Remote Sensing Image Matching Algorithm for Coastal Zone Based on Local Features

• Published in: Journal of coastal research 2019-09, Vol.93 (sp1), p.723-728
• Main Authors: Li, Meiman, Xie, Wenfu
• Format: Article
• Language: English
• Subjects: coastal zone; Local features; MARINE ENVIRONMENT COMMUNICATION; matching; remote sensing image
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/SI93-100.1

Li, M. and Xie, W., 2019. Remote sensing image matching algorithm for coastal zone based on local features. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 723–728. Coconut Creek (Florida), ISSN 0749-0208. In order to improve the high resolution digital imaging ability of coastal remote sensing image, a pixel spatial fusion feature matching method based on local feature adaptive feature matching is proposed. The edge profile feature detection and pixel reconstruction model of coastal remote sensing image is constructed, and the multi-level feature decomposition and pixel region profile feature detection of coastal remote sensing image are carried out. The optimal high spatial resolution feature of coastal zone remote sensing image is extracted, and the high spatial edge profile feature extraction and block segmentation of coastal zone remote sensing image are carried out by using similarity information fusion and image region reconstruction methods. The target block matching and overlapping region high resolution reconstruction of coastal zone remote sensing image are carried out based on approximate sparse representation method, and the pixel spatial fusion feature matching of coastal zone remote sensing image is carried out under the constraint of high resolution. The simulation results show that the fusion degree of pixel spatial fusion feature matching of coastal remote sensing image is high, the reconstruction quality of image is good, the peak signal-to-noise ratio of output is high, the matching output quality of coastal remote sensing image is good, and it has good image resolution and detection ability.