Engineering topics

Huck, F. O.

Publications and source records attributed to Huck, F. O..

At least 19 records

NASA NTRS1986

First data from the earth radiation budget experiment (ERBE)

The first data obtained from the Earth Radiation Budget Experiment (ERBE) are presented. These data include emitted infrared radiation, albedo, and estimated scene types for Nov. 15, 1984, as well as measurements of the 'solar constant'. Images from the GOES on the same day are included for comparison with the ERBE scene identification. On an instantaneous basis, clouds appear colder and more reflective than seems to have been noted before. The experiment data will be applied to several key studies of cloud-radiation-climate interactions.

Barkstrom, B. R.↗

NASA NTRS1986

The Earth Radiation Budget Experiment - Early validation results

The primary techniques used to obtain and validate the data of the Earth Radiation Budget Experiment (ERBE) are described, together with preliminary results of the validation. The ERBE consists of radiometers aboard the ERB Satellite, dedicated to a 57-deg orbit, and each of the two NOAA meteorological spacecraft (NOAA 9 and NOAA G) in near polar orbits. The radiometers include scanning narrow field-of-view (FOV) and nadir-looking wide and medium FOV radiometers, and a solar monitoring channel. Measurements of the solar constant by the solar monitors, and the wide and medium FOV radiometers of the ERB and the NOAA 9 spacecraft agree within a fraction of a percent. Comparison of the wide and medium FOV radiometers with the scanning radiometers showed an agreement of 1 to 4 percent. The multiple ERBE satellites are acquiring the first global measurements of regional scale-diurnal variations in the earth's radiation budget. These were verified by comparison with the high-temporal-resolution geostationary satellite data.

Smith, G. L.↗

NASA NTRS1985

Image gathering and processing - Information and fidelity

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Huck, F. O.↗

NASA NTRS1985

Electroacoustical imaging technique for encoding incoherent radiance fields as Gabor elementary signals

A technique is presented for directly encoding incoherent radiance fields as Gabor elementary signals. This technique uses an electro-acoustic sensor to modulate the electronic charges induced by the incident radiance field with the electric fields generated by Gaussian modulated sinusoidal acoustic waves. The resultant signal carries the amplitude and phase information required for localizing spatial frequencies of the radiance field. These localized spatial frequency representations provide a link between the either geometric or Fourier transform representations currently used in computer vision and pattern recognition.

Fales, C. L.↗

NASA NTRS1984

Image-plane processing of visual information

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Huck, F. O.↗

NASA NTRS1984

Imaging system design for improved information capacity

Shannon's theory of information for communication channels is used to assess the performance of line-scan and sensor-array imaging systems and to optimize the design trade-offs involving sensitivity, spatial response, and sampling intervals. Formulations and computational evaluations account for spatial responses typical of line-scan and sensor-array mechanisms, lens diffraction and transmittance shading, defocus blur, and square and hexagonal sampling lattices.

Fales, C. L.↗

NASA NTRS1984

Image-plane processing for improved computer vision

The proper combination of optical design with image plane processing, as in the mechanism of human vision, which allows to improve the performance of sensor array imaging systems for edge detection and location was examined. Two dimensional bandpass filtering during image formation, optimizes edge enhancement and minimizes data transmission. It permits control of the spatial imaging system response to tradeoff edge enhancement for sensitivity at low light levels. It is shown that most of the information, up to about 94%, is contained in the signal intensity transitions from which the location of edges is determined for raw primal sketches. Shading the lens transmittance to increase depth of field and using a hexagonal instead of square sensor array lattice to decrease sensitivity to edge orientation improves edge information about 10%.

Huck, F. O.↗

NASA NTRS1983

Information theory analysis of sensor-array imaging systems for computer vision

Information theory is used to assess the performance of sensor-array imaging systems, with emphasis on the performance obtained with image-plane signal processing. By electronically controlling the spatial response of the imaging system, as suggested by the mechanism of human vision, it is possible to trade-off edge enhancement for sensitivity, increase dynamic range, and reduce data transmission. Computational results show that: signal information density varies little with large variations in the statistical properties of random radiance fields; most information (generally about 85 to 95 percent) is contained in the signal intensity transitions rather than levels; and performance is optimized when the OTF of the imaging system is nearly limited to the sampling passband to minimize aliasing at the cost of blurring, and the SNR is very high to permit the retrieval of small spatial detail from the extensively blurred signal. Shading the lens aperture transmittance to increase depth of field and using a regular hexagonal sensor-array instead of square lattice to decrease sensitivity to edge orientation also improves the signal information density up to about 30 percent at high SNRs.

