Extremely fast selective enhancement method for fine granular scalable enabled H.264 video

TitleExtremely fast selective enhancement method for fine granular scalable enabled H.264 video
Publication TypeConference Paper
Year of Publication2003
AuthorsUgur, K., G. Louizis, P. Nasiopoulos, and R. Ward
Conference NameElectrical and Computer Engineering, 2003. IEEE CCECE 2003. Canadian Conference on
Pagination1103 - 1106 vol.2
Date Publishedmay.
Keywordsblock-by-block basis, camera motion, fast selective enhancement method, feature extraction, fine granular scalability, image enhancement, image motion analysis, image sequences, intercoded macroblock types, motion vector data, MPEG-4 streaming video profile, predecessor standards, real-time systems, real-time video communications systems, scalable H.264 video encoding, video coding

A novel method, that selectively enhances the visually important regions in scalable H.264 video encoding, is proposed. The proposed method is extremely fast and is designed to be used in real-time video communications systems. The method is based on fine granular scalability (FGS). FGS provides a framework to adapt to variations in the channel bandwidth, and it was recently standardized in the streaming video profile of MPEG-4. FGS also provides to the encoder the ability to selectively enhance the regions that are visually important, increasing the subjective video quality. In this paper we use the emerging video coding standard, H.264, for encoding the base layer, as opposed to MPEG-4. H.264 has several key differences with its predecessor standards, one of them being the new inter coded macroblock types. It was observed that specific macroblock types indicate visually important regions. In our proposed method, the macroblock (MB) type information along with motion vector (MV) data are used to extract features such as motion activity and camera motion. These features are used for defining the regions to be enhanced. Since, all of the operations are taking place on a block-by-block basis, the method presented here has very low computational complexity and suitable for real-time video communication systems. Experimental results show that subjective quality of the video sequence is significantly improved using our method.


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