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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Ali Kamil Ahmed
University of Technology
Computer Science & IT Electrical & Electronics Engineering

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Underwater Image De-nosing using Discrete Wavelet Transform and Pre-Whitening Filter Mohanad Najm Abdulwahed; Ali Kamil Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.9236

Abstract

Image denoising and improvement are essential processes in many underwater applications. Various scientific studies, including marine science and territorial defence, require underwater exploration. When it occurs underwater, noise power spectral density is inconsistent within a certain range of frequency, and the noise autocorrelation function is not a delta function. Therefore, underwater noise is characterised as coloured noise. In this study, a novel image denoising technique is proposed using discrete wavelet transform with different basis functions and a whitening filter, which converts coloured noise characteristics to white noise prior to the denoising process. Results of the proposed method depend on the following performance measures: peak signal-to-noise ratio (PSNR) and mean squared error. The results of different wavelet bases, such as Debauchies, biorthogonal and symlet, indicate that the denoising process that uses a pre-whitening filter produces more prominent images and better PSNR values than other methods.
Improved anti-noise attack ability of image encryption algorithm using de-noising technique Mohanad Najm Abdulwahed; Ali Kamil Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 6: December 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i6.16384

Abstract

Information security is considered as one of the important issues in the information age used to preserve the secret information through out transmissions in practical applications. With regard to image encryption, a lot of schemes related to information security were applied. Such approaches might be categorized into 2 domains; domain frequency and domain spatial. The presented work develops an encryption technique on the basis of conventional watermarking system with the use of singular value decomposition (SVD), discrete cosine transform (DCT), and discrete wavelet transform (DWT) together, the suggested DWT-DCT-SVD method has high robustness in comparison to the other conventional approaches and enhanced approach for having high robustness against Gaussian noise attacks with using denoising approach according to DWT. MSE in addition to the peak signal-to-noise ratio (PSNR) specified the performance measures which are the base of this study’s results, as they are showing that the algorithm utilized in this study has high robustness against Gaussian noise attacks.
Enhancement of DWT-SVD digital image watermarking against noise attack using time–frequency representation Mohanad Najm Abdulwahed; Ali Kamil Ahmed
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.5011

Abstract

Information security has been defined as one of the most critical issues in the information era, as it is utilized to protect confidential information during transfers in real-world applications. In the case of image encryption, a variety of information security approaches were used. Domain spatial and domain frequency are two domains in which such techniques can be classified. This study uses a combination of the singular value de-composition (SVD) and discrete wavelet transformation (DWT) to construct an encryption method based on a traditional watermarking system. Compared with other traditional methods, the proposed DWT-SVD approach has excellent robustness, and it has been strengthened for having high degree of the robustness against the additive white Gaussian noise (AWGN) attacks by utilizing a de-noising strategy based upon S-transform approach. Compared with DWT algorithm denoising approach, the results reveal that the S-transform denoising algorithm that has been deployed in the present article has a robust protection towards the Gaussian noise attack for mean squared error (MSE) around 0.005 and peak signal to noise ratio (PSNR) around 24 dB.
Co-Authors Mohanad Najm Abdulwahed