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The compressive sensing is a technique which can reduce the sampling rate at the time of sampling the signal. Most high speed video cameras have relatively low spatial resolution. It is hard to overcome the tradeoff between temporal and spatial resolution without incurring a remarkable increase in hardware costs. In this paper, in order to overcome this tradeoff, we adopt compressive sensing techniques...
We address the problem of super-resolution-obtaining high-resolution images and videos from multiple low-resolution inputs. The increased resolution can be in spatial or temporal dimensions, or even in both. We present a unified framework which uses a generative model of the imaging process and can address spatial super-resolution, space-time super-resolution, image deconvolution, single-image expansion,...
We address the problem of video super resolution - obtaining a single high-resolution video whose spatial and temporal resolutions are higher than any of the input low-resolution videos. We employ a reconstruction based approach using MRF -MAP formalism, and use approximate optimization using graph cuts to carry out the reconstruction. We show that in our formulation it is possible to selectively...
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