文献类型：期刊文献

英文题名：Noise-tolerant matched filter scheme supplemented with neural dynamics algorithm for sea island extraction

作者：Chen, Yiyu[1];Fu, Dongyang[1];Wang, Difeng[2];Huang, Haoen[3];Si, Yang[1];Du, Shangfeng[1]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang, Peoples R China;[2]Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou, Peoples R China;[3]Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan, Peoples R China

年份：2024

卷号：9

期号：4

起止页码：996

外文期刊名：CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY

收录：SCI-EXPANDED(收录号：WOS:001189532200001)、、EI(收录号：20241415839003)、Scopus(收录号：2-s2.0-85189074670)、WOS

基金：This research was funded in part by the National Key Research and Development Program of China under Grant 2022YFC3103101, Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory under Contract GML2021GD0809, National Natural Science Foundation of China under Contract 42206187, Key projects of the Guangdong Education Department under Grant 2023ZDZX4009. We thank all the anonymous reviewers who generously contributed their time and efforts. Their professional recommendations have greatly enhanced the quality of the manuscript.

语种：英文

外文关键词：edge detection; image classification; image recognition; shape extraction

外文摘要：Achieving high-precision extraction of sea islands from high-resolution satellite remote sensing images is crucial for effective resource development and sustainable management. Unfortunately, achieving such accuracy for sea island extraction presents significant challenges due to the presence of extensive background interference. A more widely applicable noise-tolerant matched filter (NTMF) scheme is proposed for sea island extraction based on the MF scheme. The NTMF scheme effectively suppresses the background interference, leading to more accurate and robust sea island extraction. To further enhance the accuracy and robustness of the NTMF scheme, a neural dynamics algorithm is supplemented that adds an error integration feedback term to counter noise interference during internal computer operations in practical applications. Several comparative experiments were conducted on various remote sensing images of sea islands under different noisy working conditions to demonstrate the superiority of the proposed neural dynamics algorithm-assisted NTMF scheme. These experiments confirm the advantages of using the NTMF scheme for sea island extraction with the assistance of neural dynamics algorithm.