Bayesian high-resolution reconstruction of low-resolution compressed video

C. A. Segall*, R. Molina, A. K. Katsaggelos, J. Mateos

*Corresponding author for this work

Research output: Contribution to conferencePaper

23 Scopus citations

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.

Original languageEnglish (US)
Pages25-28
Number of pages4
StatePublished - 2001
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: Oct 7 2001Oct 10 2001

Other

OtherIEEE International Conference on Image Processing (ICIP)
CountryGreece
CityThessaloniki
Period10/7/0110/10/01

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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    Segall, C. A., Molina, R., Katsaggelos, A. K., & Mateos, J. (2001). Bayesian high-resolution reconstruction of low-resolution compressed video. 25-28. Paper presented at IEEE International Conference on Image Processing (ICIP), Thessaloniki, Greece.