Spatial and Temporal Information as Camera Parameters for Super-resolution Video

Most modern consumer cameras are capable of video capture, but their spatial resolution is generally lower than that of still images. The spatial resolution of videos can be enhanced with a hybrid camera system that combines information from high-resolution still images with low-resolution video frames in a process known as super-resolution. As this process is computationally intensive, we propose a camera system that uses the spatial and temporal information measures SI and TI standardized by ITU as camera parameters to determine during capture whether super-resolution processing would result in an increase in perceived quality. Experimental results show that the difference of these two measures can be used to determine the feasibility of super-resolution processing.

[1]  Michael Cohen,et al.  Enhancing and experiencing spacetime resolution with videos and stills , 2009, 2009 IEEE International Conference on Computational Photography (ICCP).

[2]  Yaron Caspi,et al.  Under the supervision of , 2003 .

[3]  Ethan D. Montag,et al.  Louis Leon Thurstone in Monte Carlo: creating error bars for the method of paired comparison , 2003, IS&T/SPIE Electronic Imaging.

[4]  Roger Y. Tsai,et al.  Multiframe image restoration and registration , 1984 .

[5]  Peter G. Engeldrum,et al.  Psychometric Scaling: A Toolkit for Imaging Systems Development , 2000 .

[6]  W.E. Snyder,et al.  Color image processing pipeline , 2005, IEEE Signal Processing Magazine.

[7]  Stefan Winkler,et al.  Digital Video Quality: Vision Models and Metrics , 2005 .

[8]  Seth J. Teller,et al.  Particle Video: Long-Range Motion Estimation Using Point Trajectories , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Joyce E. Farrell,et al.  Handbook of Image Quality: Characterization and Prediction , 2004 .