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Image Restoration Based on Inverse Filtering Order and Power Spectrum Density
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 Title & Authors
Image Restoration Based on Inverse Filtering Order and Power Spectrum Density
Kim, Yong-Gil; Moon, Kyung-Il;
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In this paper, we suggest a approach which comprises fast Fourier transform inversion by wavelet noise attenuation. It represents an inverse filtering by adopting a factor into the Wiener filtering, and the optimal factor is chosen to minimize the overall mean squared error. in order to apply the Wiener filter, we have to compute the power spectrum of original image from the corrupted figure. Since the Wiener filtering contains the inverse filtering process, it expands the noise when the blurring filter is not invertible. To remove the large noises, the best is to remove the noise using wavelet threshold. Wavelet noise attenuation steps are consisted of inverse filtering and noise reduction by Wavelet functions. experimental results have not outperformed the other methods over the overall restoration performance.
Image restoration;Inverse filter;Power spectrum;Wiener filter;Wavelet transform;
 Cited by
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