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Hoye G.,Norwegian Defence Research Establishment FFI | Fridman A.,Norsk Elektro Optikk
Optics Express | Year: 2013

Current high-resolution push-broom hyperspectral cameras introduce keystone errors to the captured data. Efforts to correct these errors in hardware severely limit the optical design, in particular with respect to light throughput and spatial resolution, while at the same time the residual keystone often remains large. The mixel camera solves this problem by combining a hardware component - an array of light mixing chambers - with a mathematical method that restores the hyperspectral data to its keystone-free form, based on the data that was recorded onto the sensor with large keystone. A Virtual Camera software, that was developed specifically for this purpose, was used to compare the performance of the mixel camera to traditional cameras that correct keystone in hardware. The mixel camera can collect at least four times more light than most current high-resolution hyperspectral cameras, and simulations have shown that the mixel camera will be photon-noise limited - even in bright light - with a significantly improved signal-to-noise ratio compared to traditional cameras. A prototype has been built and is being tested. © 2013 Optical Society of America.

Hovland H.,Norwegian Defence Research Establishment FFI
Optics Express | Year: 2014

This work presents a novel imaging device based on tomographic reconstruction. Similar in certain aspects to the earlier presented tomographic scanning (TOSCA) principle, it provides several important enhancements. The device described generates a stream of onedimensional projections from a linear array of thin stripe detectors onto which the (circular) image of the scene is rotated. A two-dimensional image is then reproduced from the one-dimensional signals using tomographic processing techniques. A demonstrator is presented. Various aspects of the design and construction are discussed, and resulting images and movies are presented. ©2014 Optical Society of America

Skauli T.,Norwegian defence research establishment FFI
Optics Express | Year: 2011

Many types of hyperspectral image processing can benefit from knowledge of noise levels in the data, which can be derived from sensor physics. Surprisingly, such information is rarely provided or exploited. Usually, the image data are represented as radiance values, but this representation can lead to suboptimal results, for example in spectral difference metrics. Also, radiance data do not provide an appropriate baseline for calculation of image compression ratios. This paper defines two alternative representations of hyperspectral image data, aiming to make sensor noise accessible to image processing. A "corrected raw data" representation is proportional to the photoelectron count and can be processed like radiance data, while also offering simpler estimation of noise and somewhat more compact storage. A variance-stabilized representation is obtained by square-root transformation of the photodetector signal to make the noise signal-independent and constant across all bands while also reducing data volume by almost a factor 2. Then the data size is comparable to the fundamental information capacity of the sensor, giving a more appropriate measure of uncompressed data size. It is noted that the variance-stabilized representation has parallels in other fields of imaging. The alternative data representations provide an opportunity to reformulate hyperspectral processing algorithms to take actual sensor noise into account. © 2011 Optical Society of America.

Hanson T.,Norwegian Defence Research Establishment FFI
International Journal of Production Economics | Year: 2016

Most nations spend a considerable part of their gross domestic product (GDP) on defense. However, no previous study has addressed productivity and efficiency in the core area of the armed forces, operational units, using Data Envelopment Analysis (DEA). Introducing a model for the production process of an operational unit, productivity and efficiency are estimated by DEA for units of one branch of the Norwegian armed forces. Small samples are a characteristic of DEA studies in the military, and the public sector in general, resulting in nearly half of the units being estimated as fully efficient. We find that, by using the bootstrap technique to estimate confidence intervals, we can point to uncertainty in the estimates and reduce the number of candidates for best practice. © 2016 Elsevier B.V. All rights reserved. All rights reserved.

Skauli T.,Norwegian Defence Research Establishment FFI
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011

It is well known that in multi- and hyperspectral imaging, the spatial coregistration of bands is important for the quality of image data. In practice, all spectral imaging sensors exhibit some degree of coregistration error, so that in any given pixel, different bands have a somewhat different "footprint" in the scene. Such coregistration errors may be in the form of differences in the position, size and shape of the spatial responsivity distribution, here termed pixel response function (PRF). There appears to be no standardized way to quantify the combined effect of these errors. This paper proposes a common metric for different types of coregistration error. Basically, the metric is the integrated difference between the PRFs of two bands in a given pixel. It is shown that under reasonable assumptions, this metric reflects the worst-case error in the signal resulting from coregistration errors between the two bands. To specify the coregistration of multiple bands, or in multiple pixels, an aggregate metric can be defined. The metric may be used for design optimization and should also be experimentally measurable. Extension to spectral and temporal coregistration is briefly discussed. The metric is proposed as a standardized way to report the coregistration performance of spectral image sensors. © 2011 SPIE.

