Ensemble Learning-Based Rate-Distortion Optimization for End-to-End Image Compression

End-to-end image compression using trained deep networks as encoding/decoding models has been developed substantially in the recent years. Previous work is limited in using a single encoding/decoding model, whereas we explore the usage of multiple encoding/decoding models as an ensemble. We propose...

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Bibliographic Details
Published in:	IEEE transactions on circuits and systems for video technology Vol. 31; no. 3; pp. 1193 - 1207
Main Authors:	Wang, Yefei, Liu, Dong, Ma, Siwei, Wu, Feng, Gao, Wen
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation models Coders Coding Decoding Distortion Encoding-Decoding Ensemble learning Entropy coding Floating point arithmetic Geometric transformation Image coding Image compression Modal choice Optimization Rate-distortion rate-distortion optimization Transforms
ISSN:	1051-8215, 1558-2205
Online Access:	Get full text
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