Algorithms of the Objects’ Identification According to Hyperspectral Shooting of the „Resource-P“ Spacecraft

Liliya Demidova,Sergey Trukhanov

doi:10.1051/matecconf/20179903002

Abstract

The identification algorithms, which carry out the objects’ identification of the Earth’s surface by means of their hyperspectral features’ analysis, received on the base of the processed space images from the „Resource-P” spacecrafts with application of the similarity measures, have been considered. The identification algorithms on the base of the Euclidean distance similarity measure, the angular similarity measure and the fuzzy similarity measure have been applied. The use expediency of the fuzzy linear regression in the algorithm of objects’ hyperspectral features’ identification has been shown. The results of the hyperspectral information processing with using of the offered algorithms have been presented.

Highlights

The problem of processing and analysis of hyperspectral information formed on the base of hyperspectral images of the Earth’s surface presented by a big set of pictures of the same scene in the narrow adjoining spectral ranges received from a board of the spacecraft is one of the actual tasks solved by systems of Earth remote sensing
As the required we choose that standard hyperspectral features (HSF), for which fuzzy similarity measures’ value (17) is maximum
Further researches can be directed on reasonable attraction of new similarity measures for the solution of identification’s problem and improvement of aggregation algorithm of identification’s private results of objects’ HSF

Summary

Introduction

The problem of processing and analysis of hyperspectral information formed on the base of hyperspectral images of the Earth’s surface presented by a big set of pictures of the same scene in the narrow adjoining spectral ranges received from a board of the spacecraft is one of the actual tasks solved by systems of Earth remote sensing. Despite use at identification of a large number of the standard HSFs, results of identification with application of Euclidean distance similarity measure or angular similarity measure can be unsatisfactory In this regard it is expedient to carry out confirmation of identification’s result, which, in particular, can be received by means of application of other identification’s algorithms of object’s HSF with the subsequent aggregation of identification’s private results. As the required we choose that standard HSF, for which fuzzy similarity measures’ value (17) is maximum As it was already noted, for improvement of identification’s quality of the analyzed object’s HSF the aggregation realization of identification's private results (in one way or another) is necessary. After the visual comparative analysis of identification’s results of the analyzed object’s HSF by means of some best standard HSFs from the database received in the above way and presented both in text and in a graphic form, the software operator can make a final decision on compliance to the analyzed object’s HSF of some standard HSFs from the database

The experimental studies

Conclusions