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Pixel wise coded aperture for new acquisition paradigms in CMOS Image Sensors based on active illumination

Technological challenge: New computing paradigms, circuits and technologies, incl. quantum (learn more)

Department: Département d'Optronique (LETI)

Laboratory: Laboratoire conception de Circuits Intégrés Intelligents pour l'image

Start Date: 01-10-2022

Location: Grenoble

CEA Code: SL-DRT-22-0494

Contact: arnaud.verdant@cea.fr

Active illumination combined with image sensors bring the opportunity to extract a large amount of features about the observed scene that are generally not reachable to standard image acquisition approaches. This modality is now largely spread in industrial computer vision, consumer electronics and medical imaging applications. However, major challenges still need to be solved to increase the performances of such devices, and many associated research questions need to be addressed, with respect to the choices of the modulation and measurement strategy, the sensor architecture, or the signal processing techniques to employ for data analysis. The goal of this thesis is to jointly address those issues by first proposing a simulation framework aiming at finding the best trade-offs between light modulation and signal reconstruction approaches. Then, developing the system that will best fit to the derived specifications according to typical scene characteristics (ballistic or diffuse light behavior, depth range and resolution, ambient light levels, light source interferences?) will be addressed. This thesis will be structured in two main parts. The first part will tend to define an exploration framework based on a combination of physical modeling, physical measurements and deep learning approaches. Based on this tool, the second part will be dedicated to the development of an image sensor architecture using the issued specifications. The PhD student will benefit during his 3-years thesis of the expertise and the scientific excellence of the CEA Leti to attend objectives with a high level of innovation through international patents and publications. The dynamic and autonomous candidate will have a master or Engineer degree, specialized in electrical engineering and signal processing. A good knowledge of circuit design CAD and programming tools will be important (Cadence, Matlab, Python) and some basics in optics will be appreciated.

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