Abstract
Multimodal images fusion has the potential to enrich the information gathered by multi-sensor plant phenotyping platforms. Fusion of images from multiple sources is, however, hampered by the technical lock of image registration. The aim of this paper is to provide a solution to the registration and fusion of multimodal wheat images in field conditions and at close range. Eight registration methods were tested on nadir wheat images acquired by a pair of red, green and blue (RGB) cameras, a thermal camera and a multispectral camera array. The most accurate method, relying on a local transformation, aligned the images with an average error of 2 mm but was not reliable for thermal images. More generally, the suggested registration method and the preprocesses necessary before fusion (plant mask erosion, pixel intensity averaging) would depend on the application. As a consequence, the main output of this study was to identify four registration-fusion strategies: (i) the REAL-TIME strategy solely based on the cameras’ positions, (ii) the FAST strategy suitable for all types of images tested, (iii) and (iv) the ACCURATE and HIGHLY ACCURATE strategies handling local distortion but unable to deal with images of very different natures. These suggestions are, however, limited to the methods compared in this study. Further research should investigate how recent cutting-edge registration methods would perform on the specific case of wheat canopy.
Highlights
In recent years, close-range multi-sensor platforms and vehicles have been developed for crop phenotyping in natural conditions
The multimodal cameras system consisted of a Micro-MCA multispectral cameras array (Tetracam Inc., Gainesville, FL, USA), two GO-5000C-USB RGB cameras (JAI A/S, Copenhagen, Denmark) and a PI640 thermal camera (Optris GmbH, Berlin, Germany)
The multispectral array consisted of six monochrome cameras equipped with 1280 × 1024 pixels
Summary
Close-range multi-sensor platforms and vehicles have been developed for crop phenotyping in natural conditions. The obvious interest of multi-sensor approaches lies in the ability to measure an increased number of pertinent traits. This is especially crucial when studying plant stresses whose symptoms are often complex and not determined by a single physiological or morphological component. For this reason, the philosophy for most modern field phenotyping platforms is to measure both physiological and morphological traits. The philosophy for most modern field phenotyping platforms is to measure both physiological and morphological traits Spectrometers and 2D imagers provide plant reflectance (visible, near infrared (NIR), thermal
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