Multiscale Blind Image Restoration with a New Method

A new method, based on the normal shrink and modified version of Katssagelous and Lay, is proposed for multiscale blind image restoration. The method deals with the noise and blur in the images. It is shown that the normal shrink gives the highest S/N (signal to noise ratio) for image denoising process. The multiscale blind image restoration is divided in two sections. The first part of this paper proposes normal shrink for image denoising and the second part of paper proposes modified version of katssagelous and Lay for blur estimation and the combination of both methods to reach a multiscale blind image restoration.

Authors:

• Alireza Mallahzadeh
• Hamid Dehghani
• Iman Elyasi

Keywords:

• Multiscale blind image restoration
• image denoising
• blur estimation.

References:

[1] Hyuk Park ''Blind Image Restoration for MMW Radiometer Based On
Wavelet'' Techniques Gwangju Institute of Science and Technology
Korea 2005 IEEE.
[2] Paul s Addison ''The Illustrated Wavelet Transform Handbook''. Napier
University, Edinburgh, UK British library 2002.
[3] Sze-Ho ''Multiscale Blind Image Restoration Using A Wavelet
Decomposition'', Computer Engineering Georgia Institute 1996 IEEE.
[4] Mark. R. Banham ''Spatially Adaptive Wavelet-Based Multiscale Image
restoration'' IEEE transaction on Image Processing, Vol. 5, No. 4, April
1996.
[5] S. Grace Chang ''adaptive Wavelet Thresholding for Image denoising
and compression'' IEEE transactions on Image processing, Vol. 9, No. 9
September 2000.
[6] D. Kundur and D.Hatzinakos, ''Blind Image Deconvolution Revisited''
IEEE Signal Processing Magazine'', Vol.13, No.6, pp.61-63, Nov 1996.
[7] A.K. Katssagelous ''Digital Image Restoration'' New-York: springer-
Verlag.1991.
[8] Savita Gupta ''wavelet Based Image Compression Using Daubechies
Filter'', Bombay, NCC-2002.
[9] N M. Vatterli and J. Kovacevic, ''Wavelets and subband Coding''.
Englewood Cliffs, NJ, Prentice Hall, 1995.
[10] Lakhwinder Kaur and Savita Gupta and R.C.Chauhan, ''Image denoising
using wavelet thresholding''.punjab (148106), India.2003.
[11] A. K. Katssagelous and K. T. Lay, ''Maximum Likelihood Blur
Identification and Image restoration Using the EM algorithm'' .IEEE
Transactions on Signal Processing, Vol. 39, No.3, March 1991.