JOURNAL ARTICLE

<title>Digital video blue-screen editing in compressed domain</title>

Bo ShenIshwar K. SethiVasudev Bhaskaran

Year: 1997 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3024 Pages: 971-982   Publisher: SPIE

Abstract

Chroma-keying or blue screen matting is an important video editing operational. In blue screen matting, everything in the image that has the 'user specified level for the blue channel' is 'keyed' out and replaced by either another image or a color from a color generator. We develop a technique for blue screen matting that manipulates the image when the information for the image is available only in compressed form such as a JPEG or MPEG bitstream. Specifically, for the compressed domain approach, we show that the matting process is a convolution operation; hence, we develop a DCT convolution theorem. The DCT convolution theorem can be used to show that the compressed domain approach proposed in this paper provides a significant reduction in computation complexity compared to previously developed approaches which were mostly adhoc techniques. The convolution theorem exploits the sparseness as well as the orthogonality of the data available in the DCT domain and thus yields an efficient algorithm for he chroma-keying or blue screen matting. The algorithm extends to the DCT domain concepts such as alpha channel and premultiplied alpha. The method is also extended to MPEG video domain wherein we explore the efficiency of the matting process when interframe coding is used.

Keywords:
Computer science Discrete cosine transform JPEG Convolution (computer science) Artificial intelligence Computer vision Decoding methods Channel (broadcasting) Computer graphics (images) Data compression Algorithm Image (mathematics) Telecommunications

Metrics

2
Cited By
0.39
FWCI (Field Weighted Citation Impact)
0
Refs
0.62
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Color Science and Applications
Physical Sciences →  Physics and Astronomy →  Atomic and Molecular Physics, and Optics

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