FID: Frame Interpolation and Dct-Base d Video Compression

Authors

Yeganeh Jalalpour, Portland State UniversityFollow
Li-Yun Wang, Portland State UniversityFollow
Wu-Chi Feng, Portland State UniversityFollow
Feng Liu, Portland State UniversityFollow

Published In

2020 IEEE International Symposium on Multimedia (ISM)

Document Type

Citation

Publication Date

2020

Abstract

In this paper, we present a hybrid video compression technique that combines the advantages of residual coding techniques found in traditional DCT-based video compression and learning-based video frame interpolation to reduce the amount of residual data that needs to be compressed. Learning-based frame interpolation techniques use machine learning algorithms to predict frames but have difficulty with uncovered areas and non-linear motion. This approach uses DCT-based residual coding only on areas that are difficult for video interpolation and provides tunable compression for such areas through an adaptive selection of data to be encoded. Experimental data for both PSNR and the newer video multi-method assessment fusion (VMAF) metrics are provided. Our results show that we can reduce the amount of data required to represent a video stream compared with traditional video coding while outperforming video frame interpolation techniques in quality.

Rights

© Copyright 2021 IEEE - All rights reserved

Locate the Document

https://doi.org/10.1109/ISM.2020.00045

DOI

10.1109/ISM.2020.00045

Persistent Identifier

https://archives.pdx.edu/ds/psu/34918

Publisher

IEEE

Citation Details

Jalalpour, Y., Wang, L.-Y., Feng, W.-C., & Liu, F. (2020). FID: Frame Interpolation and DCT-based Video Compression. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ism.2020.00045