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NASA NTRS2019

Tunable mid-wave infrared spectral filters based on GexSbyTez for multispectral imaging

The mid-wave infrared (MWIR) spectrum contains a wealth of invaluable information including the spectral ‘fingerprint’ of many chemical species and has applications in remote sensing and astronomical imaging. Traditionally, filtering for the MWIR is achieved by means of passive multilayer interference (dichroic) filters, Fabry-Perot-based micro-electro-mechanical system (MEMS) filters, liquid crystal tunable filters, and focal plane array (FPA) filters. For accurate multispectral imaging applications, these approaches suffer from various limitations such as: having moving parts; exhibiting slow response times, and; having limited spectral bandwidth / resolution. Recently, there has been significant interest toward ‘active’ spectral imaging technologies, whereby the ability to provide electrically tunable narrowband filtering—spanning the entire MWIR—is highly desirable. In this work we introduce a new spectral imaging technology, namely actively tunable optical transmission filters using the phase-change material (PCM) GexSbyTez (GST). The GST exhibits a large, reversible change in its refractive index across the MWIR upon a phase transition (from amorphous to crystalline). This refractive index modulation governs the filter’s optical characteristics. Through an optical stimulus or applied voltage—which changes the GST state from amorphous to crystalline—one can actively tune the filter with MHz speed. We incorporate GST into optimized guided mode resonance (GMR) and plasmonic nanohole array (PNA) device architectures, enabling <10nm spectral resolution and tunable operation across 3~5µm. Our proposed PCM-MWIR filter will be able to extract the maximum amount of ‘useful’ information within the atmosphere for remote Earth sensing measurements at operational speeds orders of magnitude faster than current airborne-based sensors. Moreover, it may enable affordable SmallSat-based MWIR instrumentation which is complimentary to other observation systems. The MISSE (Materials International Space Station Experiment-Flight Facility) experiment has been proposed as a testbed for a PCM-based tunable MWIR filter module to allow exposure of the module to the low Earth orbit space environment. This will provide valuable data regarding the robustness of the filter to withstand the radiation and atomic oxygen environment and allow assessment of the technology for use in space applications.

Kim, Hyun Jung↗
NASA NTRS2006

Spatial Resolution Characterization for AWiFS Multispectral Images

Within the framework of the Joint Agency Commercial Imagery Evaluation program, the National Aeronautics and Space Administration, the National Geospatial-Intelligence Agency, and the U.S. Geological Survey cooperate in the characterization of high-to-moderate-resolution commercial imagery of mutual interest. One of the systems involved in this effort is the Advanced Wide Field Sensor (AWiFS) onboard the Indian Remote Sensing (IRS) Reourcesat-1 satellite, IRS-P6. Spatial resolution of the AWiFS multispectral images was characterized by estimating the value of the system Modulation Transfer Function (MTF) at the Nyquist spatial frequency. The Nyquist frequency is defined as half the sampling frequency, and the sampling frequency is equal to the inverse of the ground sample distance. The MTF was calculated as a ratio of the Fourier transform of a profile across an AWiFS image of the Lake Pontchartrain Causeway Bridge and the Fourier transform of a profile across an idealized model of the bridge for each spectral band evaluated. The mean MTF value for the AWiFS imagery evaluated was estimated to be 0.1.

Blonski, Slawomir↗
NASA NTRSDate not supplied

Comparison of Multispectral Imaging and Traditional Fundoscopy in the Detection of Terrestrial Retinal and Optic Nerve Pathologies like those Encountered During and/or Immediately Following Long-Duration Spaceflight

INTRODUCTION: The purpose of this investigation was to evaluate if MultiColor Imaging (MCI) can replace color fundus photography (CFP) as a diagnostic screening tool during spaceflight. MCI significantly reduces crew time (approx. 115 minutes/session, 36 hours/year) by eliminating nominal on-orbit fundoscopy sessions, while also providing the option to capture a larger field of view (55 vs. 35). METHODS: A comprehensive PubMed literature search was conducted using the following key words: multicolor, multispectral, imaging, retina, choroid, optic nerve, optic disc, and papilledema. Publications were filtered based on optic nerve and chorioretinal pathologies matching those seen during or immediately after spaceflight: optic disc edema (ODE), cotton wool spots (CWS), retinal hemorrhage, pigment epithelial detachment (PED), and serous chorioretinopathy (SCR). In a separate effort, 44 multicolor images (30 abnormal) of terrestrial patients were graded and compared to corresponding color fundus images acquired at the Doheny Eye Centers and UCLA. RESULTS: The search identified 340 articles; 9 describing MCI in relevant pathologies, 6 comparing MCI to CFP. MCI is superior in detecting CWS (1 paper), PED (2 papers), retinal hemorrhages (2 papers), and choroidal folds (1 paper), and can better delineate extent or boundaries of subretinal fluid and identify areas of RPE damage in SCR (2 papers). On MCI, ODE was described as a hyperreflective ring with a green shift and indistinct disc margins, with equaldetectability as using CFP (3 papers). Grading at Doheny Eye Institute confirmed these findings. DISCUSSION: MCI can effectively detect all retinal and optic nerve findings detectable by CFP during and immediately post-spaceflight and represents a suitable replacement as an on-orbit diagnostic screening tool. Additionally, by eliminating the nominal on-orbit fundoscopy sessions, dozens of crew hours are spared per year by utilizing MCI.

