MULTISPEC 4C RESOLUTION FULL
Users should refer to the original published version of the material for the full abstract. Dcouvrez toutes les informations sur le produit : camra de surveillance multiSPEC 4C de la socit Airinov. No warranty is given about the accuracy of the copy. However, users may print, download, or email articles for individual use. Copyright of Precision Agriculture is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. Camera Sensor size Sensitivity Lens Resolution Panasonic Lumix GX7 17.3 x 13.0 mm 8 bit RGB Live MOS 20 mm 4592x3448 Airinov Multispec 4C 4 x 6x4.8 mm 10 bit G, R, RedEdge, NIR CMOS 4 mm 1280x960 TEAX TC 2.0 FLIR TAU2 640 10.88x8.
The comparison confirmed the ability of the model to assess vegetation-soil and crop-weed discrimination potential for specific sensors (such as the multiSPEC 4C sensor, AIRINOV, Paris, France), where the acquisition chain parameters can be tested. To compare the results with data from real images, the same classification was tested on multispectral images of a weed infested field. Classification between monocotyledonous and dicotyledonous plants requires pixels with a high vegetation rate: to obtain a probability to be correctly classified better than 80%, vegetation rates in the pixels have to be over 0.9. The results of soil-vegetation discrimination show that pixels with low vegetation rates can be classified as vegetation: pixels with vegetation rate greater than 0.5 had a probability to be correctly classified between 80 and 100%. The classification is unsupervised and based on the Mahalanobis distance computation. the ability to separate two classes) in soil and vegetation and in monocotyledon and dicotyledon classes is studied using simulations for different vegetation rates (defined as the proportion of vegetation covering the surface projected in the considered pixel). This can complement data acquired by the cameras above with visual real colour renderings. resolution (pixels/sensor) 12 mp (bayer) 4 sensors 0.4 mp 4 sensors 1.2 mp sensor dimensions mm 7.44 x 5.58 4.51 x 2.88 (per sensor) 4.8 x 3.6 (per sensor) pixel size m 1.33 3.75 gsd at 100 m agl 3. The spectral mixings in the pixels are modeled, based on an image with a 60 mm spatial resolution, to estimate the impact of the resolution on the ability to discriminate small plants. property canon s110 nir multispec 4c prototype multispec 4c commercial geom. A model is proposed in which the entire image acquisition chain is simulated in order to compute the digital values of image pixels according to several parameters (light, plant characteristics, optical filters, sensors.) to reproduce in-field acquisition conditions. Abstract: This study aimed to assess the spectral information potential of images captured with an unmanned aerial vehicle, in the context of crop-weed discrimination.
0 kommentar(er)
