaneously motion-deblur the HRLS image and reconstruct a high resolution depth map. Our method estimates the motion flow in the LRHS pair and then warps the flow field to the HRLS camera to estimate the point spread function (PSF). We then motion-deblur the HRLS image and use the resulting image to enhance the low-resolution depth map using joint bilateral filters. We demonstrate the hybrid camera in depth map super-resolution and motion deblurring with spatially varying kernels. Experiments show that our framework is robust and highly effective.
引用
收藏
页码:1803 / +
页数:2
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