Jorge Nagel↗
NASA NTRS1975

Joint pattern recognition/data compression concept for ERTS multispectral imaging

This paper describes a new technique which jointly applies clustering and source encoding concepts to obtain data compression. The cluster compression technique basically uses clustering to extract features from the measurement data set which are used to describe characteristics of the entire data set. In addition, the features may be used to approximate each individual measurement vector by forming a sequence of scalar numbers which define each measurement vector in terms of the cluster features. This sequence, called the feature map, is then efficiently represented by using source encoding concepts. A description of a practical cluster compression algorithm is given and experimental results are presented to show trade-offs and characteristics of various implementations. Examples are provided which demonstrate the application of cluster compression to multispectral image data of the Earth Resources Technology Satellite.

Hilbert, E. E.↗
NASA NTRS1991

Integration of visible-through microwave-range multispectral image data sets for geologic mapping

Multispectral remote sensing data sets collected during the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 in the southwestern U.S. were used to produce thematic image maps showing details of the surface geology. LANDSAT TM (Thematic Mapper) images were used to map the distribution of clays, carbonates, and iron oxides. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data were used to identify and map calcite, dolomite, sericite, hematite, and geothite, including mixtures. TIMS (Thermal Infrared Multispectral Scanner) data were used to map the distribution of igneous rock phases and carbonates based on their silica contents. AIRSAR (Airborne Synthetic Aperture Radar) data were used to map surface textures related to the scale of surface roughness. The AIRSAR also allowed identification of previously unmapped fault segments and structural control of lithology and minerology. Because all of the above data sets were geographically referenced, combination of different data types and direct comparison of the results with conventional field and laboratory data sets allowed improved geologic mapping of the test site.

Kruse, Fred A.↗
NASA NTRS1994

High spatial resolution telescopic multispectral imaging and spectroscopy of the Moon. 1: The Serenitatis/Tranquillitatis border region

The region of the moon near the border between Mare Serenitatis and Mare Tranquillitatis is one of the most geologically and compositionally complex areas of the nearside. The geologic history of this region has been shaped by impacts of widely-varying spatial scale and temporal occurrence, by volcanism of variable style and composition with time, and by limited tectonism. We have been studying this region as part of a larger multi remote sensing technique effort to understand the composition, morphology, geology, and stratigraphy of the moon at spatial scales of 2 km or less. The effort has been aided by the proximity of this area to the Apollo 11, 15, and 17 landing sites and by the occurrence of one of the primary lunar spectroscopic 'standard areas' within our scene (MS2). Here, some of the findings from the multispectral imaging and spectroscopy part of this effort are reported.

Bell, James F., III↗
NASA NTRS1971

A multispectral image sensor array.

A silicon monolithic multispectral photosensor device is described. Fabrication techniques and preliminary spectral response data are presented. The device is designed to meet small size and weight requirements and to impose a reduced load upon cooling systems in use on satellites.

Gerhard, G. C.↗
NASA NTRS1974

ERTS: A multispectral image analysis contribution for the geomorphological evaluation of southern Maracaibo Lake Basin

Multispectral analysis of ERTS-A images at scales of 1:1,000,000 and 1:500,000 has been conducted with conventional photointerpretation methods. Specific methods have been developed for the geomorphological analysis of southern Maracaibo Lake Basin which comprises part of the Venezuelan Andean Range, Perija Range, the Tachira gap and the Southern part of the Maracaibo Lake depression. A steplike analysis was conducted to separate macroforms, landscapes and relief units as well as drainage patterns and tectonic features, which permitted the delineation of tectonic provinces, stratigraphic units, geomorphologic units and geomorphologic positions. The geomorphologic synthesis obtained compares favorably with conventional analysis made on this area for accuracy of 1:100,000 scale, and in some features with details obtained through conventional analysis for accuracy of 1:15,000 and field work. Geomorphological units in the mountains were identified according to changes in tone, texture, forms orientation of interfluves and tectonic characteristics which control interfluvial disimetrics.

