Motion-vector-based adaptive quantization in MPEG-4 fine granular scalable coding

Shuping Yang; Xinggang Lin; Guijin Wang

doi:10.1117/12.476354

7 May 2003 Motion-vector-based adaptive quantization in MPEG-4 fine granular scalable coding

Shuping Yang, Xinggang Lin, Guijin Wang

Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476354
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

Selective enhancement mechanism of Fine-Granular-Scalability (FGS) In MPEG-4 is able to enhance specific objects under bandwidth variation. A novel technique for self-adaptive enhancement of interested regions based on Motion Vectors (MVs) of the base layer is proposed, which is suitable for those video sequences having still background and what we are interested in is only the moving objects in the scene, such as news broadcasting, video surveillance, Internet education, etc. Motion vectors generated during base layer encoding are obtained and analyzed. A Gaussian model is introduced to describe non-moving macroblocks which may have non-zero MVs caused by random noise or luminance variation. MVs of these macroblocks are set to zero to prevent them from being enhanced. A segmentation algorithm, region growth, based on MV values is exploited to separate foreground from background. Post-process is needed to reduce the influence of burst noise so that only the interested moving regions are left. Applying the result in selective enhancement during enhancement layer encoding can significantly improves the visual quality of interested regions within an aforementioned video transmitted at different bit-rate in our experiments.

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Shuping Yang, Xinggang Lin, and Guijin Wang "Motion-vector-based adaptive quantization in MPEG-4 fine granular scalable coding", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476354

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KEYWORDS

Video surveillance

Video

Computer programming

Quantization

Visualization

Motion models

Image enhancement

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