Comparison between Three Registration Methods in the Case of Non-Georeferenced Close Range of Multispectral Images
نویسندگان
چکیده
Cucumber powdery mildew, which is caused by Podosphaera xanthii, a major disease that has significant economic impact in cucumber greenhouse production. It necessary to develop non-invasive fast detection system for disease. Such will use multispectral imagery acquired at close range with camera attached mobile cart’s mechanic extension. This study evaluated three image registration methods applied non-georeferenced images over plants MicaSense® RedEdge camera. The of matching points was performed using Speeded-Up Robust Features (SURF), and outliers were removed the M-estimator Sample Consensus (MSAC) algorithm. Three geometric transformations (affine, similarity, projective) considered process. For each transformation, we mapped blue, green, red, NIR band into red-edge space computed root mean square error (RMSE pixel) estimate accuracy registration. Our results achieved an RMSE less than 1 pixel similarity affine 2 pixels projective whatever image. We determined best method corresponded transformation because RMSEs have Gaussian distribution all bands, but blue band.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2021
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs13030396