Full characterization of spatial coregistration errors and spatial resolution in spectral imagers.

For multi- and hyperspectral imagers, the integrity of the spectral information depends critically on the spatial coregistration between bands. There is at present no commonly accepted way to fully specify coregistration performance. This Letter shows how a relatively simple measurement technique can be used to form sharp images of the point spread function (PSF) in all bands, yielding information about spatial coregistration, as well as spatial resolution.

Imaging systems and applications: introduction to the feature.

Imaging systems have numerous applications in industrial, military, consumer, and medical settings. Assembling a complete imaging system requires the integration of optics, sensing, image processing, and display rendering. This issue features original research ranging from design of stimuli for human perception, optics applications, and image enhancement to novel imaging modalities in both color and infrared spectral imaging, gigapixel imaging as well as a systems perspective to imaging.

Compact camera for multispectral and conventional imaging based on patterned filters.

A multispectral camera concept is presented. The concept is based on using a patterned filter in the focal plane, combined with scanning of the field of view. The filter layout has stripes of different bandpass filters extending orthogonally to the scan direction.

Enhancing far-field thermal emission with thermal extraction.

The control of thermal radiation is of great current importance for applications such as energy conversions and radiative cooling. Here we show theoretically that the thermal emission of a finite-size blackbody emitter can be enhanced in a thermal extraction scheme, where one places the emitter in optical contact with an extraction device consisting of a transparent object, as long as both the emitter and the extraction device have an internal density of state higher than vacuum, and the extraction device has an area larger than the emitter and moreover has a geometry that enables light extraction. As an experimental demonstration of the thermal extraction scheme, we observe a four-fold enhancement of the far-field thermal emission of a carbon-black emitter having an emissivity of 0.

Pixel scaling in infrared focal plane arrays.

We discuss effects that arise in pixels of IR focal plane arrays (FPAs) when pixel size scales down to approach the wavelength of the incident radiation. To study these effects, we perform first-principles electromagnetic simulations of pixel structures based on a mercury-cadmium-telluride photoconductor for use in FPAs. Specifically, we calculate the pixel quantum efficiency and crosstalk as pixel size scales from 16 μm, which is in the range of current detectors, down to 0.

Information capacity as a figure of merit for spectral imagers: the trade-off between resolution and coregistration.

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.

An upper-bound metric for characterizing spectral and spatial coregistration errors in spectral imaging.

Coregistration errors in multi- and hyperspectral imaging sensors arise when the spatial sensitivity pattern differs between bands or when the spectral response varies across the field of view, potentially leading to large errors in the recorded image data. In imaging spectrometers, spectral and spatial offset errors are customarily specified as "smile" and "keystone" distortions. However these characteristics do not account for errors resulting from variations in point spread function shape or spectral bandwidth.

Sensor noise informed representation of hyperspectral data, with benefits for image storage and processing.

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.