A Review on Wavelet Transform Based SONAR Image Denoising using Wavelet Thresholding

Abstract

Devices which use underwater sound for communication or observation are generally mentioned to as SONAR
system. Basic principle for SONAR image formation is transmission of pulse energy into water medium and subsequent
reception of any returned energy reflected from objects or seabed. But during this image formation considerable amount of
acoustic noise get added into sonar signals. The presence of acoustic noise distorts and degrades the accuracy of information
extracted from sonar images. Thus it is very essential to eliminate or reduce noise from sonar images before using those
images for various purposes. The main property of a good image denoising model is that it should completely remove noise
as far as possible as well as preserve edges. Discrete Wavelet Transform(DWT) is most powerful tool in image denoising.
One of the most popular method in wavelet domain is thresholding the wavelet coefficients (using the Hard threshold or the
Soft threshold) as introduced by Donoho. This paper presents a review of wavelet domain denoising techniques in non-linear
coefficient thresholding based methods. One of the key properties underlying the success of wavelet expansions tend to
concentrate the signal energy into a relatively small number of large coeffcients. This energy compaction property of the
wavelet transform makes the wavelet domain attractive for signal processing.