Recent Advances in Entropy Based Image Compression
- Resource Type
- Conference
- Authors
- Depoian, Arthur C.; Adams, Ethan; Kurz, Aidan; Bailey, Colleen P.; Guturu, Parthasarathy; Namuduri, Kamesh
- Source
- 2022 IEEE MetroCon MetroCon, 2022 IEEE. :1-3 Nov, 2022
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Transportation
Image coding
Transform coding
Artificial neural networks
Feature extraction
Entropy
Communications technology
Data communication
Image Compression
Image Coding
Neural Networks
Rate-Distortion
- Language
The future of image compression is abundant with the opportunities recently developed through the application of advanced neural network algorithms configured to take into account multiple image parameters. This progress has spurred on further progression into more complex architectures to extract the feature of the image for optimal compression. Of the many models available, this work tracks an evolution of end to end image compression by first analyzing BLS2017 and its successors, BMSHJ2018 and MS2020.