Green Coding: Low-Complexity Learning-based Image/Video Coding
C.-C. Jay Kuo, University of Southern California
Abstract
Deep-learning-based coding (or deep coding in short) has attracted a lot of attention in recent years due to its superior rate-distortion (RD) performance. Yet, its huge computational complexity and model sizes are of concern in practical applications. An alternative learning-based coding, called green coding, has been intensively studied in my lab for the last two and half years. Green coding targets at a model size that is significantly smaller than that of deep coding. Furthermore, it has much lower decoding complexity than today’s advanced codecs such as HEVC and VVC. It is particularly attractive for mobile devices. Green coding uses multi-grids to capture short-, mid- and long-range correlations in images and adopts vector quantization (VQ) to leverage correlations between images. Extensive experiments are conducted to demonstrate the high RD performance and low complexity of green image coding. Its generalization to green video coding will also be discussed.
Biography
Dr. C.-C. Jay Kuo received his Ph.D. degree from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as William M. Hogue Professor, Distinguished Professor of Electrical and Computer Engineering and Computer Science, and Director of the Media Communications Laboratory. His research interests are in visual computing and communication. He is a Fellow of AAAS, NAI, IEEE and SPIE and an Academician of Academia Sinica.
Dr. Kuo has received numerous awards for his research contributions, including the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2019 IEEE Computer Society Edward J. McCluskey Technical Achievement Award, the 2019 IEEE Signal Processing Society Claude Shannon-Harry Nyquist Technical Achievement Award, the 72nd annual Technology and Engineering Emmy Award (2020), and the 2021 IEEE Circuits and Systems Society Charles A. Desoer Technical Achievement Award. Dr. Kuo was Editor-in-Chief for the IEEE Transactions on Information Forensics and Security (2012-2014) and the Journal of Visual Communication and Image Representation (1997-2011). He is currently the Editor-in-Chief for the APSIPA Trans. on Signal and Information Processing (2022-2023). He has guided 164 students to their PhD degrees and supervised 31 postdoctoral research fellows.