New-Tech Europe Magazine | Dec 2017

benefit from hyperspectral imaging. The applications include industrial parts inspection, specimen classification in medicine and biophysics, and, airborne remote sensing and military target detection. This article explains the two most common operating principles of hyperspectral cameras, and highlights the main applications in which they are typically used. Principles of Hyperspectral Cameras The spectral decomposition of light is traditionally achieved with a narrow slit in combination with dispersive optical elements. This technique allows high spectral accuracy, but results in an elaborate and complex optical setup inside the camera. This can lead to a large camera footprint, unreliable performance, and increased costs. In recent years, the advances in sensor design have enabled the implementation of precisely tuned narrow-band spectral filters at the pixel-level. While conventional color sensors have filter patterns with only three distinct broadband color channels, hyperspectral sensors have filter patterns that sample the full spectral range with a greater number of evenly distributed narrow band filters. Depending on the application, this range can span from the ultra-violet to the near-infrared spectrum, and might be significantly beyond the perception of the human eye. Hyperspectral cameras can be divided into two main categories, based on the characteristics of the filter pattern and the resulting operating modes: snapshot mosaic and pushbroom scanning. Both these modes impose different requirements on the application setup. Pushbroom Scanning The relative motion between the camera and the imaged object is often a natural requirement in many

Figure 1: Outline of the CMOSIS CMV2000 sensor with a narrow band filter pattern aligned with the sensor rows. Each spectral band covers an area given by the full width (2048 pixels) multiplied by 8 rows. The spectral range from 600nm to 1000nm is sampled with 100 spectral bands. The modified sensor is provided by IMEC and is implemented by a number of camera manufacturers. Image credits: XIMEA

vision applications. Typical examples include parts inspection on conveyor belts, remote sensing via aircraft or satellites, or autonomous agriculture via unmanned ground vehicles. These kinds of applications are best addressed with pushbroom-scanning hyperspectral cameras, in which contiguous pixel rows of the image sensor are coated with spectrally adjacent narrowband filters. The relative motion between the camera and the scenery causes the object to effectively drift over the image sensor. By synchronizing the sensor line read-out to the relative motion

speed, the scenery is imaged line by line; or, due to the row-wise filter coating of the sensor, one spectral band after the other. The full spectrum is obtained after the object has passed completely over the sensor. Therefore, on a two-dimensional area sensor, the pixel rows image one spatial dimension, while the columns capture the spectral dimension. The second spatial dimension is obtained from the relative motion of the camera and the scenery; termed the pushbroom scan. This working principle is illustrated in Figure 1. Typically, the number of spectral bands

Figure 2: Outline of the CMOSIS CMV2000 sensor with repetitive 4×4 pixels tiles. In each tile, the full spectral range between 465nm and 630nm is sampled with 16 spectral bands. The modified sensor is provided by IMEC and is implemented by a number of camera manufacturers. Image credits: XIMEA

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