Ice Reconnaissance Data Processing Under Low Quality Source Images

نویسندگان

چکیده

The ice reconnaissance task is extremely important for maritime logistics in high latitudes as the results of its solution are basis development rational ship routes areas. intermediate result a huge corpus aerial survey data poor quality. Since amount high, it necessary to ensure maximum efficiency processing under low quality source images. paper considers issues highly efficient automation based on use machine learning methods. In particular, problem automatic classification sea-ice floe size distribution (FSD) type three-class model solved. case low-quality images considered, which usual situation meteorological conditions Far North. We have proposed new method FSD using methods quite effective processing. Also, an original feature space, ensured this method, was proposed. has shown testing Data Set, compiled from real (high blurriness, fuzziness, presence disturbances). developed algorithm multi-class SVM and undemanding computing resources, so can be placed onboard UAV.

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ژورنال

عنوان ژورنال: Lecture notes on data engineering and communications technologies

سال: 2023

ISSN: ['2367-4520', '2367-4512']

DOI: https://doi.org/10.1007/978-3-031-24434-6_3