JOURNAL ARTICLE

<title>Encoding-scaled MPEG video in compressed domain</title>

Qingwen HuSethuraman Panchanathan

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3024 Pages: 983-991   Publisher: SPIE

Abstract

Image and video compression is becoming increasingly popular with the advent of broadband networks, high powered workstations, and compression standards. Visual data are therefore expected to be stored in the compressed format in future image and video databases. Recently, techniques for manipulating the DCT parameters have been proposed in the literature. However, these techniques are not directly applicable to MPEG video due to motion estimation/compensation procedure present in addition to DCT coding. In this paper, we propose a macroblock type selective encoder to implement scalable MPEG video coding using a combined DCT domain scaling operation and a modified DCT domain motion compensation technique. The proposed encoder removes the unnecessary decompression/re-compression and motion estimation procedures, and derives the motion information and DCT coefficients of the prediction errors for the scaled macroblocks for the original motion vectors and DCT coefficients, respectively. Hence, it provides an elegant way to re-encode the scaled video while maintaining a good video quality. In addition, it is compatible with the standard MPEG encoder.

Keywords:
Motion compensation Computer science Macroblock Discrete cosine transform Computer vision Data compression Motion estimation Quarter-pixel motion Encoder Artificial intelligence Block-matching algorithm Motion vector Multiview Video Coding Video compression picture types Video tracking Video processing Decoding methods Algorithm Image (mathematics)

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Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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