We have assessed and reduced the particle count in coatings from a magnetron sputter coater used for production of optical coatings for applications in photonics and semiconductor industry. Results for particle levels in single layers from Al2O3, SiO2, Nb2O5, Ta2O5, and TiO2 showed semiconductor grade particle levels for the upgraded deposition system. Moreover, particle levels were also investigated for optical filter stacks deposited on bare Si, glass substrates and actual CMOS device wafers, which were used for the manufacturing of hyperspectral imaging (HSI) sensors. In all cases, low particle counts were detected in the optical filters as expected from the results obtained for the single layer. It could be shown that the coating on the device wafers had no negative impact on the production yield of the HSI sensors.
Snapshot multispectral mosaic imagers are based on optical filters monolithically integrated directly on top of a standard CMOS image sensor, extending the traditional Bayer color imaging concept to multi- or hyperspectral imaging without a need for dedicated fore-optics. This overcomes the requirement for spatial or spectral scanning during acquisition by sensing an entire multispectral data cube at one discrete point in time, enabling the multispectral acquisition of scenes containing movement. The use of CMOS process technology based, monolithically integrated optical filters further enables the qualities of compactness, low cost, high acquisition speed, a limited spectral crosstalk and a high degree of design flexibility, differentiating it from other snapshot spectral cameras. However, the use of CMOS process technology also introduces process variability leading to peak wavelength variations and challenges in repeatable sensor-to-sensor behavior. In this paper we introduce a new compact snapshot multispectral mosaic imager with an improved deposition process. The new snapshot imager has 16 bands covering a wavelength range of 460-600nm, with a resolution of 272x512pixels for each band. The deposition process is based on in-line optical monitoring, dynamically compensating the depositions to reach a targeted optical performance. By depositing on a full batch of wafers in parallel on a rotating spindle, wafer-to-wafer variability is further reduced. Filter performance repeatability is further maximized by an improved intra-wafer layer thickness uniformity. Combining this with a deposition process tuned for optical materials also enables more complex filter stacks, such as multiple cavity and high OD filters.
o allow for adoption of optical spectroscopy in mobile and consumer devices, truly miniaturized, low-cost, mass producible spectrometers are needed. We present such a miniature (4mm x 3.2mm x 3.3mm) LGA packaged CMOS spectrometer in the range of 650-900nm and 720-1000nm. It leverages a wafer-level patterned spectral filter technology. The devices include diffuse optics and integrated spectral calibration and embedded corrections processor for part-to-part stable and repeatable performance across input angles and temperature with 68dB dynamic range, 5nm spectral resolution and up to 70 spectra/s. The run-time spectral corrections allow for plug-and-play operation of the sensor, without any need for recalibration in the field. The sensor enables portable spectroscopic applications in smart agriculture, anti-counterfeit, food analysis and skin sensing. For example, the combination of high sensitivity and speed of the spectrometer enables high sampling rate measurement of PPG signals and accurate measurement of heart rate and blood oxygenation (SpO2).
This paper presents system-level analysis of a sensor capable of simultaneously acquiring both standard absorption based RGB color channels (400-700nm, ~75nm FWHM), as well as an additional NIR channel (central wavelength: ~808 nm, FWHM: ~30nm collimated light). Parallel acquisition of RGB and NIR info on the same CMOS image sensor is enabled by monolithic pixel-level integration of both a NIR pass thin film filter and NIR blocking filters for the RGB channels. This overcomes the need for a standard camera-level NIR blocking filter to remove the NIR leakage present in standard RGB absorption filters from ~700-1000nm. Such a camera-level NIR blocking filter would inhibit the acquisition of the NIR channel on the same sensor. Thin film filters do not operate in isolation. Rather, their performance is influenced by the system context in which they operate. The spectral distribution of light arriving at the photo diode is shaped a.o. by the illumination spectral profile, optical component transmission characteristics and sensor quantum efficiency. For example, knowledge of a low quantum efficiency (QE) of the CMOS image sensor above 800nm may reduce the filter’s blocking requirements and simplify the filter structure. Similarly, knowledge of the incoming light angularity as set by the objective lens’ F/# and exit pupil location may be taken into account during the thin film’s optimization. This paper demonstrates how knowledge of the application context can facilitate filter design and relax design trade-offs and presents experimental results.
This paper presents multispectral active gated imaging in relation to the transportation and security fields. Active gated imaging is based on a fast gated camera and pulsed illuminator, synchronized in the time domain to provide range based images. We have developed a multispectral pattern deposited on a gated CMOS Image Sensor (CIS) with a pulsed Near Infrared VCSEL module. This paper will cover the component-level description of the multispectral gated CIS including the camera and illuminator units. Furthermore, the design considerations and characterization results of the spectral filters are presented together with a newly developed image processing method.
