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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Diagnosis of cutaneous thermal burn injuries by multispectral imaging analysis

Special photographic or television image analysis is shown to be a potentially useful technique to assist the physician in the early diagnosis of thermal burn injury. A background on the medical and physiological problems of burns is presented. The proposed methodology for burns diagnosis from both the theoretical and clinical points of view is discussed. The television/computer system constructed to accomplish this analysis is described, and the clinical results are discussed.

Anselmo, V. J.↗
NASA NTRS1979

Lunar multispectral imaging at 2.26 microns - First results

The first results of line-scan imaging of the moon at 2.26 microns and 0.56 micron are presented. Among the many features observed in the 2.26 micron/0.56 micron ratio image, fresh rock and immature soils stand out as dark (i.e., low ratio) due to their infrared absorption bands. Also notable in this image are several strikingly bright (high 2.26 micron/0.56 micron ratio) areas which are likely to contain pyroclastic, glass-related materials. Some of these bright areas correspond to dark mantling material. Others (e.g., Sulpicius Gallus, Aristarchus Plateau) are distinctly different in their overall spectral reflectance and it is suggested that these localities contain varieties of pyroclastic glass-related materials which were not sampled by Apollo 17 but which are relatively abundant elsewhere on the moon.

Davies, D. W.↗
NASA NTRS1979

Medical diagnosis system and method with multispectral imaging

A skin diagnosis system includes a scanning and optical arrangement whereby light reflected from each incremental area (pixel) of the skin is directed simultaneously to three separate light filters, e.g., IR, red, and green. As a result, the three devices simultaneously produce three signals which are directly related to the reflectance of light of different wavelengths from the corresponding pixel. These three signals for each pixel after processing are used as inputs to one or more output devices to produce a visual color display and/or a hard copy color print, for one usable as a diagnostic aid by a physician.

Anselmo, V. J.↗
NASA NTRS1980

Context distribution estimation for contextual classification of multispectral image data

A classification algorithm incorporating contextual information in a general, statistical manner is presented. Methods are investigated for obtaining adequate estimates of the context distribution (a statistical characterization of context) upon which the classification algorithm depends. Finally, a method of estimating optimal algorithm parameters prior to performing preliminary classifications is explored.

Tilton, J. C.↗
NASA NTRS1981

Contextual classification of multispectral image data - An unbiased estimator for the context distribution

Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach. This statistical classification algorithm exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context distribution. Here a discussion is given of an unbiased estimator of the context distribution which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗
NASA NTRS1981

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗
NASA NTRS1982

Estimation of context for statistical classification of multispectral image data

Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach. This statistical classification algorithm exploits the tendency of certain ground cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context function. An unbiased estimator of the context function is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context-function estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context-function estimation techniques.

Tilton, J. C.↗
NASA NTRS1987

Characterization of surficial units on Mars using Viking orbiter multispectral image and thermal data

Albedo and thermal property correlations of the topography of Mars were conducted with emphases upon the types and origins of materials exposed in the central equatorial region. This area displays a wide variation in color, albedo and thermal properties, and is relatively free of dust and haze. The physical, mineralogical and elemental characteristics of this area are discussed.

Presley, M. A.↗
NASA NTRS1987

The Land Analysis System (LAS) - A general purpose system for multispectral image processing

The present, general-purpose Land Analysis System (LAS) for image processing furnishes a comprehensive set of functions for the manipulation of MSS data; the initial version has more than 240 functions and utilities ranging from pixel manipulation to complex classification. A LAS user's guide describes each such function in terms of purpose, input parameters, illustrative examples, algorithms, error messages, and user codes. The LAS source code is so distributed as to simplify system maintenance; the Transportable Application Executive is employed as the user interface, thereby accommodating both expert and novice users by means of menus and tutored prompting.

Wharton, Stephen W.↗
NASA NTRS1990

A mixture neural net for multispectral imaging spectrometer processing

Each spatial region viewed by an imaging spectrometer contains various elements in a mixture. The elements present and the amount of each are to be determined. A neural net solution is considered. Initial optical neural net hardware is described. The first simulations on the component requirements of a neural net are considered. The pseudoinverse solution is shown to not suffice, i.e. a neural net solution is required.

Casasent, David↗
NASA NTRS1992

Remote sensing of surface hemispherical reflectance (albedo) using pointable multispectral imaging spectroradiometers

Remote techniques for determining albedo are examined in terms of the range of view angles required in the use of string techniques with the Moderate Resolution Imaging Spectroradiometer (MODIS) and the High Resolution Imaging Spectroradiometer (HIRIS). Ground data are used to compute full and half strings out to 15, 30, 45, and 60 degrees for various sun angles and ground cover types. A knowledge-based system is employed to evaluate both the visible and near-IR bands, and the results indicate errors of up to 7 percent for the MODIS data, HIRIS data, and the full-string +/- 60 degrees. In the cases of large extrapolations greater ranges of error are noted indicating that 60-deg systems are most effective. The error is increased in the case of sensor systems that only view in the fore or aft direction, and the MODIS full string for +/- 45 deg is also considered a good system.

Kimes, D. S.↗