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Proceedings Paper

Image deblurring by the combined use of a super-resolution technique and inverse filtering
Author(s): Yasuyuki Yamada; Koji Nakamae; Hiromu Fujioka
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Paper Abstract

We have tried to deblur the image by the combined use of a super-resolution technique (extrapolation by error energy reduction) and inverse filtering. The procedure is as follows. At first, the blurring function is estimated from an observed image. Then the Fourier transforms of the original image and the estimated blurring function are low-pass filtered by truncating their Fourier transforms to zero outside the specified interval. The bandlimited image is divided by the bandlimited blurring function to obtain the bandlimited estimated original image in the frequency domain (inverse filtering). By limiting the analysis to frequencies near the origin, we reduce the probability of encountering zero values in inverse filtering. Lastly, by applying the error energy reduction extrapolation method to the bandlimited estimated original image, we can estimate the original, deblurred image. We applied our proposed method to a model image with noise and a scanning electron microscope image. The quality of our results is superior to that of images restored with Wiener filtering technique.

Paper Details

Date Published: 2 February 2006
PDF: 8 pages
Proc. SPIE 6065, Computational Imaging IV, 60651C (2 February 2006); doi: 10.1117/12.642731
Show Author Affiliations
Yasuyuki Yamada, Osaka Univ. (Japan)
Koji Nakamae, Osaka Univ. (Japan)
Hiromu Fujioka, Fukui Univ. of Technology (Japan)


Published in SPIE Proceedings Vol. 6065:
Computational Imaging IV
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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