Abstract
Blind restoration of aerial multipspectral images, through a sequential deconvolution scheme is addressed in this paper. The proposed scheme is composed of three successive optimized processes : image denoising followed by Point Spread Function (PSF) estimation and finally image restoration. First, an iterative denoising filter is applied and stopped at the iteration when an optimal estimation of the blurry image is obtained. Secondly, slighty TV (Total Variation) regularized PSF estimation is carried out on an almost noise free version of the blurry image. In order to keep unknown original image fixed during PSF estimation, shocked filtering of filtered image is efficiently considered. Thirdly, assuming the previously estimated PSF fixed, a TV-regularized deconvolution is performed on filtered image to give better estimation of original image. Regularization parameters are automatically tuned using regularization-scale relationship. Results obtained on aerial CASI and AISA Eagle multispectral images prove efficacy of the proposed scheme.
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Rahmani, P., Vozel, B., Chehdi, K. (2008). Sequential Blind PSF Estimation and Restoration of Aerial Multispectral Images. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_37
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DOI: https://doi.org/10.1007/978-3-540-88458-3_37
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