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Your search keyword '"Garrido-Cantos, Rosario"' showing total 5 results
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2. Temporal video transcoding for Digital TV broadcasting.

Author

Garrido-Cantos, Rosario, Martinez, Jose Luis, Cuenca, Pedro, Garrido, Antonio, De Cock, Jan, Van Leuven, Sebastiaan, and Van de Walle, Rik

Abstract

Mobile Digital TV environments demand flexible video compression like Scalable Video Coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. This paper proposes two techniques to convert an H.264/AVC bitstream in Main Profile (B-pictures based) without scalability to a scalable bitstream with temporal scalability as part of a framework for low-complexity video adaptation for mobile digital TV. Our approaches are based on accelerating the interprediction, focusing on reducing the coding complexity of mode decision and motion estimation tasks of the encoder stage by using information available after the H.264/AVC decoding stage. The results show that when our techniques are applied, the complexity is reduced by 98% while maintaining coding efficiency. [ABSTRACT FROM PUBLISHER]

Published
2012
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5. Generic techniques to reduce SVC enhancement layer encoding complexity.

Author

Van Leuven, Sebastiaan, De Cock, Jan, Garrido-Cantos, Rosario, Martinez, Jose, and Van de Walle, Rik

Subjects
CODING theory, COMPUTATIONAL complexity, MATHEMATICAL optimization, SCALABILITY, PREDICTION models, END-user computing, STREAMING technology, DECISION making
Abstract

Scalable video coding is an important mechanism to provide several types of end-user devices with different versions of the same encoded bitstream. However, scalable video encoding remains a computationally expensive operation. To decrease the complexity we propose generic techniques. These techniques are generic in a sense that they can be combined with existing fast mode decision methods and optimizations. We show that extending such an existing fast mode decision technique yields an average complexity reduction of 87.27%, while only an additional 0.74% of bit rate increase and a decrease of 0.11dB in PSNR is required, compared to the original fast mode decision method. [ABSTRACT FROM AUTHOR]

Published
2011
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