Bayesian high-resolution reconstruction of low-resolution compressed video

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.

• Type: Conference
• Year: 2001
• Where: ICIP
• Authors: Rafael Molina, Aggelos K. Katsaggelos, Javier Mateos, C. Andrew Segall
• Keywords: ICIP 2001, Image Processing, Low-resolution Observation, Low-resolution Video Sequence, Transmitted Motion Vectors