Multispectral imaging is a powerful tool that extends the capabilities of the human eye. However, multispectral imaging systems generally are expensive and bulky, and multiple exposures are needed. Here, we report the demonstration of a compact multispectral imaging system that uses vertical silicon nanowires to realize a filter array. Multiple filter functions covering visible to near-infrared (NIR) wavelengths are simultaneously defined in a single lithography step using a single material (silicon). Nanowires are then etched and embedded into polydimethylsiloxane (PDMS), thereby realizing a device with eight filter functions. By attaching it to a monochrome silicon image sensor, we successfully realize an all-silicon multispectral imaging system. We demonstrate visible and NIR imaging. We show that the latter is highly sensitive to vegetation and furthermore enables imaging through objects opaque to the eye.

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Multispectral imaging with vertical silicon nanowires

Spectral imaging is becoming increasingly interesting not only for agricultural use but also for industrial applications. Wavelengths in the near infrared (NIR) range, in particular, can be used for materials classification. However, sorting paper according to quality is a very difficult task due to the close similarities between the materials. This work describes the development of a unique industrial inline material sorting system which uses the spectral imaging technique. The main functional parts and the sensor unit are described in detail. Classification methods for cellulose-based materials such as pulp, paper and cardboard will be discussed, as will hardware requirements for the industrial use of spectral imaging solutions, including adjustment and calibration techniques. The description of the software design focuses on the classification speed required.

Industrial application for inline material sorting using hyperspectral imaging in the NIR range

Characterization of post-consumer polyolefin wastes by hyperspectral imaging for quality control in recycling processes

Classification of oat and groat kernels using NIR hyperspectral imaging

Multispectral image acquisition considerably improves color accuracy in comparison to RGB technology. A common multispectral camera design concept features a filter-wheel consisting of six or more optical bandpass filters. By shifting the filters sequentially into the optical path, the electromagnetic spectrum is acquired through the channels, thus making an approximate reconstruction of the spectrum feasible. However, since the optical filters exhibit different thicknesses, refraction indices and may not be aligned in a perfectly coplanar manner, geometric distortions occur in each spectral channel: The reconstructed RGB images thus show rainbow-like color fringes. To compensate for these, we analyze the optical path and derive a mathematical model of the distortions. Based on this model we present two different algorithms for compensation and show that the color fringes vanish completely after application of our algorithms. We also evaluate our compensation algorithms in terms of accuracy and execution time.

/pdf/multispectral-filter-wheel-cameras-geometric-distortion-5d1n9pj7yp.pdf

Multispectral Filter-Wheel Cameras: Geometric Distortion Model and Compensation Algorithms

Imaging spectrometry has mainly been a research tool, employing laboratory spectrographs and scientific cameras. This paper describes an add-on imaging spectrograph that provides a unique combination of high quality image in a small, rugged, industrial, easy-to-use component. The spectrograph is based on a prism/grating/prism (PGP) dispersing element which provides straight optical axis, astigmatism free image and polarization independent throughput. A volume holographic transmission grating is used for high efficiency (up to 70%). The tubular optomechanical construction of the spectrograph is stable and small, D30 x L110 mm with F/2.8 numerical aperture and 2/3 inch image size. Equipped with C-mounts, the spectrograph plugs between lens and area camera, converting the camera to a spectral line imaging system. The spectrograph allows the utilization of rapidly developing monochrome camera techniques, like high speed digital cameras, smart cameras and CMOS sensors, in color and spectral analytical applications. It is the first component available for upgrading existing industrial monochrome vision systems with color/spectral capability without the need to change the basic platform hardware and software. The spectrograph brings the accuracy of spectral colorimetry to industrial vision and overcomes the complex calibration that is needed when an RGB color camera is applied to colorimetric applications. Other applications include NIR imaging (up to 2500 nm), spectral microscopy, multichannel fiberoptics spectrometry and remote sensing.

Alberto Dall'Ava

Papers

Direct sight imaging spectrograph: a unique add-on component brings spectral imaging to industrial applications