Layered Image Compression Using Scalable Auto-Encoder

Chuanmin Jia, Zhaoyi Liu, Yao Wang, Siwei Ma, Wen Gao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a novel convolutional neural network (CNN) based image compression framework via scalable auto-encoder (SAE). Specifically, our SAE based deep image codec consists of hierarchical coding layers, each of which is an end-to-end optimized auto-encoder. The coarse image content and texture are encoded through the first (base) layer while the consecutive (enhance) layers iteratively code the pixel-level reconstruction errors between the original and former reconstructed images. The proposed SAE structure alleviates the need to train multiple models for different bit-rate points by recently proposed auto-encoder based codecs. The SAE layers can be combined to realize multiple rate points, or to produce a scalable stream. The proposed method has similar rate-distortion performance in the low-to-medium rate range as the state-of-the-art CNN based image codec (which uses different optimized networks to realize different bit rates) over a standard public image dataset. Furthermore, the proposed codec generates better perceptual quality in this bit rate range.

Original languageEnglish (US)
Title of host publicationProceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages431-436
Number of pages6
ISBN (Electronic)9781728111988
DOIs
StatePublished - Apr 22 2019
Event2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019 - San Jose, United States
Duration: Mar 28 2019Mar 30 2019

Publication series

NameProceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019

Conference

Conference2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019
CountryUnited States
CitySan Jose
Period3/28/193/30/19

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Keywords

  • CNN
  • end-to-end optimization
  • Image Compression
  • scalable auto-encoder

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Media Technology

Cite this

Jia, C., Liu, Z., Wang, Y., Ma, S., & Gao, W. (2019). Layered Image Compression Using Scalable Auto-Encoder. In Proceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019 (pp. 431-436). [8695403] (Proceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MIPR.2019.00087