A Hybrid Layered Image Compressor with Deep-Learning Technique

Wei Cheng Lee, Chih Peng Chang, Wen Hsiao Peng, Hsueh Ming Hang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a detailed description of NCTU's proposal for learning-based image compression, in response to the JPEG AI Call for Evidence Challenge. The proposed compression system features a VVC intra codec as the base layer and a learning-based residual codec as the enhancement layer. The latter aims to refine the quality of the base layer via sending a latent residual signal. In particular, a base-layer-guided attention module is employed to focus the residual extraction on critical high-frequency areas. To reconstruct the image, this latent residual signal is combined with the base-layer output in a non-linear fashion by a neural-network-based synthesizer. The proposed method shows comparable rate-distortion performance to single-layer VVC intra in terms of common objective metrics, but presents better subjective quality particularly at high compression ratios in some cases. It consistently outperforms HEVC intra, JPEG 2000, and JPEG. The proposed system incurs 18M network parameters in 16-bit floating-point format. On average, the encoding of an image on Intel Xeon Gold 6154 takes about 13.5 minutes, with the VVC base layer dominating the encoding runtime. On the contrary, the decoding is dominated by the residual decoder and the synthesizer, requiring 31 seconds per image.

Original languageEnglish
Title of host publicationIEEE 22nd International Workshop on Multimedia Signal Processing, MMSP 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728193205
DOIs
StatePublished - 21 Sep 2020
Event22nd IEEE International Workshop on Multimedia Signal Processing, MMSP 2020 - Virtual, Tampere, Finland
Duration: 21 Sep 202024 Sep 2020

Publication series

NameIEEE 22nd International Workshop on Multimedia Signal Processing, MMSP 2020

Conference

Conference22nd IEEE International Workshop on Multimedia Signal Processing, MMSP 2020
CountryFinland
CityVirtual, Tampere
Period21/09/2024/09/20

Keywords

  • hybrid-based layered coding
  • learned image compression
  • residual coding
  • variable rate

Fingerprint Dive into the research topics of 'A Hybrid Layered Image Compressor with Deep-Learning Technique'. Together they form a unique fingerprint.

Cite this