Efficient joint noise removal and multi exposure fusion

• URL: http://arxiv.org/abs/2112.03701v1
• Date: Sat, 4 Dec 2021 09:30:10 GMT
• Title: Efficient joint noise removal and multi exposure fusion
• Authors: A. Buades, J.L Lisani, O. Martorell
• Abstract summary: Multi-exposure fusion (MEF) is a technique for combining different images of the same scene acquired with different exposure settings into a single image. We propose a novel multi-exposure image fusion chain taking into account noise removal.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Multi-exposure fusion (MEF) is a technique for combining different images of the same scene acquired with different exposure settings into a single image. All the proposed MEF algorithms combine the set of images, somehow choosing from each one the part with better exposure. We propose a novel multi-exposure image fusion chain taking into account noise removal. The novel method takes advantage of DCT processing and the multi-image nature of the MEF problem. We propose a joint fusion and denoising strategy taking advantage of spatio-temporal patch selection and collaborative 3D thresholding. The overall strategy permits to denoise and fuse the set of images without the need of recovering each denoised exposure image, leading to a very efficient procedure.

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