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All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Theory on data processing and instrumentation

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Billingsley, F. C.↗
NASA NTRS1984

Advanced CID array multispectral pushbroom scanner

An optical imager, called the Scanning Imaging Spectroradiometer (SIS), was built for NASA in the early 1970's. Later, the Solidstate Array Spectroradiometer (SAS) was developed on the basis on a substitution of a Charge Injection Device (CID) array for the vidicon of the SIS. The Advanced Solidstate Array Spectroradiometer (ASAS) represents an improvement of the SAS. ASAS is a solidstate multispectral optical imaging radiometer which is currently the most versatile instrument of its type in the visible part of the spectrum. The instrument is capable of absolute radiometric measurements in all of its 32 bands. ASAS can be easily mounted in small aircraft as well as high altitude craft such as the U-2, taking into account also the possibility of a use in the Space Shuttle. The instrument consists of three separate subsystems. Attention is given to the optics, the detector array, data storage, data retrieval, and system performance.

Stewart, S. E.↗
NASA NTRS1993

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Jaggi, S.↗
NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗
NASA NTRS1987

Enhanced LANDSAT images of Antarctica and planetary exploration

Since early in the LANDSAT program, black-and-white paper prints of band 7 (near infrared) of the LANDSAT multispectral scanner have been used extensively to prepare semicontrolled maps of Antarctica. Image-processing techniques are now employed to enhance fine detail and to make controlled image-mosaic maps in color. LANDSAT multispectral images of Antarctica help to expand our knowledge of extraterrestrial bodies by showing bare-ice areas as bright blue patches; on such patches meteorites tend to be concentrated and are collected. Many subtle flow features in Antarctic ice streams resemble features at the mouths of Martian outflow channels, which suggests that the channels also contained ice. Furthermore, flow lines in Antarctic ice sheets that merge with ice shelves resemble Martian flow features associated with dissected terrain along the Martian northern highland margin, and support the concept that ice was involved in the transport of material from the southern highlands to the northern lowland plains. In Antarctica, as on Mars, the virtual absence of fluvial activity over millions of years has permitted the growth of glacial and eolian features to unusually large sizes.

Lucchitta, B. K.↗
NASA NTRS2002

Radiometric Characterization of IKONOS Multispectral Imagery

A radiometric characterization of Space Imaging's IKONOS 4-m multispectral imagery has been performed by a NASA funded team from the John C. Stennis Space Center (SSC), the University of Arizona Remote Sensing Group (UARSG), and South Dakota State University (SDSU). Both intrinsic radiometry and the effects of Space Imaging processing on radiometry were investigated. Relative radiometry was examined with uniform Antarctic and Saharan sites. Absolute radiometric calibration was performed using reflectance-based vicarious calibration methods on several uniform sites imaged by IKONOS, coincident with ground-based surface and atmospheric measurements. Ground-based data and the IKONOS spectral response function served as input to radiative transfer codes to generate a Top-of-Atmosphere radiance estimate. Calibration coefficients derived from each vicarious calibration were combined to generate an IKONOS radiometric gain coefficient for each multispectral band assuming a linear response over the full dynamic range of the instrument. These calibration coefficients were made available to Space Imaging, which subsequently adopted them by updating its initial set of calibration coefficients. IKONOS imagery procured through the NASA Scientific Data Purchase program is processed with or without a Modulation Transfer Function Compensation kernel. The radiometric effects of this kernel on various scene types was also investigated. All imagery characterized was procured through the NASA Scientific Data Purchase program.

Pagnutti, Mary↗
NASA NTRS1976

Geometric assessment of image quality using digital image registration techniques

Image registration techniques were developed to perform a geometric quality assessment of multispectral and multitemporal image pairs. Based upon LANDSAT tapes, accuracies to a small fraction of a pixel were demonstrated. Because it is insensitive to the choice of registration areas, the technique is well suited to performance in an automatic system. It may be implemented at megapixel-per-second rates using a commercial minicomputer in combination with a special purpose digital preprocessor.

Tisdale, G. E.↗
NASA NTRS2001

Spatial/Spectral Identification of Endmembers from AVIRIS Data using Mathematical Morphology

During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Plaza, Antonio↗
NASA NTRS2012

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

Le Moigne, Jacqueline↗
NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗
NASA NTRS2001

In-Flight Edge Response Measurements for High Spatial Resolution Remote Sensing Systems

In-flight measurement of spatial resolution were conducted as part of the ASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. Characterization included remote sensing systems with ground sample distance (GSD) of 1 meter or less, such as the panchromatic imager on-board the ICONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effect of both the image acquisition system (e.g., optics, electronics, motion, jitter, atmosphere) and image post-processing (e.g., resampling, modulation trasfer function (MTF) compensator). Spatial resolution was characterized by full width at half maximum (FWHM) of an edge response-derived line spread function. This was found to be a more robust measure of spatial resolution than the value of NTF at Nyquist frequency The edge responses were analysed using the tilted-edge technique that ovecomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as traps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. Numerous edge target images were analyzed for each of the tested sensors. The effect of such factors as acquisition geometry, temporal variability, MTF compensation, and GSD on spatial resolution were investigated.

