Underwater Acoustic Image Denoising Using Stationary Wavelet Transform and Various Shrinkage Functions
Ravisankar, Priyadharsini (Sri Sivasubramanya Nadar College of Engineering)

Date:	2021
Abstract:	Underwater acoustic images are captured by sonar technology which uses sound as a source. The noise in the acoustic images may occur only during acquisition. These noises may be multiplicative in nature and cause serious effects on the images affecting their visual quality. Generally image denoising techniques that remove the noise from the images can use linear and non-linear filters. In this paper, wavelet based denoising method is used to reduce the noise from the images. The image is decomposed using Stationary Wavelet Transform (SWT) into low and high frequency components. The various shrinkage functions such as Visushrink and Sureshrink are used for selecting the threshold to remove the undesirable signals in the low frequency component. The high frequency components such as edges and corners are retained. Then the inverse SWT is used for reconstruction of denoised image by combining the modified low frequency components with the high frequency components. The performance measure Peak Signal to Noise Ratio (PSNR) is obtained for various wavelets such as Haar, Daubechies,Coiflet and by changing the thresholding methods.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Acoustic images ; Coiflet ; Daubachies ; Haar ; Stationary wavelet ; Sureshrink ; Visushrink ; Image analysis and processing ; Applications
Published in:	ELCVIA. Electronic letters on computer vision and image analysis, Vol. 20 Núm. 2 (2021) , p. 38-50 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1360
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/980000000994
DOI: 10.5565/rev/elcvia.1360

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