Multispectral Imaging: Transverse-field-detector sensor has 36 color channels

Nov. 5, 2014
An international team of researchers has 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.

Researchers at the University of Granada (Spain) and the Politecnico di Milano (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 in 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 color filter arrays (CFAs) to improve their performance.

Depth-dependent color sensing

The sensors, called transverse field detectors (TFDs), take advantage of a physical phenomenon in 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 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 more spectral information from the colors in each pixel, it is necessary to apply algorithms that in most cases are among manufacturers’ best-kept secrets. In contrast, the TFD-CDA architecture allows detection of up to 36 “colors” (channels) without the use of such algorithms.

Because photons can penetrate deeper into silicon as their wavelength increases, photoelectrons at different depths are produced by light at different wavelengths. What the TFD has to do, then, is to sort the collection of generated electrons at different depths within the silicon so that multiple spectral channels can be separately collected. The TFD does this by varying the applied transverse electric field via a tunable bias voltage.

A TFD can retrieve up to five spectral channels, but two of these are in the near-IR; thus, the researchers decided for now to use only the three visible channels, leaving the near-IR region for future research. The spectral shift in each of these channels can be varied by bias, allowing finer capture of spectral information.

The CFA is made of an array of six different bandpass filters. This, in combination with the three initial channels and two different biasing conditions, results in the ability to get information from 36 channels (in two shots, one for each biasing condition).

Many different systems compared

The researchers chose the channels’ spectra based on a calculation called a voting principal feature analysis (VPFA). They then simulated many variants of the above system (“System 1”), mainly to see if System 1 was indeed the best arrangement. These versions included a TFD variant that had two polarization channels, an ordinary silicon sensor with a CFA optimized for it, variants using a scientific camera with filters mechanically switched in front of it, a system with channels chosen randomly instead of with VPFA, and numerous others (11 in all).

Experimentally, they compared their proposed system against those that had different CDAs, relied on polarization, or did not use VPFA. The results showed two systems (1 and 10) as the best, with System 1 winning out if the number of shots was increased. They also determined that the use of two polarization states of the TFD could slightly improve performance.

The TFD technology is still under development, with only prototypes having been made so far. 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.

REFERENCE
1. M. A. Martínez et al., Appl. Opt. (2014); doi:10.1364/AO.53.000C14.

About the Author

John Wallace | Senior Technical Editor (1998-2022)

John Wallace was with Laser Focus World for nearly 25 years, retiring in late June 2022. He obtained a bachelor's degree in mechanical engineering and physics at Rutgers University and a master's in optical engineering at the University of Rochester. Before becoming an editor, John worked as an engineer at RCA, Exxon, Eastman Kodak, and GCA Corporation.

Sponsored Recommendations

Melles Griot® XPLAN™ CCG Lens Series

March 19, 2024
IDEX Health & Science sets a new standard with our Melles Griot® XPLAN™ CCG Lens Series fluorescence microscope imaging systems. Access superior-quality optics with off-the-shelf...

Spatial Biology

March 19, 2024
Spatial Biology refers to the field that integrates spatial information into biological research, allowing for the study of biological systems in their native spatial context....

Custom-Engineered Optical Solutions for Your Application

March 19, 2024
We combine advanced optical design and manufacturing technology, with decades of experience in critical applications, to take you from first designs to ongoing marketplace success...

Semrock Optical Filters Resources

March 19, 2024
Looking for more information about Semrock optical filters? Explore sets by fluorophore, download the 2023 Semrock catalog and more.

Voice your opinion!

To join the conversation, and become an exclusive member of Laser Focus World, create an account today!