Huck, F. O.↗

NASA NTRS1982

Computational modeling for the study of multispectral sensor systems and concepts

A computational model of the deterministic and stochastic processes involved in remote sensing is being developed as a tool for studying multispectral sensor systems and concepts. The goal is to improve the efficiency of sensor systems for routine worldwide monitoring of earth resources and the environment. Preliminary computational results are presented for simple models of the natural variability of atmospheric radiative transfer and surface reflectance. These results illustrate the dependence of classification accuracy on the selection of sensor spectral channels and data processing algorithms.

Huck, F. O.↗

NASA NTRS1982

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Huck, F. O.↗

NASA NTRS1981

Application of information theory to the design of line-scan imaging systems

Information theory is used to formulate a single figure of merit for assessing the performance of line scan imaging systems as a function of their spatial response (point spread function or modulation transfer function), sensitivity, sampling and quantization intervals, and the statistical properties of a random radiance field. Computational results for the information density and efficiency (i.e., the ratio of information density to data density) are intuitively satisfying and compare well with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV systems.

Huck, F. O.↗

NASA NTRS1981

Information efficiency of line-scan imaging mechanisms

Information theory is used to formulate a single figure of merit for assessing the performance of line-scan imaging systems as a function of their spatial response (PSF or MTF), sensitivity, and sampling and quantization intervals and of the statistical properties of a random radiance field. Information density and efficiency (i.e., the ratio of information density to data density) tend to be optimum when the MTF and sampling passband of the imaging system are matched to the Wiener spectrum of the radiance field. Computational results for the statistical properties of natural radiance fields and the responses of common line-scan imaging mechanisms indicate that information density and efficiency are not strongly sensitive to variations in typical statistical properties of the radiance field and that the best practically realizable performance is approached when the sampling intervals are approximately 0.5-0.7 times the equivalent diameter of the PSF.

Huck, F. O.↗

NASA NTRS1981

Information density and efficiency of two-dimensional /2-D/ sampled imagery

Information density and efficiency (i.e., the ratio of information density to data density) are used as criteria for assessing the quality of 2-D sampled and quantized imagery as a function of the statistical properties of random radiance fields, the spatial response (PSF or MTF) and sensitivity of imaging systems, and the sampling and quantization intervals. Computational results are intuitively satisfying: they are consistent with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV cameras, and they provide useful guidelines for optimizing the design of line-scan and sensor-array imaging systems, especially if these systems use a digital communication link for transmitting data.

Huck, F. O.↗

NASA NTRS1980

Aliasing and blurring in 2-D sampled imagery

The quality of image reconstructions from discrete data suffers not only from the blurring of spatial detail caused by limitations in the spatial frequency response of electrooptical systems, but also from the aliasing generated if spatial detail has been undersampled. Previous studies have observed that reasonable spot intensity profiles and photosensor aperture shapes of equivalent size result in about equal blurring but that some profiles and shapes suppress aliasing better than others. This paper presents quantitative results of the magnitude of aliasing and blurring as a function of random radiance fields typical for natural scenes and of spatial responses and sampling intervals typical for TV cameras and optical-mechanical scanners. These results indicate that aliasing may often be a larger source of degradation than either blurring or electronic noise.

Huck, F. O.↗

NASA NTRS1980

Aliased noise in radiometric measurements

The magnitude of aliased noise that degrades the accuracy of continuous reconstructions of discrete radiometric measurements was evaluated as a function of the spatial response and sampling intervals of the radiometer, and of the resolution of the reconstructed measurements. A Wiener spectrum, representative of a wide range of scenes, was used to characterize the radiance fluctuations.

Huck, F. O.↗

NASA NTRS1980

Multispectral data acquisition and classification - Computer modeling for smart sensor design

In this paper a model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing and evaluating smart sensors. The model has both stochastic and deterministic elements and accounts for solar radiation, atmospheric radiative transfer, surface reflectance, sensor spectral reponses, and classification algorithms. Preliminary results are presented which indicate the validity and usefulness of this approach. Future capabilities of smart sensors will ultimately be limited by the accuracy with which multispectral remote sensing processes and their error sources can be computationally modeled.

Park, S. K.↗

NASA NTRS1980

ERBE - Assessment of measurement accuracy

The Earth Radiation Budget Experiment (ERBE) represents a continuing effort to estimate the solar incident and earth reflected and emitted radiance from spacecraft measurements. The development of accurate and stable sensors and calibration sources is mandatory but not sufficient to attain and validate required measurement accuracies. It is also necessary to develop and experimentally test computational models of the calibration and measurement processes to account for environmental differences between (static) calibrations and (dynamic) measurements of the earth radiant exitance that varies with wavelength, position, direction, and time.

Spiers, R. B., Jr.↗

NASA NTRS1978

Multispectral data acquisition and classification - Statistical models for system design

In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.

Huck, F. O.↗