Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Multi-Frame Super-Resolution Without Priors(01. Izmir Institute of Technology, 2023) Özuysal, Mustafa; Özuysal, Mustafa; 03.04. Department of Computer Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThere are mainly two types of super-resolution methods: traditional methods and deep learning methods. While traditional methods define closed-form expressions with assumptions, deep learning methods rely on priors learned from data sets. However, both of them have disadvantages such as being too simple and having strong trust in priors. We focus on how to generate a high-resolution image using low-resolution images without priors by utilizing spatial hash encoding. We propose a grid-based super-resolution model using spatial hash encoding to map coordinate information into higher dimensional space. Our aim is to eliminate long training times and not rely on priors from data sets that are not able to cover all real-world scenarios. Therefore, our proposed model is able to do task- specific super-resolution without priors and eliminate potential hallucination effects caused by wrong priors.Master Thesis A Tool for Synthetic Evaluation of Active Calibration Algorithms(01. Izmir Institute of Technology, 2022) Özuysal, Mustafa; Özuysal, Mustafa; Özuysal, Mustafa; 03.04. Department of Computer Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyTo calibrate a camera, the choice of poses is very important and different angled poses can increase accuracy. Gathering those poses needs expert intuition in order to constrain all parameters accurately. There are various tools to help users calibrate the camera with its guidance. In this study, two successful calibration tools are tested. Both of them guide the user interactively to obtain the best poses. The first method tries to avoid singular poses and captures the poses that reduce the uncertainty of calibration. The second method uses a different approach. It uses the current calibration state to suggest the next pose. In the end, it verifies the parameters with the specified ones by the user. To test these two methods, ground truth data is needed. The ground truth data is obtained with the help of a 3D modeling program. The suggested poses are generated also with the modeling program and knowing the ground truth camera parameters given in the program, the results of the tools are compared.