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Sensors combined with logic and memory circuitry. Cross-correlation of two inputs accomplished by transversal filter. Position of image taken to point where image and template data yield maximum value correlation function. Circuit used for controlling robots, medical-image analysis, automatic vehicle guidance, and precise pointing of scientific cameras.
The recovery of the three dimensional structure of visible surfaces depicted in an image by emphasizing the role of geometric cues present in line drawings, was studied. Three key components are line classification, line interpretation, and surface interpolation. A model for three dimensional line interpretation and surface orientation was refined and a theory for the recovery of surface shape from surface marking geometry was developed. A new approach to the classification of edges was developed and implemented signatures were deduced for each of several edge types, expressed in terms of correlational properties of the image intensities in the vicinity of the edge. A computer program was developed that evaluates image edges as compared with these prototype signatures.
A calculation is presented for the cross-correlation of the radar images obtained by processing the same signal data over different portions of the chirp spectrum bandwidth as a function of the center frequency spacings for these portions. This is shown to be proportional to the square of the product of the characteristic function for ocean wave heights and the pupil function describing the chirp spectrum bandwidth used in the processing. Measurements of this function for ocean wave imagery over the coast of Alaska, the North Atlantic, and Monterey Bay, California, and correlation with the significant wave heights reported from ground truth data indicate that the synthetic aperture radar instrument can be used for providing wave height information in addition to the ocean wave imagery.
This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.
A visual-tracker computer program controls an articulated mast on a Mars rover to keep a designated feature (a target) in view while the rover drives toward the target, avoiding obstacles. Several prior visual-tracker programs have been tested on rover platforms; most require very small and well-estimated motion between consecutive image frames a requirement that is not realistic for a rover on rough terrain. The present visual-tracker program is designed to handle large image motions that lead to significant changes in feature geometry and photometry between frames. When a point is selected in one of the images acquired from stereoscopic cameras on the mast, a stereo triangulation algorithm computes a three-dimensional (3D) location for the target. As the rover moves, its body-mounted cameras feed images to a visual-odometry algorithm, which tracks two-dimensional (2D) corner features and computes their old and new 3D locations. The algorithm rejects points, the 3D motions of which are inconsistent with a rigid-world constraint, and then computes the apparent change in the rover pose (i.e., translation and rotation). The mast pan and tilt angles needed to keep the target centered in the field-of-view of the cameras (thereby minimizing the area over which the 2D-tracking algorithm must operate) are computed from the estimated change in the rover pose, the 3D position of the target feature, and a model of kinematics of the mast. If the motion between the consecutive frames is still large (i.e., 3D tracking was unsuccessful), an adaptive view-based matching technique is applied to the new image. This technique uses correlation-based template matching, in which a feature template is scaled by the ratio between the depth in the original template and the depth of pixels in the new image. This is repeated over the entire search window and the best correlation results indicate the appropriate match. The program could be a core for building application programs for systems that require coordination of vision and robotic motion.
Photographic recording film evaluation for star field image processing in spacecraft environment and use in star correlator
Some applications of Landsat data, particularily agricultural and forestry applications, require the ability to geometrically superimpose or register data acquired at different times and possibly by different satellites. An experimental investigation relating to a registration processor used by the Johnson Space Center for this purpose is the subject of this paper. Correlation of small subareas of images is at the heart of this registration processor and the manner in which various system parameters affect the correlation process is the prime area of investigation. Parameters investigated include preprocessing methods, methods for detecting sucessful correlations, fitting a surface to the correlation patch, fraction of pixels designated as edge pixels in edge detection adn local versus global generation of edge images. A suboptimum search procedure is used to find a good parameter set for this registration processor.
Filled arrays of bolometers are currently being employed for use in astronomy from the far-infrared through millimeter portion of the electromagnetic spectrum. Because of the large range of wavelengths for which such detectors are applicable, the size of a pixel (p) relative to the wavelength (lambda) will vary according to the specific application of a given available technology. As the pixel size becomes comparable to a wavelength of the absorbed radiation, correlations in the radiation field at the pixel can affect the imaging properties of the system independent of the correlations introduced by the front-end optics. We study the dependence of image fidelity and induced polarization on the size of the pixel by employing a formalism in which diffraction due to the pixel boundary is treated by propagating the second-order statistical correlations of the radiation field through a model optical system. We construct simulated polarized images of square pixels for various ratios of p lambda. For the limit in which few modes are supported by the pixel (p lambda lesssiml), we find that the diffraction due to the pixel edges is non-negligible and hence must be considered along with the telescope diffraction pattern in modeling the ultimate spatial resolution of an imaging system. For the case in which the pixel is over-moded (p lambda ggl), the geometric limit is approached as expected. This technique provides a quantitative approach to understand and optimize the imaging properties of planar detectors in the few-mode limit.
