Résumé: Image sensors are widely used in various applications. With the increasing requirement for high resolutions and frame rates, power consumption has become a critical issue, which limits the use of image sensors in mobile devices and IoT applications. Compressive sensing (CS) techniques can achieve a sub-Nyquist sampling rate to reduce the power consumption in hardware circuits. Currently, most compressive measurements are implemented in digital CMOS circuits, leading to high hardware complexity and power consumption, as well as the limited sampling speed. Furthermore, CS applications with large image sizes are usually based on block-wise methods, which require real-time rate controls during practical operations. In this article, we propose a memristor-based CS encoder that can be integrated with conventional image sensors to achieve high performance with low power consumption and hardware overheads. A self-adaptive compressing rate controlmechanism is also devised to maximize the performance of the proposed technique. Simulation results of wireless video streaming demonstrate the advantages of the proposed technique.

Langue: Anglais