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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38175

Title: An Efficient Sidescan Sonar Image Denoising Method Based on a New Roughness Entropy Fractal Dimension
Authors: 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
Date: 2013
Issue Date: 2016-08-10T02:45:48Z
Publisher: IEEE
Abstract: Abstract: This paper proposed a fractal-wavelet (FW)
denoising alternative based on applying texture analysis
technique to the fractal matching process. Texture has been
regarded as a similarity grouping in an image. Roughness is a
perceived property to describe the structural texture. This
paper applies the roughness entropy fractal dimension (REFD)
algorithm to FW coding process, as the REFD FW algorithm, in
finding each range subtree for the optimal matched domain
subtree according to the best possible minimal differential of
texture similarity measurements. It is believed that such
measurement would well capture the texture similarity.
The REFD FW algorithm denoises a side-scan sonar image
in such a way that the parts of noise-free image have to be
approximated as well as possible whereas the noisy parts are
discarded. The best possible minimal distance between the two
REFD values of domain-range subtrees is used to determine
which the best approximation is. The minimal similarity
distance quantifies the degree of texture similarity between
domain-range subtrees. The REFD FW algorithm have been
applied to two side-scan sonar images, one is the wreck of M.V.
Sea Angel which is taken by the Polaris, Taiwan, and the wreck
of a sailing schooner from MSTL, in different configurations to
investigate the corresponding quality of the images using two
error criteria: mean square error (MSE) and the peak signal to
noise ratio (PSNR). The experimental results indicate that the
REFD is appropriate as the criteria of determining rangedomain
matching in FW coder to well approximate the images.
We conclude that the REFD FW algorithm is adaptable in
denoising side-scan sonar image and that the images are more
appealing visually.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38175
Appears in Collections:[電機工程學系] 期刊論文

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