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Performance Analysis and Optimization of Nonlinear Image Restoration Techniques in Spatial Domain
Anil L. Wanare, Dilip D. Shah
Pages - 123 - 137     |    Revised - 15-03-2012     |    Published - 16-04-2012
Volume - 6   Issue - 2    |    Publication Date - April 2012  Table of Contents
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KEYWORDS
Nonlinear image restoration, Additive noise, Monochrome image denoising, Median with weight, Correlation distortion metrics
ABSTRACT
Abstract: This paper is concerned with critical performance analysis of spatial nonlinear restoration techniques for continuous tone images from various fields (Medical images, Natural images, and others images).The performance of the nonlinear restoration methods is provided with possible combination of various additive noises and images from diversified fields. Efficiency of nonlinear restoration techniques according to difference distortion and correlation distortion metrics is computed.Tests performed on monochrome images, with various synthetic and real-life degradations, without and with noise, in single frame scenarios, showed good results, both in subjective terms and in terms of the increase of signal to noise ratio(ISNR) measure. The comparison of the present approach with previous individual methods in terms of mean square error, peak signal-to-noise ratio, and normalised absolute error is also provided. In comparisons with other state of art methods, our approach yields better to optimization, and shows to be applicable to a much wider range of noises. We discuss how experimental results are useful to guide to select the effective combination. Promising performance analysed through computer simulation and compared to give critical analysis.
CITED BY (4)  
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2 Bedi, P., Bansal, R., & Sehgal, P. (2013). Using PSO in a spatial domain based image hiding scheme with distortion tolerance. Computers & Electrical Engineering, 39(2), 640-654.
3 Hatwar, S. K., Wanare, A. L., Shah, D. D., & Helonde, J. B. (2013). Performance Analysis and Automatic Selection of Restoration Techniques for Diversified Field Images. Digital Image Processing, 5(9), 422-427.
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Mr. Anil L. Wanare
G.H.Raisoni Institute of Engg. & Technology - India
a.wanare@rediffmail.com
Dr. Dilip D. Shah
GHRCEM,PUNE UNIVERSITY - India


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