Optical pattern recognition allows objects to be recognized from their images and permits their positional parameters to be estimated accurately in real time. The guiding principle behind optical pattern recognition is that a lens focusing a beam of coherent light modulated with an image produces the two-dimensinal Fourier transform of that image. When the resulting output is further transformed by the matched filter corresponding to the original image, one obtains the autocorrelation function of the original image, which has a peak at the origin. Such a device is called an optical correlator and may be used to recognize the locate the image for which it is designed. (From a practical perspective, an approximation to the matched filter must be used since the spatial light modulator (SLM) on which the filter is implemented usually does not allow one to independently control both the magnitude and phase of the filter.) Generally, one is not just concerned with recognizing a single image but is interested in recognizing a variety of rotated and scaled views of a particular image. In order to recognize these different views using an optical correlator, one may select a subset of these views (whose elements are called training images) and then use a composite filter that is designed to produce a correlation peak for each training image. Presumably, these peaks should be sharp and easily distinguishable from the surrounding correlation plane values. In this report we consider two areas of research regarding composite optical correlators. First, we consider the question of how best to choose the training images that are used to design the composite filter. With regard to quantity, the number of training images should be large enough to adequately represent all possible views of the targeted object yet small enough to ensure that the resolution of the filter is not exhausted. As for the images themselves, they should be distinct enough to avoid numerical difficulties yet similar enough to avoid gaps in which certain views of the target will be unrecognized. One method that we introduce to study this problem is called probing and involves the creation of the artificial imagery. The second problem we consider involves the clasification of the composite filter's correlation plane data. In particular, we would like to determine not only whether or not we are viewing a training image, but, in the former case, we would like to determine which training image is being viewed. This second problem is investigated using traditional M-ary hypothesis testing techniques.
The author has identified the following significant results. Data from twelve successful ERTS-1 passes over Delaware Bay have been analyzed with special emphasis on coastal vegetation, land use, current circulation, water turbidity and pollution dispersion. Secchi depth, suspended sediment concentration and transmissivity as measured from helicopters and boats were correlated with ERTS-1 image radiance. Multispectral signatures of acid disposal plumes, sediment plumes and slick were investigated. Ten vegetative cover and water discrimination classes were selected for mapping: (1) forest-land; (2) Phragmites communis; (3) Spartina patens and Distichlis spicata; (4) Spartina alterniflora; (5) cropland; (6) plowed cropland; (7) sand and bare sandy soil; (8) bare mud; (9) deep water; and (10) sediment-laden and shallow water. Canonical analysis predicted good classification accuracies for most categories. The actual classification accuracies were very close to the predicted values with 8 of 10 categories classified with greater than 90% accuracy indicating that representative training sets had been selected.
The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.
The present study is based on Lighthill-Curle's theory of aerodynamic noise. Using a correlation approach and the image concept of Powell, the volume contribution of turbulent flow over a large surface is approximated by a surface contribution of pressure fluctuations. Far-field noise intensities are expressed in terms of the surface pressure fluctuations and surface impedance. Based on available experimental measurements, numerical examples are performed for noise radiated from a turbulent boundary layer and from a normal jet impingement over rigid surfaces. Comparisons with available noise measurements are made. For general turbulent flows over compliant surfaces, measurements are suggested to obtain useful data for noise predictions.
The Hunter Mountain plateau in the northern Panamint Range, California, exhibits anomalous topographic, vegetative, color and structural features in Skylab and LANDSAT satellite images which have strong correlation with mineralized areas and should prove significant for future exploration. Data observed to date were studied with reference to published geology and is interpreted in terms of greatest probability of ore mineralization. Further study in conjunction with space imagery analysis is recommended for location of potential mineral zones.
Altitudes and relative ages of mare surface units were compared to test if a systematic correlation in height of lava eruption surfaces and age might reflect a corresponding increase in depth of the magma chamber with time; in addition the altitudes were studied to shed light on the time and place of warping of mare surfaces. The laser altimeter data from the Apollo missions and relative age data based on crater erosion models and crater counts were used for the study. The data were correlated by using the image data bank of the Lunar Geoscience Consortium. Results of the first part of the study are inconclusive as no systematic increase in height of lavas with time could be shown. The data of the second part of the study support the conclusion that mare surfaces may have warped throughout most of the time represented by sample ages from the Apollo missions, and that the lithosphere may have become strong enough to remain stable after the time of Apollo 12 samples around 3 b.y. ago.
Distortions inherent on synthetic aperture radio (SAR) imagery and the development to date of unsupervised postprocessing rectification techniques are described. The geometric distortion can be divided into two categories: (1) distortion derived from the radar viewing geometry, this includes such effects as ground range nonlinearities, radar foreshortening and radar layover; (2) distortion introduced during the data processing, these distortions result from approximations made during the correlation such as in estimation of the target phase history, or compensation for the earth rotation. The processor induced distortions depends on the specific correlation algorithm used for image formation. The effects are addressed on the image product resulting from assumptions during the processing and it specifically considers distortions inherent in digital imagery produced by the digital image processor.
Separate holograms of horizontally (HH) and vertically (HV) polarized responses obtained by the APQ-102 side-looking radar were processed through an optical correlator and the resulting image was recorded on positive film from which black and white negative and positive prints were made. Visual comparison of the HH and HV images reveals a distinct dark band in the imagery which covers about 30% of the radar strip. Preliminary evaluaton of the flight line 1 date indicates that various features on the HH and HV images seem to have different response levels. The amount of sidelap due to the look angle between flight lines 1 and 2 is negligible. NASA mission #425 to obtain flightlines of NS-001 MSS data and supporting aerial photography was successfully flown. Flight line 3 data are of very good quality and virtually cloud-free. Results of data analysis for selection of test fields and for evaluation of waveband combination and spatial resolution are presented.
Four frequency like polarized scatterometer data over a sand dune field and a volcanic field were analyzed to understand the scattering characteristics of these two terrain types as a function of frequency and incidence angle. For the frequency range studied (400 MHz to 13.3 GHz) unvegetated sand dunes are specular reflectors that return an echo to the radar antenna particularly when the geometry is such that the dune slope is nearly perpendicular to the antenna. Vegetation on the dunes can cause significant backscatter. Lava flows are strong diffuse scatterers which have backscatter values similar to coniferous forest at certain frequencies. Different observation frequencies are required for different situations. The scatterometer data correlate well with radar images.
A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.