Going far beyond RGB, detectors in new visible imaging system sense 36 different colors
| Spectral information from the same image is seen through a conventional three-color channel system (left) and through the new system developed at the University of Granada and the Politecnico de Milano (36 color channels, right, although not all are shown). (Image: University of Granada) |
Researchers at the University of Granada (Granada, Spain) and the Politecnico di Milano (Milan, Italy) have designed a multispectral imaging system capable of obtaining information from a total of 36 color channels, as opposed to the usual three-color image sensors.1
The scientists, from the Color Imaging Lab group at the Optics Department, University of Granada, have designed this new system using a new generation of sensors developed at the Politecnico di Milano in combination with a matrix of multispectral filters to improve their performance.
Intrinsic color sensing
The sensors, called transverse field detectors (TFDs), take advantage of a physical phenomenon in which which each photon penetrates at a different depth depending on its wavelength. "By collecting these photons at different depths on the silica surface of the sensor, the different channels of color can be separated without the necessity of filters," says the principal investigator, Miguel Ángel Martínez Domingo.
However, combining these TFDs with narrowband filters that simply sharpen each detector's spectral resolution further improves the TFD-based system's performance.
Conventional color sensors have an architecture that consists of a monochrome sensor covered with a layer of color filters -- commonly, red, green and blue (RGB). Such an architecture only extracts information from one of these three colors in each pixel within the image. To extract the information from the rest of colors in each pixel, it is necessary to apply algorithms that in most cases are among manufacturers' best-kept secrets.
Potential uses of the new TFD-based imagers with spectral-sharpening filters include assisted vehicle driving systems, identifying counterfeit bills and documents, and obtaining more accurate medical images than those provided by current systems.
Source: http://canal.ugr.es/index.php/information-and-communication-technologies/item/74220
REFERENCE:
1. Miguel A. Martínez et al., Applied Optics (2014); http://dx.doi.org/10.1364/AO.53.000C14