Pre-Processing of Compressed Digital Video Based on Perceptual Quality Metrics

Passant V. Karunaratne*, Aggelos K Katsaggelos, Thrasyvoulos N Pappas

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


The objective of pre-processing is to eliminate information of least visual significance prior to encoding, in order to achieve best overall performance of a video compression system. We formulate the pre-processing problem in an operational rate-distortion framework, with the aim of maximizing the visual quality of the compressed video, as well as the coding efficiency of the system. Rather than filtering the original video, our novel approach consists of filtering the motion compensated error signal. This offers a significant computational advantage over other pre-filtering methods without sacrificing effectiveness. The proposed method selects the parameters of a pre-filter in conjunction with the selection of the quantization scales of the encoder. We incorporate a perceptual quality metric in the optimization process, in order to maximize the visual quality of the compressed video for given rate constraints. Our approach is developed for motion-compensated block-based discrete cosine transform coders, which form the basis of several video coding standards. We use the visual quality metric that was proposed by Watson, which was developed for such coders, based on the discrete cosine transform decomposition. The effectiveness of the proposed approach is demonstrated by simulation results, carried out within the framework of MPEG-2 video compression.

Original languageEnglish (US)
Pages (from-to)137-148
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Nov 20 2003
EventHuman Vision and Electronic Imaging VIII - Santa Clara, CA, United States
Duration: Jan 21 2003Jan 24 2003


  • Perceptual Quality Metrics
  • Rate-distortion Optimization
  • Video Pre-processing

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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