Open AccessA real-time semantic segmentation algorithm for aerial imagery
Author(s) -
Yu. B. Blokhinov,
В. А. Горбачев,
Y. O. Rakutin,
Andrey Nikitin
Publication year - 2018
Publication title -
kompʹûternaâ optika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.491
H-Index - 29
eISSN - 2412-6179
pISSN - 0134-2452
DOI - 10.18287/2412-6179-2018-42-1-141-148
Subject(s) - segmentation , artificial intelligence , computer science , terrain , modular design , computer vision , aerial image , pattern recognition (psychology) , scale space segmentation , image segmentation , pixel , image (mathematics) , geography , cartography , operating system
We propose a novel effective algorithm for real-time semantic segmentation of images that has the best accuracy in its class. Based on a comparative analysis of preliminary segmentation methods, methods for calculating attributes from image segments, as well as various algorithms of machine learning, the most effective methods in terms of their accuracy and performance are identified. Based on the research results, a modular near real-time algorithm of semantic segmentation is constructed. Training and testing is performed on the ISPRS Vaihingen collection of aerial photos of the visible and IR ranges, to which a pixel map of the terrain heights is attached. An original method for obtaining a normalized nDSM for the original DSM is proposed.