Blind Image Deblurring with FFT-ReLU Sparsity Prior

• URL: http://arxiv.org/abs/2406.08344v3
• Date: Tue, 24 Sep 2024 20:01:29 GMT
• Title: Blind Image Deblurring with FFT-ReLU Sparsity Prior
• Authors: Abdul Mohaimen Al Radi, Prothito Shovon Majumder, Md. Mosaddek Khan,
• Abstract summary: Blind image deblurring is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. We introduce a method that leverages a prior which targets the blur kernel to achieve effective deblurring across a wide range of image types.
• Score: 1.179778723980276
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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