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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Algorithms for solving tensor completion problem and its application for reconstruction of images</dc:title><dc:creator>Sekulović,	Una	(Avtor)
	</dc:creator><dc:creator>Zalar,	Aljaž	(Mentor)
	</dc:creator><dc:creator>Pock,	Thomas	(Komentor)
	</dc:creator><dc:subject>image reconstruction</dc:subject><dc:subject>tensor completion problem</dc:subject><dc:subject>patch-based algorithms</dc:subject><dc:subject>singular value decomposition</dc:subject><dc:description>The tensor completion problem asks to complete a partially known tensor such that the rank of the completion is the smallest possible. In this thesis, we present the mathematical background of six algorithms used to solve this problem (HaLRTC, T-SVD, WangLRTC, TNN, TNN_DCT, SPC). We implement and compare them in the area of image reconstruction. Focusing on the area of image reconstruction, we study the robustness of the algorithms, quality of the reconstruction and convergence times. To obtain good performance, we also employ image preprocessing techniques to decompose the image into smaller low-rank subimages, known as patches.</dc:description><dc:date>2024</dc:date><dc:date>2024-10-15 10:05:01</dc:date><dc:type>Magistrsko delo/naloga</dc:type><dc:identifier>163975</dc:identifier><dc:identifier>VisID: 37062</dc:identifier><dc:identifier>COBISS_ID: 215090691</dc:identifier><dc:language>sl</dc:language></metadata>
