Blind Image Deblurring with FFT-ReLU Sparsity Prior

Autor:	Radi, Abdul Mohaimen Al, Majumder, Prothito Shovon, Khan, Md. Mosaddek
Rok vydání:	2024
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Blind image deblurring is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. It is a small data problem, since the key challenge lies in estimating the unknown degrees of blur from a single image or limited data, instead of learning from large datasets. The solution depends heavily on developing algorithms that effectively model the image degradation process. We introduce a method that leverages a prior which targets the blur kernel to achieve effective deblurring across a wide range of image types. In our extensive empirical analysis, our algorithm achieves results that are competitive with the state-of-the-art blind image deblurring algorithms, and it offers up to two times faster inference, making it a highly efficient solution. Comment: The first two authors have equal contributions to this work. The paper has 10 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2406.08344 Zobrazit plný text záznamu View this record from Arxiv