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Contourlet based multi-exposure image fusion with compensation for multi-dimensional camera shake
journal contributionposted on 2016-06-28, 14:56 authored by Sara Saravi, Eran Edirisinghe
Multi-exposure image fusion algorithms are used for enhancing the perceptual quality of an image captured by sensors of limited dynamic range by rendering multiple images captured at different exposure settings. One practical problem overlooked by existing algorithms is the compensation required for image deregistration due to possible multi-dimensional camera shake that results within the time gap of capturing the multiple exposure images. In our approach RANdom SAmple Consensus (RANSAC) algorithm is used to identify inliers of key-points identified by the Scale Invariant Feature Transform (SIFT) approach subsequently to the use of Coherent Point Drift (CPD) algorithm to register the images based on the selected set of key points. We provide experimental results on set of images with multi-dimensional (translational and rotational) to prove the proposed algorithm's capability to register and fuse multiple exposure images taken in the presence of camera shake providing subjectively enhanced output images.
- Mechanical, Electrical and Manufacturing Engineering
Published inVISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications
Pages182 - 185
CitationSARAVI, S. and EDIRISINGHE, E.A., 2012. Contourlet based multi-exposure image fusion with compensation for multi-dimensional camera shake. IN: Csurka, G. and Braz, J. (EDS.) Proceeding of the the International Conference on Computer Vision Theory and Applications, (VISAPP 2012), 1, pp. 182-185.
- AM (Accepted Manuscript)
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesThis is a conference paper.