Robotics and Computer Engineering - Master's theses

Selle kollektsiooni püsiv URIhttps://hdl.handle.net/10062/42116

Sirvi

Sirvi Robotics and Computer Engineering - Master's theses Märksõna "3D kuva" järgi

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    Experiment Design for a 3D Ghost Imaging Setup Utilizing a LinoSPAD Sensor
    (Tartu Ülikool, 2019) Bogdanov, Jan; Valdmann, Andreas, supervisor; Omelkov, Sergey, supervisor; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    High-resolution 3D-imaging is a rapidly developing field driven by the increasing sensing requirements of automation and robotics. Computational ghost imaging based 3Dimaging is an emerging technology, offering increased spatial resolution when compared to conventional 3D ash imaging systems. Usually, however, computational ghost imaging systems are characterized by their compromise between image acquisition times and image spatial resolution. This thesis presents a LinoSPAD line sensor based experiment design for a novel time of flight based 3D computational ghost imaging method. Contrary to single-pixel computational ghost imaging, where a single-pixel detector is used for imaging the entire scene, the proposed method utilizes a state-of-the-art prototype sensor array to divide the scene to be imaged between the detector's individual pixels' fields of view. This approach significantly reduces the system's image acquisition times while avoiding a reduction in its spatial resolution. Prior to developing a final design, the requirements for the light source and the spatial light modulator and the capabilities of the LinoSPAD sensor were analyzed. Furthermore, the design was complemented with photon budget calculations, shot noise and detector dead time simulations, and preliminary setup tests focusing on the triggering scheme of the design. The system's stringent timing requirements require the optimizing the parameters of triggering electronics in the experiment's implementation. Regardless, conducted tests and simulations confirm the feasibility of the experiment design for the novel 3D computational ghost imaging approach.