Title :
Video from a single coded exposure photograph using a learned over-complete dictionary
Author :
Hitomi, Yasunobu ; Gu, Jinwei ; Gupta, Mohit ; Mitsunaga, Tomoo ; Nayar, Shree K.
Abstract :
Cameras face a fundamental tradeoff between the spatial and temporal resolution - digital still cameras can capture images with high spatial resolution, but most high-speed video cameras suffer from low spatial resolution. It is hard to overcome this tradeoff without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing and reconstructing the space-time volume in order to overcome this tradeoff. Our approach has two important distinctions compared to previous works: (1) we achieve sparse representation of videos by learning an over-complete dictionary on video patches, and (2) we adhere to practical constraints on sampling scheme which is imposed by architectures of present image sensor devices. Consequently, our sampling scheme can be implemented on image sensors by making a straightforward modification to the control unit. To demonstrate the power of our approach, we have implemented a prototype imaging system with per-pixel coded exposure control using a liquid crystal on silicon (LCoS) device. Using both simulations and experiments on a wide range of scenes, we show that our method can effectively reconstruct a video from a single image maintaining high spatial resolution.
Keywords :
dictionaries; image representation; image resolution; image sampling; learning (artificial intelligence); video cameras; camera face; digital still camera; high-speed video camera; image sensor device; learned over-complete dictionary; liquid crystal on silicon device; per-pixel coded exposure control; prototype imaging system; single coded exposure photograph; space-time volume reconstruction; space-time volume representation; space-time volume sampling; sparse representation; spatial resolution; temporal resolution; Cameras; Dictionaries; Image reconstruction; Sensors; Spatial resolution;
Conference_Titel :
Computer Vision (ICCV), 2011 IEEE International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-1-4577-1101-5
DOI :
10.1109/ICCV.2011.6126254