Compression Artifacts Reduction by a Deep Convolutional Network
Chinese University of Hong Kong
Abstract
Lossy compression introduces complex compression artifacts, particularly the blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking artifacts and produce blurred output, or restores sharpened images that are accompanied with ringing effects. Inspired by the deep convolutional networks (DCN) on super-resolution, we formulate a compact and efficient network for seamless attenuation of different compression artifacts. We also demonstrate that a deeper model can be effectively trained with the features learned in a shallow network. Following a similar "easy to hard" idea, we systematically investigate several practical transfer settings and show the effectiveness of…
Citation impact
- FWCI
- 33.50
- Percentile
- 100%
- References
- 51
Authors
4Topics & keywords
- Compression artifact
- Ringing
- Computer science
- Lossy compression
- Artificial intelligence
- Benchmark (surveying)
- Reduction (mathematics)
- Compression (physics)
- Life below water