De-speckling 2D-Discrete Wavelet Transform with Hard Threshold Stage

In this work, a new method is implemented for removing noise from gray scale image that depends on two-dimensional discrete wavelet transform and Threshold stage (hard threshold). This paper represents the algorithm to remove the speckle noise by using logarithm operation. This operation changes the...

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Bibliographic Details
Main Authors: Dhafer Hasan, Maha Abdul-Jabar, Zahraa Abed Al-Mokhtar
Format: Article
Language:English
Published: Mosul University 2012-07-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.mosuljournals.com/article_163674_c4f3b7049d41c0db8d44b13dc8e4c02e.pdf
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Summary:In this work, a new method is implemented for removing noise from gray scale image that depends on two-dimensional discrete wavelet transform and Threshold stage (hard threshold). This paper represents the algorithm to remove the speckle noise by using logarithm operation. This operation changes the multiplicative noise to additive noise. So that, the removing operation becomes easier. The Matlab program is used to build the Algorithm and measure the PSNR and other measurement criteria as (NMV, NV, NSD, ENL and PSNR) to study the effect of removing noise from corrupted image. The PSNR  reaches to 24dB which is very satisfactory result in the reconstructed image,  while the maximum value of ENL is 2.23 * 10<sup>6</sup>,  and the minimum value of NMV, NV, NSD which is equal to 6.79, 2.67*10<sup>-5</sup>, 46* 10<sup>-4 </sup>respectively gives a smoother and cleaner image. The universal Threshold is applied in high frequency coefficient (i.e. the LH, HL, and HH-sub band of image) to remove the speckle noise and the low frequency coefficient (LL-sub band of image) is still without any change.
ISSN:1815-4816
2311-7990