Imec has developed a process for the monolithic integration of optical filters on top of CMOS image sensors, leading to compact, cost-efficient and faster hyperspectral cameras. Different prototype sensors are available, most notably a 600- 1000 nm line-scan imager, and two mosaic sensors: a 4x4 VIS (470-620 nm range) and a 5x5 VNIR (600-1000 nm). In response to the users’ demand for a single sensor able to cover both the VIS and NIR ranges, further developments have been made to enable more demanding applications. As a result, this paper presents the latest addition to imec’s family of monolithically-integrated hyperspectral sensors: a line scan sensor covering the range 470-900 nm. This new prototype sensor can acquire hyperspectral image cubes of 2048 pixels over 192 bands (128 bands for the 600- 900 nm range, and 64 bands for the 470-620 nm range) at 340 cubes per second for normal machine vision illumination levels.
Spectral imaging can reveal a lot of hidden details about the world around us, but is currently confined to laboratory environments due to the need for complex, costly and bulky cameras. Imec has developed a unique spectral sensor concept in which the spectral unit is monolithically integrated on top of a standard CMOS image sensor at wafer level, hence enabling the design of compact, low cost and high acquisition speed spectral cameras with a high design flexibility. This flexibility has previously been demonstrated by imec in the form of three spectral camera architectures: firstly a high spatial and spectral resolution scanning camera, secondly a multichannel snapshot multispectral camera and thirdly a per-pixel mosaic snapshot spectral camera. These snapshot spectral cameras sense an entire multispectral data cube at one discrete point in time, extending the domain of spectral imaging towards dynamic, video-rate applications. This paper describes the integration of our per-pixel mosaic snapshot spectral sensors inside a tiny, portable and extremely user-friendly camera. Our prototype demonstrator cameras can acquire multispectral image cubes, either of 272x512 pixels over 16 bands in the VIS (470-620nm) or of 217x409 pixels over 25 bands in the VNIR (600-900nm) at 170 cubes per second for normal machine vision illumination levels. The cameras themselves are extremely compact based on Ximea xiQ cameras, measuring only 26x26x30mm, and can be operated from a laptop-based USB3 connection, making them easily deployable in very diverse environments.
The adoption of spectral imaging by industry has so far been limited due to the lack of high speed, low cost and compact
spectral cameras. Moreover most state-of-the-art spectral cameras utilize some form of spatial or spectral scanning
during acquisition, making them ill-suited for analyzing dynamic scenes containing movement. This paper introduces a
novel snapshot multispectral imager concept based on optical filters monolithically integrated on top of a standard
CMOS image sensor. It overcomes the problems mentioned for scanning applications by snapshot acquisition, where an
entire multispectral data cube is sensed at one discrete point in time. This is enabled by depositing interference filters per
pixel directly on a CMOS image sensor, extending the traditional Bayer color imaging concept to multi- or hyperspectral
imaging without a need for dedicated fore-optics. The monolithic deposition leads to a high degree of design flexibility.
This enables systems ranging from application-specific, high spatial resolution cameras with 1 to 4 spectral filters, to
hyperspectral snapshot cameras at medium spatial resolutions and filters laid out in cells of 4x4 to 6x6 or more. Through
the use of monolithically integrated optical filters it further retains the qualities of compactness, low cost and high
acquisition speed, differentiating it from other snapshot spectral cameras.
Traditional spectral imaging cameras typically operate as pushbroom cameras by scanning a scene. This approach makes
such cameras well-suited for high spatial and spectral resolution scanning applications, such as remote sensing and
machine vision, but ill-suited for 2D scenes with free movement. This limitation can be overcome by single frame,
multispectral (here called snapshot) acquisition, where an entire three-dimensional multispectral data cube is sensed at
one discrete point in time and multiplexed on a 2D sensor.
Our snapshot multispectral imager is based on optical filters monolithically integrated on CMOS image sensors with
large layout flexibility. Using this flexibility, the filters are positioned on the sensor in a tiled layout, allowing trade-offs
between spatial and spectral resolution. At system-level, the filter layout is complemented by an optical sub-system
which duplicates the scene onto each filter tile. This optical sub-system and the tiled filter layout lead to a simple
mapping of 3D spectral cube data on the sensor, facilitating simple cube assembly. Therefore, the required image
processing consists of simple and highly parallelizable algorithms for reflectance and cube assembly, enabling real-time
acquisition of dynamic 2D scenes at low latencies. Moreover, through the use of monolithically integrated optical filters
the multispectral imager achieves the qualities of compactness, low cost and high acquisition speed, further
differentiating it from other snapshot spectral cameras. Our prototype camera can acquire multispectral image cubes of
256x256 pixels over 32 bands in the spectral range of 600-1000nm at 340 cubes per second for normal illumination
levels.
