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Plug-And-Play Registration and Fusion

Unni, VS and Nair, P and Chaudhury, KN (2020) Plug-And-Play Registration and Fusion. In: Proceedings - International Conference on Image Processing, ICIP, 25-28 September 2020, Virtual, Abu Dhabi, pp. 2546-2550.

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Official URL: https://dx.doi.org/10.1109/ICIP40778.2020.9190847

Abstract

We consider the problem of synthetically fusing a high-spatial, low-spectral resolution image with a low-spatial, high-spectral resolution image to achieve high spatial and spectral resolution. In practice, the images to be fused are usually misaligned and need to be registered before fusion is carried out. However, due to significant difference in spatial resolutions (between the input images), it can be difficult to register them accurately. We consider a variational framework for simultaneous registration and fusion along with regularization that is built upon a standard observation (forward) model. Using a mix of alternating minimization and proximal gradient descent, we obtain an algorithm in which we iteratively optimize over rotations/translations, the model mismatch, and the regularization term. Motivated by the 'plug-and-play' paradigm for image restoration, we propose to replace (i) the alignment process by an efficient registration method, and (ii) the proximal map (of the regularizer) with a powerful denoiser. As the iterations proceed, we notice that better registration and regularization results in improved fusion. We demonstrate that our method is competitive with state-of-the-art fusion algorithms on standard datasets, and is particularly effective even for larger misalignments. © 2020 IEEE.

Item Type: Conference Paper
Publication: Proceedings - International Conference on Image Processing, ICIP
Publisher: IEEE Computer Society
Additional Information: cited By 0; Conference of 2020 IEEE International Conference on Image Processing, ICIP 2020 ; Conference Date: 25 September 2020 Through 28 September 2020; Conference Code:165772
Keywords: Alignment; Gradient methods; Spectral resolution, Alternating minimization; Fusion algorithms; Gradient descent; High spectral resolution images; Registration methods; Regularization terms; Spatial resolution; Variational framework, Image reconstruction
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 21 Jan 2021 06:46
Last Modified: 21 Jan 2021 06:46
URI: http://eprints.iisc.ac.in/id/eprint/67726

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