Multispectral imagery is a large domain with a number of practical applications: thermography and quality control in industry, food science, and agronomy. The main interest is to obtain spectral information of the objects for which a reflectance signal can be associated to physical, chemical, and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in visible and near infrared wavelengths. We first present a different kind of multispectral devices used for agronomic applications and then introduce an original multispectral acquisition system based on a single CCD. First results in laboratory are detailed, presenting a detection method using a neural network and in-field acquisitions and their results are shown. To improve the quality of weed detection, the spatial distribution of crops is used by a second method. Finally, the first works on merging are outlined.
This paper presents an algorithm specifically developed for filtering low frequency signals. The application is related to weed detection into aerial images where crop lines are detected as repetitive structures.
Theoretical bases of this work are presented first. Then, two methods are compared to select low frequency signals and their limitations are described.
A decomposition based on wavelet packet is used to combine advantages of both methods. This algorithm allows a high selectivity of low frequency signals with an interesting computation time. At last, a complete algorithm for weed/crop classification is explained and a few results are shown.
Multispectral imagery is a large domain with number of practical applications: thermography, quality control in industry, food science and agronomy, etc. The main interest is to obtain spectral information of the objects for which reflectance signal can be associated with physical, chemical and/or biological properties.
Agronomic applications of multispectral imagery generally involve the acquisition of several images in the wavelengths of visible and near infrared.
This paper will first present different kind of multispectral devices used for agronomic issues and will secondly introduce an original multispectral design based on a single CCD. Third, early results obtained for weed detection are presented.