NDLI: General generative model-based image compression method using an optimisation encoder

Content Provider	IET Digital Library
Author	Wu, Mengtian He, Zaixing Zhao, Xinyue Zhang, Shuyou
Abstract	Image compression is an intensively studied subject in computer vision. The deep generative model, especially generative adversarial networks (GANs), is a popular new direction for this subject. In this study, the authors propose a new compression method based on a generative model and focus on its application by GANs. The decoder in the proposed method is modified from the GAN generator model, which can produce visually real-like synthetic images. It is one of the two models in GANs, which is trained through a two-players' contest game. The encoder is an optimisation algorithm called backpropagation-to-the-input, which derives from an image inpainting algorithm based on generative models. In the proposed method, the authors turn the encoding process into an optimisation task to search for optimal encoded representations. Compared with traditional methods, the proposed method can compress images from certain domains into extremely small and shape-fixed encoded space but still retain better visual representations. It is easy and convenient to apply without any retraining or additional modification to the generative models.
Starting Page	1750
Ending Page	1758
Page Count	9
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 9, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0715
Journal	IET Image Processing
Publisher Date	2020-03-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Backpropagation Computer Vision Computer Vision And Image Processing Technique Data Compression Deep Generative Model Encoding Encoding Process Extremely Small Shape-fixed Encoded Space GAN Generator Model GANs General Generative Model-based Image Compression Method Generative Adversarial Network Generative Model Image And Video Coding Image Coding Image Inpainting Algorithm Image Restoration Intensively Studied Subject Optical, Image And Video Signal Processing Optimal Encoded Representations Optimisation Optimisation Algorithm Optimisation Encoder Optimisation Task Optimisation Technique Synthetic Image
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Generative adversarial networks model for visible watermark removal

Regional attention generative adversarial network

Computational complexity of fractal image compression algorithm

Adaptive low-complexity motion estimation algorithm for high efficiency video coding encoder

Model-based Lagrangian multiplier derivation method for depth map coding

Fast algorithm for HEVC intra-coding implemented by preprocessing

Fast generative adversarial networks model for masked image restoration

Siamese adversarial network for object tracking

Encoder-Driven Inpainting Strategy in Multiview Video Compression

General generative model-based image compression method using an optimisation encoder

Similar Documents

Generative adversarial networks model for visible watermark removal

Regional attention generative adversarial network

Computational complexity of fractal image compression algorithm

Adaptive low-complexity motion estimation algorithm for high efficiency video coding encoder

Model-based Lagrangian multiplier derivation method for depth map coding

Fast algorithm for HEVC intra-coding implemented by preprocessing

Fast generative adversarial networks model for masked image restoration

Siamese adversarial network for object tracking

Encoder-Driven Inpainting Strategy in Multiview Video Compression

General generative model-based image compression method using an optimisation encoder