Title :
Jitter camera: high resolution video from a low resolution detector
Author :
Ben-Ezra, Moshe ; Zomet, Assaf ; Nayar, Shree K.
Author_Institution :
Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
fDate :
27 June-2 July 2004
Abstract :
Video cameras must produce images at a reasonable frame-rate and with a reasonable depth of field. These requirements impose fundamental physical limits on the spatial resolution of the image detector. As a result, current cameras produce videos with a very low resolution. Moving the camera and applying super-resolution reconstruction algorithms can computationally enhance the resolution of videos. However, a moving camera introduces motion blur, which limits super-resolution quality. We analyze this effect and derive a theoretical result showing that motion blur has a substantial degrading effect on the performance of super resolution. The conclusion is, that in order to achieve the highest resolution, motion blur should be avoided. Sampling the space-time volume of the video in a specific manner can minimize motion blur. We have developed a novel camera, called the "jitter camera" that achieves this sampling. By applying an adaptive super-resolution algorithm to the video produced by the jitter camera, we show that resolution can be notably enhanced for stationary or slowly moving objects, while it is improved slightly or left unchanged for objects with fast and complex motions. The end result is a video that has a significantly higher resolution than the captured one.
Keywords :
image motion analysis; image reconstruction; image resolution; image sampling; jitter; object detection; video cameras; video signal processing; high resolution video; jitter camera; low resolution detector; motion blur; space-time volume; super-resolution reconstruction algorithms; video sampling; Cameras; Degradation; Detectors; Image motion analysis; Jitter; Motion analysis; Performance analysis; Reconstruction algorithms; Sampling methods; Spatial resolution;
Conference_Titel :
Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
Print_ISBN :
0-7695-2158-4
DOI :
10.1109/CVPR.2004.1315155