Visible to the public Performance analysis of various wavelet thresholding techniques for despeckiling of sonar images

TitlePerformance analysis of various wavelet thresholding techniques for despeckiling of sonar images
Publication TypeConference Paper
Year of Publication2015
AuthorsSaurabh, A., Kumar, A., Anitha, U.
Conference Name2015 3rd International Conference on Signal Processing, Communication and Networking (ICSCN)
KeywordsBayes shrink, denoising, discrete wavelet transform, discrete wavelet transforms, DWT, DWT Thresholding techniques, Entropy, image denoising, Image edge detection, image processing, Image quality, image segmentation, image statistic, Neigh shrink, Noise, noise reduction, Performance analysis, pubcrawl170111, Quality metrics, Sonar image, sonar image despeckling, speckle, speckle noise, Vishnu shrink, wavelet thresholding technique
Abstract

Image Denoising nowadays is a great Challenge in the field of image processing. Since Discrete wavelet transform (DWT) is one of the powerful and perspective approaches in the area of image de noising. But fixing an optimal threshold is the key factor to determine the performance of denoising algorithm using (DWT). The optimal threshold can be estimated from the image statistics for getting better performance of denoising in terms of clarity or quality of the images. In this paper we analyzed various methods of denoising from the sonar image by using various thresholding methods (Vishnu Shrink, Bayes Shrink and Neigh Shrink) experimentally and compare the result in terms of various image quality parameters. (PSNR,MSE,SSIM and Entropy). The results of the proposed method show that there is an improvenment in the visual quality of sonar images by suppressing the speckle noise and retaining edge details.

DOI10.1109/ICSCN.2015.7219869
Citation Keysaurabh_performance_2015