Detection of Control Points for UAV-Multispectral Sensed Data Registration through the Combining of Feature Descriptors

摘要

The popularization of the Unmanned Aerial Vehicle (UAV) and the development of new sensors has enabled the acquisition and use of multispectral and hyperspectral images in precision agriculture. However, performing the image registration process is a complex task due to the lack of image characteristics among the various spectra and the distortions created by the use of the UAV during the acquisition process. Therefore, the objective of this work is to evaluate different techniques for obtaining control points in multispectral images of soybean plantations obtained by UAVs and to investigate if combining features obtained by different techniques generates better results than when used individually. In this work Were evaluated 3 different feature detection algorithms (KAZE, MEF and BRISK) and their combinations. Results shown that the KAZE technique, achieve better results.