Abstract
To prevent the growth of weeds in precision farming, multispectral imaging has gained much interest for its ability to provide vegetation images with a high spectral resolution. However, spectral reflectance computation is an issue when the image is assembled from successive frames acquired under varying illumination conditions. In this study, we present a method to estimate reflectance from images acquired by a linescan camera in such conditions. Because rows in a given channel are associated to different illumination conditions, we process the image row-wise to improve reflectance estimation. Experimental segmentation results show that our method is a good candidate to effectively identify crops from weeds.
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