JOURNAL ARTICLE

<title>Linear restoration of block-transform-coded motion video</title>

Shun-Fan YangDavid W. Lin

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3024 Pages: 1274-1284   Publisher: SPIE

Abstract

Block-based transform coding employing the discrete cosine transform (DCT) is a popular technique in image and video compression. We consider Wiener-filter-based restoration for transform-coded images and motion video. The scheme operates at the decoder end. It capitalizes on the residual correlation among quantized DCT coefficients and the quantization errors. The scheme, termed error pattern compensation or EPC in short, is derived by simplifying and extending related work of other researchers. When applied to motion video, it is activated for intraframe-coded macroblocks only. It first classifies an encoded image block according to some visually meaningful features and vector quantization. Different Wiener filters can be designed for different classes of input blocks. Experimental results show that the scheme yields performance improvement in the range of a few percent in MSE or PSNR. It is more effective in restoring image blocks with greater quantizing distortion. Results also show that intraframe-coded pictures usually benefit the most from EPC, followed by predictive-coded pictures and then by bidirectional-predictive-coded pictures. At times, the last two types of pictures show performance degradation rather than gain. Possible reasons are discussed.

Keywords:
Discrete cosine transform Quantization (signal processing) Computer science Motion compensation Computer vision Lapped transform Transform coding Artificial intelligence Motion vector Coding (social sciences) Data compression Algorithm Mathematics Image (mathematics) Statistics

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Topics

Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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