Recent works have shown that learned models can achieve significant performance gains, especially in terms of perceptual quality measures, over traditional methods. Hence, the state of the art in image restoration and compression is getting redefined. This special issue covers the state of the art in learned image/video restoration and compression to promote further progress in innovative architectures and training methods for effective and efficient networks for image/video restoration and compression.
- Pub Date:
- February 2021
- Electrical Engineering and Systems Science - Image and Video Processing;
- Computer Science - Machine Learning
- IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, vol. 15, no. 2, FEBRUARY 2021