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Yasin Yousif Al-Aboosi
University of Mustansiriyah
Computer Science & IT

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Error Performance Analysis in Underwater Acoustic Noise With Non-Gaussian Distribution Nor Shahida Mohd Shah; Yasin Yousif Al-Aboosi; Musatafa Sami Ahmed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.8001

Abstract

There is a high demand for underwater communication systems due to the increase in current social underwater activities. The assumption of Gaussian noise allows the use of Traditional communication systems. However, the non-Gaussian nature of underwater acoustic noise (UWAN) results in the poor performance of such systems. This study presents an experimental model for the noise of the acoustic underwater channel in tropical shallow water at Desaru beach on the eastern shore of Johor in Malaysia, on the South China Sea with the use of broadband hydrophones. A probability density function of the noise amplitude distribution is proposed and its parameters defined. Furthermore, an expression of the probability of symbol error for binary signalling is presented for the channel in order to verify the noise effect on the performance of underwater acoustic communication binary signalling systems.
Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation Yasin Yousif Al-Aboosi; Radhi Sehen Issa; Ali Khalid Jassim
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.14381

Abstract

In many applications, Image de-noising and improvement represent essential processes in presence of colored noise such that in underwater. Power spectral density of the noise is changeable within a definite frequency range, and autocorrelation noise function is does not like delta function. So, noise in underwater is characterized as colored noise. In this paper, a novel image de-noising method is proposed using multi-level noise power estimation in discrete wavelet transform with different basis functions. Peak signal to noise ratio (PSNR) and mean squared error represented performance measures that the results of this study depend on it. The results of various bases of wavelet such as: Daubechies (db), biorthogonal (bior.) and symlet (sym.), show that denoising process that uses in this method produces extra prominent images and improved values of PSNR than other methods.
Co-Authors Ali Khalid Jassim Musatafa Sami Ahmed Nor Shahida Mohd Shah Radhi Sehen Issa