Proceedings of the 4th ACM International Conference on Multimedia in Asia
Computer vision, Image processing -- Methodology, Neural networks (Computer science), Machine learning
Video data is ubiquitous; capturing, transferring, and storing even compressed video data is challenging because it requires substantial resources. With the large amount of video traffic being transmitted on the internet, any improvement in compressing such data, even small, can drastically impact resource consumption. In this paper, we present a hybrid video compression framework that unites the advantages of both DCT-based and interpolation-based video compression methods in a single framework. We show that our work can deliver the same visual quality or, in some cases, improve visual quality while reducing the bandwidth by 10--20%.
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Jalalpour, Y., Feng, W. C., & Liu, F. (2022, December). Sequential Frame-Interpolation and DCT-based Video Compression Framework. In Proceedings of the 4th ACM International Conference on Multimedia in Asia (pp. 1-7).
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