Salas, F.↗
NASA NTRS2003

Pancam: A Multispectral Imaging Investigation on the NASA 2003 Mars Exploration Rover Mission

One of the six science payload elements carried on each of the NASA Mars Exploration Rovers (MER; Figure 1) is the Panoramic Camera System, or Pancam. Pancam consists of three major components: a pair of digital CCD cameras, the Pancam Mast Assembly (PMA), and a radiometric calibration target. The PMA provides the azimuth and elevation actuation for the cameras as well as a 1.5 meter high vantage point from which to image. The calibration target provides a set of reference color and grayscale standards for calibration validation, and a shadow post for quantification of the direct vs. diffuse illumination of the scene. Pancam is a multispectral, stereoscopic, panoramic imaging system, with a field of regard provided by the PMA that extends across 360 of azimuth and from zenith to nadir, providing a complete view of the scene around the rover in up to 12 unique wavelengths. The major characteristics of Pancam are summarized.

J F Bell III↗
NASA NTRS1974

Implementation and evaluation of ILLIAC 4 algorithms for multispectral image processing

Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data analysis algorithms on a revolutionary computer, the Illiac 4, are reported. The effectiveness and efficiency of implementing the digital multispectral data analysis techniques for producing useful land use classifications from satellite collected data were demonstrated.

Swain, P. H.↗
NASA NTRS2003

Multispectral imaging system for contaminant detection

An automated inspection system for detecting digestive contaminants on food items as they are being processed for consumption includes a conveyor for transporting the food items, a light sealed enclosure which surrounds a portion of the conveyor, with a light source and a multispectral or hyperspectral digital imaging camera disposed within the enclosure. Operation of the conveyor, light source and camera are controlled by a central computer unit. Light reflected by the food items within the enclosure is detected in predetermined wavelength bands, and detected intensity values are analyzed to detect the presence of digestive contamination.

Poole, Gavin H.↗
NASA NTRS1972

Analysis of multispectral images simulating ERTS observations

Simulation studies of selected aircraft and spacecraft acquired images were initiated in response to anticipated desires of the user community for simulated imagery prior to launch of ERTS-A. Principal modes of simulation included: (1) areas of coverage comparable to ERTS; (2) spatial resolutions within these images similar to ERTS; (3) spectral responses analogous to that expected from each channel on both the return beam vidicon and multispectral scanner, leading to production of photographic images that should appear similar to those representing each band in the two sensors; and (4) runthroughs of several analytical techniques, such as color density slicing, color additive viewing, and computer-generated reflectance and surface temperature maps, by which ERTS data can be analyzed, interpreted, and applied. The two areas involved in the simulation study were Wyoming and the Chesapeake Bay region.

Short, N. M.↗
NASA NTRS1991

Multispectral Image Processing for Plants

The development of a machine vision system to monitor plant growth and health is one of three essential steps towards establishing an intelligent system capable of accurately assessing the state of a controlled ecological life support system for long-term space travel. Besides a network of sensors, simulators are needed to predict plant features, and artificial intelligence algorithms are needed to determine the state of a plant based life support system. Multispectral machine vision and image processing can be used to sense plant features, including health and nutritional status.

Miles, Gaines E.↗
NASA NTRS1990

Multispectral image fusion using neural networks

A prototype system is being developed to demonstrate the use of neural network hardware to fuse multispectral imagery. This system consists of a neural network IC on a motherboard, a circuit card assembly, and a set of software routines hosted by a PC-class computer. Research in support of this consists of neural network simulations fusing 4 to 7 bands of Landsat imagery and fusing (separately) multiple bands of synthetic imagery. The simulations, results, and a description of the prototype system are presented.

Kagel, J. H.↗
NASA NTRS1974

Implementation of ILLIAC 4 algorithms for multispectral image interpretation

Research has focused on the design and partial implementation of a comprehensive ILLIAC software system for computer-assisted interpretation of multispectral earth resources data such as that now collected by the Earth Resources Technology Satellite. Research suggests generally that the ILLIAC 4 should be as much as two orders of magnitude more cost effective than serial processing computers for digital interpretation of ERTS imagery via multivariate statistical classification techniques. The potential of the ARPA Network as a mechanism for interfacing geographically-dispersed users to an ILLIAC 4 image processing facility is discussed.

Ray, R. M.↗
NASA NTRS1974

Investigation related to multispectral imaging systems

A summary of technical progress made during a five year research program directed toward the development of operational information systems based on multispectral sensing and the use of these systems in earth-resource survey applications is presented. Efforts were undertaken during this program to: (1) improve the basic understanding of the many facets of multispectral remote sensing, (2) develop methods for improving the accuracy of information generated by remote sensing systems, (3) improve the efficiency of data processing and information extraction techniques to enhance the cost-effectiveness of remote sensing systems, (4) investigate additional problems having potential remote sensing solutions, and (5) apply the existing and developing technology for specific users and document and transfer that technology to the remote sensing community.

Nalepka, R. F.↗