13 May 2016 Wavelet burst accumulation for turbulence mitigation
Jérôme Gilles, Stanley Osher
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Abstract
We investigate the extension of the recently proposed weighted Fourier burst accumulation (FBA) method into the wavelet domain. The purpose of FBA is to reconstruct a clean and sharp image from a sequence of blurred frames. This concept lies in the construction of weights to amplify dominant frequencies in the Fourier spectrum of each frame. The reconstructed image is then obtained by taking the inverse Fourier transform of the average of all processed spectra. We first suggest replacing the rigid registration step used in the original algorithm with a nonrigid registration in order to process sequences acquired through atmospheric turbulence. Second, we propose to work in a wavelet domain instead of the Fourier one. This leads us to the construction of two types of algorithms. Finally, we propose an alternative approach to replace the weighting idea by an approach promoting the sparsity in the used space. Several experiments are provided to illustrate the efficiency of the proposed methods.
© 2016 SPIE and IS&T 1017-9909/2016/$25.00 © 2016 SPIE and IS&T
Jérôme Gilles and Stanley Osher "Wavelet burst accumulation for turbulence mitigation," Journal of Electronic Imaging 25(3), 033003 (13 May 2016). https://doi.org/10.1117/1.JEI.25.3.033003
Published: 13 May 2016
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CITATIONS
Cited by 18 scholarly publications.
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KEYWORDS
Wavelets

Turbulence

Image registration

Image restoration

Image processing

Denoising

Convolution

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