Saturation-aware human attention region of interest algorithm for efficient video compression

Saturation-aware human attention region of interest algorithm for efficient video compression We propose a saturation-aware human attention region-of-interest (SA-HAROI) video compression method that performs a perceptual adaptive quantization algorithm on video frames as a function of the distribution of their luminance, motion vector, and color saturation. Our work is an application of a psycho-visual study that demonstrated that human attention automatically enhanced perceived saturation. Consequently, the adaptive quantization phase of our compression algorithm is characterized by a luminance and saturation-aware just noticeable distortion (JND) function. After running multiple experiments on 18 videos with various resolutions ranging from QCIF to 4 K, results showed that our method achieves higher compression than that of both the H.264/AVC JM and the HEVC HM while maintaining subjective quality. We observed that in comparison to both implementation of the standards (JM and HM), for an IPPP coding structure, the performance of our algorithm culminated with HD and 4 K videos yielding a bit rate reduction averaging 15% and an encoding time reduction of about 20% in certain cases. Finally, after comparing our method to other similar techniques, we concluded that saturation is a significant parameter in the improvement of video compression. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Saturation-aware human attention region of interest algorithm for efficient video compression

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-018-6108-0
Publisher site
See Article on Publisher Site

Abstract

We propose a saturation-aware human attention region-of-interest (SA-HAROI) video compression method that performs a perceptual adaptive quantization algorithm on video frames as a function of the distribution of their luminance, motion vector, and color saturation. Our work is an application of a psycho-visual study that demonstrated that human attention automatically enhanced perceived saturation. Consequently, the adaptive quantization phase of our compression algorithm is characterized by a luminance and saturation-aware just noticeable distortion (JND) function. After running multiple experiments on 18 videos with various resolutions ranging from QCIF to 4 K, results showed that our method achieves higher compression than that of both the H.264/AVC JM and the HEVC HM while maintaining subjective quality. We observed that in comparison to both implementation of the standards (JM and HM), for an IPPP coding structure, the performance of our algorithm culminated with HD and 4 K videos yielding a bit rate reduction averaging 15% and an encoding time reduction of about 20% in certain cases. Finally, after comparing our method to other similar techniques, we concluded that saturation is a significant parameter in the improvement of video compression.

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: Jun 4, 2018

References

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