Although the potential of spectral imaging has been demonstrated in research environments, its adoption by industry has so far been limited due to the lack of high speed, low cost and compact spectral cameras. We have previously presented work to overcome this limitation by monolithically integrating optical interference filters on top of standard CMOS image sensors for high resolution pushbroom hyperspectral cameras. These cameras require a scanning of the scene and therefore introduce operator complexity due to the need for synchronization and alignment of the scanning to the camera. This typically leads to problems with motion blur, reduced SNR in high speed applications and detection latency and overall restricts the types of applications that can use this system. This paper introduces a novel snapshot multispectral imager concept based on optical filters monolithically integrated on top of a standard CMOS image sensor. By using monolithic integration for the dedicated, high quality spectral filters at its core, it enables the use of mass-produced fore-optics, reducing the total system cost. It overcomes the problems mentioned for scanning applications by snapshot acquisition, where an entire multispectral data cube is sensed at one discrete point in time. This is achieved by applying a novel, tiled filter layout and an optical sub-system which simultaneously duplicates the scene onto each filter tile. Through the use of monolithically integrated optical filters it retains the qualities of compactness, low cost and high acquisition speed, differentiating it from other snapshot spectral cameras based on heterogeneously integrated custom optics. Moreover, thanks to a simple cube assembly process, it enables real-time, low-latency operation. Our prototype camera can acquire multispectral image cubes of 256x256 pixels over 32 bands in the spectral range of 600-1000nm at a speed of about 30 cubes per second at daylight conditions up to 340 cubes per second at higher illumination levels as typically used in machine vision applications.
In this paper we present a technique to accurately build a 3D hyperspectral image cube from a 2D imager
overlaid with a wedge filter with up to hundreds of spectral bands, providing time-multiplexed data through
scanning. The correctness of the spectral curve of each pixel in the physical scene, being the combination of
its spectral information captured over different time stamps, is directly related to the alignment accuracy and
scanning sensitivity. To overcome the accumulated alignment errors from scanning inaccuracies, frequency-
dependent scaling from lens, spectral band separations and the imager’s spectral filter technology limitations,
we have designed a new image alignment algorithm based on Random Sample Consensus (RANSAC) model
fitting. It estimates many mechanical and optical system model parameters with image feature matching over
the spectral bands, ensuring high immunity against the spectral reflectance variations, noise, motion-blur, blur
etc. The estimated system model parameters are used to align the images captured over different bands in the
3D hypercube, reducing the average alignment error to 0.5 pixels, much below the alignment error obtained
with state-of-the-art techniques. The image feature correspondences between the images in different bands of
the same object are consistently produced, resulting in a hardware-software co-designed hyperspectral imager
system, conciliating high quality and correct spectral curve responses with low-cost.
Colony counting is a procedure used in microbiology laboratories for food quality monitoring, environmental
management, etc. Its purpose is to detect the level of contamination due to the presence and growth of bacteria, yeasts
and molds in a given product. Current automated counters require a tedious training and setup procedure per product and
bacteria type and do not cope well with diversity. This contrasts with the setting at microbiology laboratories, where a
wide variety of food and bacteria types have to be screened on a daily basis. To overcome the limitations of current
systems, we propose the use of hyperspectral imaging technology and examine the spectral variations induced by factors
such as illumination, bacteria type, food source and age and type of the agar. To this end, we perform experiments
making use of two alternative hyperspectral processing pipelines and compare our classification results to those yielded
by color imagery. Our results show that colony counting may be automated through the automatic recovery of the
illuminant power spectrum and reflectance. This is consistent with the notion that the recovery of the illuminant should
minimize the variations in the spectra due to reflections, shadows and other photometric artifacts. We also illustrate how,
with the reflectance at hand, the colonies can be counted making use of classical segmentation and classification
algorithms.
Although the potential of hyperspectral imaging has been demonstrated for several applications, using laboratory setups
in research environments, its adoption by industry has so far been limited due to the lack of high speed, low cost and
compact hyperspectral cameras. To bridge the gap between research and industry, we present a novel hyperspectral
sensor that integrates a wedge filter on top of a standard CMOS sensor. To enable the low-cost processing of a
microscopic wedge filter, we have introduced a design that is able to compensate for process variability. The result is a
compact and fast hyperspectral camera made with low-cost CMOS process technology. The current prototype camera
acquires 100 spectral bands over a spectral range from 560 nm to 1000 nm, with a spectral resolution better than 10 nm
and a spatial resolution of 2048 pixels per line. The speed is 180 frames per second at illumination levels as typically
used in machine vision. The prototype is a hyperspectral line scanner that acquires 16 lines per spectral band in parallel
on a 4 MPixel sensor. The theoretic line rate for this implementation is thus 2880 lines per second.
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