Blonski, Slawomir↗
NASA NTRS1983

Preliminary airborne imaging spectrometer vegetation data

An airborne, pushbroom-style multispectral (1.2-2.4 micron) imaging sensor system known as Airborne Imaging Spectrometer (AIS) has been flown over the Pico Anticline region of the Santa Susana Mountains, California (U.S.A.). Initial interpretation of preliminary data sets suggest that the high spectral resolution data from AIS provide superior vegetation discrimination and mapping capabilities when compared with other imaging systems (MSS, TMS). AIS spectral data may also contain information concerning the state of health of both native and cultivated vegetation. Such capabilities (discrimination, mapping, and assessment of state of health) will be most useful in geobotanical assessment of this and other areas.

Rock, B. N.↗
NASA NTRS1990

Regional aeolian dynamics and sand mixing in the Gran Desierto - Evidence from Landsat Thematic Mapper images

Mesoscale mapping of spatial variations in sand composition of the Gran Desierto (Sonora, Mexico) was carried out on multispectral Landsat TM images of this region, making it possible to examine the dynamic development of sand sheets and dunes. Compositions determined from remote imagery were found to agree well with samples from selected areas. The sand populations delineated were used to describe the sediment source areas, transport paths, and deposition sites. The image analysis revealed important compositional variations aver large areas that were not readily apparent in the field data.

Blount, Grady↗
NASA NTRS1986

Present and future uses of AVHRR multispectral data

The present series of NOAA LEO satellites became operational in October 1978. Since then, four additional satellites have been launched in this series and three more are in fabrication. Planning is underway for at least three more. The AVHRR is a prime imaging sensor on these satellites. It is a multispectral imaging radiometer which has evolved in both function and the use of its data products. Investigators in a wide variety of disciplines are finding the readily available, high quality, moderate-resolution data useful in their studies.

Koczor, R. J.↗
NASA NTRS1988

Planetary optical and infrared imaging

The purpose of this investigation is to obtain and analyze high spatial resolution charge coupled device (CCD) coronagraphic images of extra-solar planetary material and solar system objects. These data will provide information on the distribution of planetary and proto-planetary material around nearby stars leading to a better understanding of the origin and evolution of the solar system. Imaging within our solar system will provide information on the current cloud configurations on the outer planets, search for new objects around the outer planets, and provide direct support for Voyager, Galileo, and CRAF by imaging material around asteroids and clouds on Neptune. Over the last year this program acquired multispectral and polarization images of the disk of material around the nearby star Beta Pictoris. This material is believed to be associated with the formation of planets and provides a first look at a planetary system much younger than our own. Preliminary color and polarization data suggest that the material is very low albedo and similar to dark outer solar system carbon rich material. A coronagraphic search for other systems is underway and has already examined over 100 nearby stars. Coronagraphic imaging provided the first clear look at the rings of Uranus and albedo limits for the ring arcs around Neptune.

Terrile, R. J.↗
NASA NTRS1976

Application LANDSAT imagery to geologic mapping in the ice-free valleys of Antarctica

The author has identified the following significant results. Studies in the Ice-Free Valleys are resulted in the compilation of a sizeable library of maps and publications. Rock reflectance measurements were taken during the Antarctic summer of 1973. Spectral reflectance of rocks (mostly mafic lava flows) in the McMurdo and Ice-Free Valleys areas were measured using a filter wheel photometer equipped to measure reflectances in the four Landsat bands. A series of samples were collected at regular intervals across a large differentiated, mafic sill near Lake Vida. Chemical analyses of the sample suggest that the tonal variations in this sill are controlled by changes in the iron content of the rock. False color images were prepared for a number of areas by the diazo method and with an optical multispectral biviewer. These images were useful in defining boundaries of sea ice, snow cover, and in the study of ablating glaciers, but were not very useful for rock discrimination.

Houston, R. S.↗
NASA NTRS1984

Mapping of glacial landforms from Seasat radar images

Glacial landforms in the drumlin drift belt of Ireland and the Alaska Range can be identified and mapped from Seasat synthetic-aperture radar (SAR) images. Drumlins cover 60 percent of the Ireland scene. The width/length ratio of individual drumlins can be measured on the SAR images, allowing regional differences in drumlin shape to be mapped. This cannot be done with corresponding Landsat multispectral scanner (MSS) images because of lower spatial resolution and because of shadowing effects that vary seasonally. The Alaska scene shows the extent and nature of morphological features such as medial and lateral moraines, stagnant ice, and fluted ground moraine in glaciated valleys. Perception of these features on corresponding Landsat MSS images is limited by seasonal diffrences in solar illumination. Because SAR is not affected by such differences or by cloud cover, it is particularly well suited for monitoring glacial movement. The disadvantage of distorted high-relief features on Seasat SAR images can be reduced in future SAR systems by modifying the radar illumination geometry.

Ford, J. P.↗