Abstract
Point spread function (PSF) estimation, an essential part for image restoration, has no accurate estimation algorithm at present. Based on the wavelet theory, a new Gaussian PSF accurate estimation algorithm is put forward in this paper. Firstly, the blurred images are smoothed, and their noise is reduced. Secondly, wavelet with varied scales is transformed, after which the local maxima of the modulus of the wavelet are computed respectively. Thirdly, on the basis of the relation deduced in this paper among the local maxima of the modulus of the wavelet at different scales, Lipschitz exponent and variance, the variance of a Gaussian PSF is computed. The experimental result shows that the proposed algorithm has an accuracy rate as high as 95%, and is of great application value.
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© 2005 Springer-Verlag Berlin Heidelberg
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Tao, QC., He, XH., Deng, HB., Liu, Y., Zhao, J. (2005). Wavelet Transform Based Gaussian Point Spread Function Estimation. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_48
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DOI: https://doi.org/10.1007/11595755_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
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