NDLI: An efficient sidescan sonar image denoising method based on a new roughness entropy fractal dimension

Content Provider	IEEE Xplore Digital Library
Author	Hsiao-Wen Tin Shao-Wei Leu Chan-Chuan Wen Shun-Hsyung Chang
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan (Hsiao-Wen Tin; Shao-Wei Leu) \|\| Dept. of Microelectron. Eng., Nat. Kaohsiung Marine Univ., Kaohsiung, Taiwan (Shun-Hsyung Chang) \|\| Dept. of Shipping Technol., Nat. Kaohsiung Marine Univ., Kaohsiung, Taiwan (Chan-Chuan Wen)
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 range-domain 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.
Sponsorship	Japan Council OE Chapt.
Starting Page	1
Ending Page	5
File Size	379570
Page Count	5
File Format	PDF
ISBN	9781467359481
e-ISBN	9781467359498
DOI	10.1109/UT.2013.6519840
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-03-05
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fractals Noise reduction Sonar Image coding PSNR Approximation methods Approximation algorithms wavelet acoustic noise denoising fractal fractal-wavelet denoising self-similarity side-scan sonar image denoising
Content Type	Text
Resource Type	Article

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