Paper
17 June 2003 Preprocessing of compressed digital video based on perceptual quality metrics
Author Affiliations +
Proceedings Volume 5007, Human Vision and Electronic Imaging VIII; (2003) https://doi.org/10.1117/12.485524
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Passant V. Karunaratne, Aggelos K. Katsaggelos, and Thrasyvoulos N. Pappas "Preprocessing of compressed digital video based on perceptual quality metrics", Proc. SPIE 5007, Human Vision and Electronic Imaging VIII, (17 June 2003); https://doi.org/10.1117/12.485524
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Video compression

Video

Visualization

Computer programming

Distortion

Video coding

Quantization

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