Title:	SONAR IMAGE DENOISING BASED ON WAVELET TRANSFORM USING NON-LOCAL MEANS FILTERING
Author(s):	Su In Lee, Wan-Jin Kim and Kun Su Yoon
ISBN:	978-989-8533-79-1
Editors:	Katherine Blashki and Yingcai Xiao
Year:	2018
Edition:	Single
Keywords:	Image Denoising, Stationary Wavelet Transform, Non-local Means Filtering
Type:	Full Paper
First Page:	277
Last Page:	283
Language:	English
Cover:
Full Contents:	click to dowload
Paper Abstract:	Comparing to optical images, sonar images experience more severe conditions such as degradation, light scattering, low contrast, and blurring. To guarantee the performance of the post processing such as object detection and classification, the need of a proper denoising method for sonar images has claimed. Conventional wavelet transform(WT) domain denoising method may be good candidates but they do not properly work for some cases which have ambiguity in edge and noise separation. Since image blurring after denoising is generally caused by the loss of edge information with low signal-to-noise ratio, the denoising performance may be improved by the introduction of a proper edge decision rule. In this paper, we propose a stationary WT denoising method with edge map and non-local means(NLM) filter for edge decision. Experimental results show that the proposed method has better performance than the three conventional methods(Visushrink, Sureshrink, and Bayesshrink) in terms of the edge preservation and the peak signal-to-noise ratio.
	Go Back