Nowadays, there emerge a growing number of various types of display devices, such as mobile phone, pad, lap-top, etc, providing great convenience to us. It is natural to pose the following two questions. The first question is how to reliably and promptly assess visual perception, enhance image quality and recognize image content on typically used display devices. For example, how to design an excellent enhancement technology on screen content images according to the inspiration of those enhancement technologies that were well designed for natural scene images. The second question is how to devise a good display technology to make typically used display devices provide high-quality image/video signals on different external conditions. For example, how to design an excellent enhancement technology for automatically adjusting display parameters to make the devise better show the images to users. Those above two types of researches can help us to better perceive and understand image/video signals on certain display devices. This special issue solicits novel and high-quality papers to present reliable solutions and technologies of the above-mentioned problems. The topics of interest include, but are not limited to:
Quality assessment/enhancement/recognition technologies on screen content images, text images, scanned images and other typical display devices;
Display technologies based on OLEDs/Els, LCDs, PDPs, 3-D displays and virtual environment, projection displays/tiled screens, etc;
Advanced machine learning technologies for display technologies, such as few-shot learning, meta learning, self-supervised learning, contrastive learning, etc.
Applications of advanced display technologies for relevant researches, such as visual enhancement, quality perception, image segmentation, etc.
Manuscript submission: April 15, 2021
First-round peer review: May 15, 2021
First-round manuscript revision: June 30, 2021
Second-round peer review: July 15, 2021
Second-round manuscript revision: August 15, 2021
Final acceptance notification: August 30, 2021
Prof. Ke Gu, Beijing University of Technology, [email protected]/[email protected]
Dr. Xiongkuo Min, The University of Texas at Austin, [email protected]
Dr. Weiling Chen, Fuzhou University, [email protected]
Dr. Jiheng Wang, University of Waterloo, [email protected]