Range Imaging
Submission deadline: 2023-12-30
Section Collection Editors

Section Collection Information

Dear Colleagues,

Computational optical imaging is an interdisciplinary research direction of optical imaging and optimization algorithms, artificial intelligence, information theory and other disciplines, attracting more and more academic and industrial researchers' interest. With the development of computational optical imaging technology, human’s observation and perception abilities have gained new vitality in recent years. Computational optical imaging breaks through the limits of traditional optical imaging and will bring more creative and imaginative applications. It has attracted considerable attention due to its advantages, such as extensive information processing capacity, high-speed calculation, and good environmental adaptability.

Computational optical imaging technology integrates "computing" into any one or more links in the process of optical image formation. The formation of optical image is closely related to three factors: the lighting mode of the scene or object, the optical transfer function of the system, and the sampling of the image sensor. "Calculation" is usually embodied in the three links of lighting mode, transfer function and sampling in the form of coding. It can find various applications in security systems, remote sensing imaging, biomedical technology, and military scenarios.

Thus, we are interested in the innovative algorithm and system design in computational optical imaging, which includes the expansion of imaging elements, improvement of imaging performance, optimization of imaging system and adaptability of imaging environment. It is important to collect new mechanism, new algorithm and new problem to promote the development of computational optical imaging technology. Research articles and reviews in this area of study are welcome.

We look forward to receiving your contributions.

Prof. Dr. Lu Gao

Section Editors


Slice Imaging; Single-Pixel Imaging; Lensless Imaging; Ghost Imaging; Deep Learning Imaging; Super-Resolution Imaging; Multispectral Imaging

Published Paper