Novel Fractal-Wavelet Technique for Denoising Side-Scan Sonar Images

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38166

Title:	Novel Fractal-Wavelet Technique for Denoising Side-Scan Sonar Images
Authors:	FU-TAI WANG LEE, C.-Y. JENNY HSIAO-WEN TIN SHAO-WEI LEU CHAN-CHUAN WEN SHUN-HSYUNG CHANG
Contributors:	國立臺灣海洋大學：電機工程學系
Keywords:	side-scan sonar images Fractal dimension fractal-wavelet denoising image denoising image roughness self-similarity
Date:	2014
Issue Date:	2016-08-10T02:06:42Z
Publisher:	SIGNAL PROCESSING
Abstract:	Abstract: Side-scan signals collected from the seabed are constructed based on elements of bottom roughness, which vary in texture and in the time they are collected. Image denoising, A procedure used for extracting image texture information and removing or reducing as much noise as possible, is a difficult problem. This study proposes a denoising algorithm based on an elaborative approach for measuring image roughness as an alternative to the fractal-wavelet (FW) coding process. By using this approach, texture similarity can be effectively captured. Because roughness is a property used to qualify image texture and a fractal dimension (FD) can be used to indicate the degree of complexity of image roughness, this study proposed an approach, namely the roughness entropy FD (REFD) method, for measuring the distribution of roughness in an image. This study applied the REFD algorithm to the FW coding process as the REFD FW algorithm. The proposed denoising algorithm approximates the parts of a noise-free image by determining the similarity distance between the two REFD values of domain-range subtrees, discarding as much noise as possible. The minimal similarity distance is used to quantify the degree of texture similarity between domain-range subtrees. This study conducted experiments on three side-scan sonar images of an undersea pipeline that were captured in Taiwan using a Polaris camera in various configurations in order to investigate the corresponding quality of the images by using two error criteria: mean square error and the peak signal-to-noise ratio. The experimental results indicated that the REFD is useful for range-domain matching in an FW coder to approximate the experimental images effectively. The proposed REFD FW algorithm is adaptable in denoising side-scan sonar images, and the images are more visually appealing.
URI:	http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38166
Appears in Collections:	[電機工程學系] 期刊論文

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