Computing-Enabled Imagers for Pervasive Computer Vision
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 20 August 2025 | Viewed by 2077
Special Issue Editor
Special Issue Information
Dear Colleagues,
Computer vision and its applications are ubiquitous in today’s technological era, with applications including computational photography, image super resolution, autonomous driving, AR/VR, medical diagnosis, robotics, space exploration, etc. Imaging technologies dominated by CMOS image sensors are often the generators of pixel-based data that are fed to computer vision (CV) algorithms. However, the extraordinary demand for CV applications and the associated explosion in data transfer and computational requirements has necessitated decentralized processing of CV workloads, starting at the source of pixel data, i.e., the imager sensor itself. Several approaches have recently been explored that include in-sensor and in-pixel computing, neural-network-embedded cameras, 3D sensing, time-of-flight sensors, compressive imaging, coded exposure pixels, high-speed, high-sensitivity cameras, and event-based dynamic vision sensors among others. These novel computing-enabled sensors are supported by new algorithms that are cognizant of the underlying camera hardware. This Special Issue aims to highlight the recent works in embedding computation inside imagers for a wide range of computer vision applications. The areas of interest include, but are not limited to:
- Processing-in-pixel;
- Processing-in-sensor;
- Time-of-flight sensors;
- Neuromorphic and bio-inspired imagers;
- High-speed imagers;
- 3D integrated cameras;
- Computational imagers;
- Coded exposure cameras;
- High-dynamic range cameras;
- Photon-counting imagers;
- Cameras for IoT and edge applications;
- Hardware-software co-design for application specific imagers.
Dr. Akhilesh Jaiswal
Guest Editor
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