Last generation instrument for agriculture multispectral data collection

In recent years, the acquisition and analysis of multispectral data are gaining a growing interest and importance in agriculture. On the other hand, new technologies are opening up for the possibility of developing and implementing sensors with relatively small size and featuring high technical performances. Thanks to low weights and high signal to noise ratios, such sensors can be transported by different type of means (terrestrial as well as aerial vehicles), giving new opportunities for assessment and monitoring of several crops at different growing stages or health conditions. The choice and specialization of individual bands within the electromagnetic spectrum ranging from the ultraviolet to the infrared, plays a fundamental role in the definition of the so-called vegetation indices (eg. NDVI, GNDVI, SAVI, and dozens of others), posing new questions and challenges in their effective implementation. The present paper firstly discusses the needs of low-distance based sensors for indices calculation, then focuses on development of a new multispectral instrument specially developed for agricultural multispectral analysis. Such instrument features high frequency and high resolution imaging through nine different sensors (1 RGB and 8 monochromes with relative band-pass filters, covering the 390 to 950 nm range). The instrument allows synchronized multiband imaging thanks to integrated global shutter technology, with a frame rate up to 5 Hz; exposure time can be as low as 1/5000 s. An applicative case study is eventually reported on an area featuring different materials (organic and non-organic), to show the new instrument potential. Last generation instrument for agriculture multispectral data collection. Available from: https://www.researchgate.net/publication/317596952_Last_generation_instrument_for_agriculture_multispectral_data_collection [accessed Jul 11, 2017]

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

International audienceMultispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

Infrared system studies for the earth resource program Final report

Obtaining terrain surface temperatures from radiances measured in orbi

The effect of the color filter array layout choice on state-of-the-art demosaicing

Interpolation from a Color Filter Array (CFA) is the most common method for obtaining full color image data. Its success relies on the smart combination of a CFA and a demosaicing algorithm. Demosaicing on the one hand has been extensively studied. Algorithmic development in the past 20 years ranges from simple linear interpolation to modern neural-network-based (NN) approaches that encode the prior knowledge of millions of training images to fill in missing data in an inconspicious way. CFA design, on the other hand, is less well studied, although still recognized to strongly impact demosaicing performance. This is because demosaicing algorithms are typically limited to one particular CFA pattern, impeding straightforward CFA comparison. This is starting to change with newer classes of demosaicing that may be considered generic or CFA-agnostic. In this study, by comparing performance of two state-of-the-art generic algorithms, we evaluate the potential of modern CFA-demosaicing. We test the hypothesis that, with the increasing power of NN-based demosaicing, the influence of optimal CFA design on system performance decreases. This hypothesis is supported with the experimental results. Such a finding would herald the possibility of relaxing CFA requirements, providing more freedom in the CFA design choice and producing high-quality cameras

Characterization of color cross-talk of CCD detectors and its influence in multispectral quantitative phase imaging

Multi-spectral quantitative phase imaging (QPI) is an emerging imaging modality for wavelength dependent studies of several biological and industrial specimens. Simultaneous multi-spectral QPI is generally performed with color CCD cameras. However, color CCD cameras are suffered from the color crosstalk issue, which needed to be explored. Here, we present a new approach for accurately measuring the color crosstalk of 2D area detectors, without needing prior information about camera specifications. Color crosstalk of two different cameras commonly used in QPI, single chip CCD (1-CCD) and three chip CCD (3-CCD), is systematically studied and compared using compact interference microscopy. The influence of color crosstalk on the fringe width and the visibility of the monochromatic constituents corresponding to three color channels of white light interferogram are studied both through simulations and experiments. It is observed that presence of color crosstalk changes the fringe width and visibility over the imaging field of view. This leads to an unwanted non-uniform background error in the multi-spectral phase imaging of the specimens. It is demonstrated that the color crosstalk of the detector is the key limiting factor for phase measurement accuracy of simultaneous multi-spectral QPI systems.Comment: 16 pages, 8 figure