LPMsDE: Multi-Scale Denoising and Enhancement Method Based on Laplacian Pyramid Framework for Forward-Looking Sonar Image

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成果类型：

期刊论文

作者：

Wang, Zhisen;Li, Zhuoyi;Teng, Xuanxuan;Chen, Deshan

通讯作者：

Chen, DS;Teng, XX

作者机构：

[Wang, Zhisen; Chen, Deshan] Wuhan Univ Technol, State Key Lab Maritime Technol & Safety, Wuhan 430063, Peoples R China.

[Wang, Zhisen; Chen, Deshan] Wuhan Univ Technol, Natl Engn Res Ctr Water Transport Safety, Wuhan 430063, Peoples R China.

[Li, Zhuoyi] Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China.

[Teng, Xuanxuan] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.

[Chen, Deshan] Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Peoples R China.

通讯机构：

[Teng, XX ; Chen, DS ] W

Wuhan Univ Technol, State Key Lab Maritime Technol & Safety, Wuhan 430063, Peoples R China.

Wuhan Univ Technol, Natl Engn Res Ctr Water Transport Safety, Wuhan 430063, Peoples R China.

Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.

Wuhan Univ Technol, Intelligent Transportat Syst Res Ctr, Wuhan 430063, Peoples R China.

语种：

英文

关键词：

Adaptation models;feature enhancement;forward-looking sonar;Image denoising;image denoising;Laplace equations;Laplacian pyramid;multi-scale analysis;Noise reduction;Optical filters;Sonar;Speckle;speckle noise

期刊：

IEEE ACCESS

ISSN：

2169-3536

年：

2023

卷：

页码：

132942-132954

DOI：

10.1109/ACCESS.2023.3335372

基金类别：

10.13039/501100012166-National Key Research and Development Program of China (Grant Number: 2023YFC3010803) 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 52272424) Key Research and Development Program of Hubei Province of China (Grant Number: 2023BCB123) Science Foundation of Educational Commission of Hubei Province of China (Grant Number: Q20191607) 10.13039/501100012226-Fundamental Research Funds for the Central Universities (Grant Number: WUT:2023IVB079)

机构署名：

本校为通讯机构

院系归属：

电气与电子工程学院

摘要：

Forward-looking sonar (FLS) images present various challenges in interpretation, recognition, and segmentation due to limitations like low resolution, speckle noise, and low contrast, making them more complex than optical images. Existing methods often focus solely on denoising or enhancement, neglecting the potential benefits of utilizing multi-scale features to create an integrated image processing approach. This paper introduces the Laplacian pyramid-based multi-scale denoising and enhancement (LPMsDE) method tailored for FLS images. The proposed method begins by presenting a novel multipli...

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LPMsDE: Multi-Scale Denoising and Enhancement Method Based on Laplacian Pyramid Framework for Forward-Looking Sonar Image

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