Hovland H.,Norwegian Defence Research Establishment FFI
Optics Express | Year: 2013

This work presents the first experimental demonstrator of an imager based on a tomographic scanning (TOSCA) principle. The device described generates a stream of multispectral images of a scene or target using simple conical scan optics and a simple patterned reticle, followed by collecting optics and one or several single pixel detectors. Tomographic processing techniques are then applied to the one-dimensional signals to reproduce two-dimensional images. Various aspects of the design and construction are described, and resulting images and movies are shown. © 2013 Optical Society of America.

Van Walree P.A.,Norwegian Defence Research Establishment FFI
IEEE Journal of Oceanic Engineering | Year: 2013

Systematic measurements were performed to characterize shallow-water acoustic propagation channels for applications in the field of underwater communications. The survey was conducted in northern Europe and covers the continental shelf, Norwegian fjords, a sheltered bay, a channel, and the Baltic Sea. The measurements were performed in various frequency bands between 2 and 32 kHz. The outcome of the study is a variety of channels that differ in many ways, defying any attempt to define a typical acoustic communication channel. Miscellaneous forward propagation effects are presented, which are relevant to channel models for the design of modulation schemes, network protocols, and simulation environments. © 2013 IEEE.

Hannevik T.N.A.,Norwegian Defence Research Establishment FFI
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

Norway's large ocean areas in the North require efficient methods to detect vessels in the High North. Radar satellites in orbit today offer dual- or quad-polarised data, which ease the task of detecting vessels in a SAR (Synthetic Aperture Radar) image. FFI has developed an automatic ship detection tool, AEGIR, which uses all polarisation channels to detect vessels. Combining the available channels increases the ship to sea contrast. 19 RADARSAT-2 quad-polarisation images have been run through AEGIR, and it showed that cross-polarisation and (HH-VV)*HV are best for ship detection for all incidence angels. HH-polarisation works well for high incidence angels. RADARSAT-2 offers new high resolution wide modes, which makes it possible to use high resolution and quad-pol images for operational ship detection. © 2012 IEEE.

Hovland H.,Norwegian Defence Research Establishment FFI
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

The tomographic scanner (TOSCA) detects signals using line detectors scanning a scene at regularly distributed angles. These line scan signals are then processed to reconstruct 2-dimensional images. In the simplest form, a 1-axis rotating conical scan optics scans across a simple patterned reticle, the signal collection being done with a single pixel detector. Experimental mono- and multispectral cameras using this approach are demonstrated under varying illumination conditions. Of particular interest is the TOSCA system's ability to handle and compensate for light sources modulated with a frequency higher than that of the frame rate. We also demonstrate for the first time a TOSCA imager operating in the infrared region. The device is put together using 3D-printed key parts and low cost optical components, leading to a very economical infrared camera. © 2014 SPIE.

Skauli T.,Norwegian Defence Research Establishment FFI
Applied Optics | Year: 2013

The performance of spectral imagers is customarily described by several characteristics including resolution, noise, and coregistration. These must be traded off against each other in a practical imager design. This paper proposes a way to use the information capacity, in an information-theoretic sense, as a figure of merit for spectral imagers. In particular, it is shown how a metric [Opt. Express 20, 918 (2012)] can be used to incorporate coregistration performance in a definition of total noise, which in turn can be used in the definition of information capacity. As an example, it is shown how the information capacity can be used to optimize the pixel size in a simple case that can be treated analytically. Generally, the information capacity is attractive as a fundamental, application-independent figure of merit for spectral imager optimization and benchmarking. © 2013 Optical Society of America.

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