Multispectral imaging (MI) techniques are being used very often to identify different properties of nature in several domains, going from precision agriculture to environmental studies, not to mention quality inspection of pharmaceutical production, art restoration, biochemistry, forensic sciences or geology, just to name some. Different implementations are commercially available from the industry and yet there is quite an interest from the scientific community to spread its use to the majority of society by means of cost effectiveness and ease of use for solutions. These devices make the most sense when combined with unmanned aerial vehicles (UAVs), going a step further and alleviating repetitive routines which could be strenuous if traditional methods were adopted. In this work, a low cost and modular solution for a multispectral camera is presented, based on the use of a single panchromatic complementary metal oxide semiconductor (CMOS) sensor combined with a rotating wheel of interchangeable band pass optic filters. The system is compatible with open source hardware permitting one to capture, process, store and/or transmit data if needed. In addition, a calibration and characterization methodology has been developed for the camera, allowing not only for quantifying its performance, but also able to characterize other CMOS sensors in the market in order to select the one that best suits the budget and application. The process was experimentally validated by mounting the camera in a Dji Matrice 600 UAV to uncover vegetation indices in a reduced area of palm trees plantation. Results are presented for the normalized difference vegetation index (NDVI) showing a generated colored map with the captured information.
Keywords: CMOS sensor; UAV; multispectral camera.