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Bayesian high-resolution reconstruction of low-resolution compressed video
Segall, C.A.; Molina, R.; Katsaggelos, A.K.; Mateos, J.;
Image Processing, 2001. Proceedings. 2001 International Conference on
Volume 2,
7-10 Oct. 2001
Page(s):25
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28 vol.2
Abstract:
A method for simultaneously estimating the high-resolution frames and the corresponding motion field from a compressed low-resolution video sequence is presented. The algorithm incorporates knowledge of the spatio-temporal correlation between low and high-resolution images to estimate the original high-resolution sequence from the degraded low-resolution observation. Information from the encoder is also exploited, including the transmitted motion vectors, quantization tables, coding modes and quantizer scale factors. Simulations illustrate an improvement in the peak signal-to-noise ratio when compared with traditional interpolation techniques and are corroborated with visual results
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