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The use of computer generated holograms to implement feature extraction operations has been achieved. The optical realization and use of multiple linear discriminant functions on a high-dimensionality feature space for large class pattern recognition is described and initial experimental results are provided.
Satellite-acquired, remotely sensed observations of the earth's land areas are substantially advancing knowledge of global vegetation patterns. Recognition that combined visible/near infrared spectral reflectance observations are a general indicator of the presence, condition and magnitude of vegetation foliage provides a basis for explanation. This information is of considerable value in climatic research because of the links between climate variables and vegetation foliage. Presence of vegetation foliage is predominantly determinated by a combination of local heat and moisture conditions. In turn, foliar presence determines local rates of photosynthesis, affects surface albedo, and influences local rates of evapotranspiration as well as other elements of surface energy/mass balance. Availability of these remotely sensed data provides, for the first time, a consistent, global means to directly study interactions between climate and vegetation. This understanding is now being incorporated in climatological research and should improve understanding of macroscale bioclimatology. Remote sensing technology and understanding of this technology are continuing to develop rapidly and further major advances in this new field of'satellite bioclimatology' can be expected in the near future.
The LANDSAT Thematic Mapper (TM) scanner records reflected solar energy from the earth's surface in six wavelength regions, or bands, and one band that records emitted energy in the thermal region, giving a total of seven bands. Useful research was extracted about terrain morphometry from remote sensing measurements and this information is used in an image-based terrain model for selected coastal geomorphic features in the Great Salt Lake Desert (GSLD). Technical developments include the incorporation of Aerial Profiling of Terrain System (APTS) data in satellite image analysis, and the production and use of 3-D surface plots of TM reflectance data. Also included in the technical developments is the analysis of the ground control point spatial distribution and its affects on geometric correction, and the terrain mapping procedure; using satellite data in a way that eliminates the need to degrade the data by resampling. The most common approach for terrain mapping with multispectral scanner data includes the techniques of pattern recognition and image classification, as opposed to direct measurement of radiance for identification of terrain features. The research approach in this investigation was based on an understanding of the characteristics of reflected light resulting from the variations in moisture and geometry related to terrain as described by the physical laws of radiative transfer. The image-based terrain model provides quantitative information about the terrain morphometry based on the physical relationship between TM data, the physical character of the GSLD, and the APTS measurements.
A study was made of software to integrate data from about 500 sensors that monitor the Space Shuttle Main Engine (SSME) and to make decisions for real-time control. Such software is expected to be applicable to other distributed systems as well. This study investigated the use of pattern recognition and other techniques to detect trends that could lead to major damage to the SSME and which would allow an orderly shutdown of the SSME before such damage could occur.
The efficiency of gravitational wave emission from axisymmetric rotating collapse to a black hole was found to be very low: Delta E/Mc sq. less than 7 x 10(exp -4). The main waveform shape is well defined and nearly independent of the details of the collapse. Such a signature will allow pattern recognition techniques to be used when searching experimental data. These results (which can be scaled in mass) were obtained using a fully general relativistic computer code that evolves rotating axisymmetric configurations and directly computes their gravitational radiation emission.
A top-down image processing scheme is described. A three-dimensional model of a robotic working environment, with robot manipulators, workpieces, cameras, and on-the-scene visual enhancements is employed to control and direct the image processing, so that rapid, robust algorithms act in an efficient manner to continually update the model. Only the model parameters are communicated, so that savings in bandwidth are achieved. This image compression by modeling is especially important for control of space telerobotics. The background for this scheme lies in an hypothesis of human vision put forward by the senior author and colleagues almost 20 years ago - the Scanpath Theory. Evidence was obtained that repetitive sequences of saccadic eye movements, the scanpath, acted as the checking phase of visual pattern recognition. Further evidence was obtained that the scanpaths were apparently generated by a cognitive model and not directly by the visual image. This top-down theory of human vision was generalized in some sense to the frame in artificial intelligence. Another source of the concept arose from bioengineering instrumentation for measuring the pupil and eye movements with infrared video cameras and special-purpose hardware.
Orbital docking, inspection, and sevicing are operations which have the potential for capability enhancement as well as cost reduction for space operations by the application of computer vision technology. Research at MSFC has been a natural outgrowth of orbital docking simulations for remote manually controlled vehicles such as the Teleoperator Retrieval System and the Orbital Maneuvering Vehicle (OMV). Baseline design of the OMV dictates teleoperator control from a ground station. This necessitates a high data-rate communication network and results in several seconds of time delay. Operational costs and vehicle control difficulties could be alleviated by an autonomous or semi-autonomous control system onboard the OMV which would be based on a computer vision system having capability to recognize video images in real time. A concept under development at MSFC with these attributes is based on syntactic pattern recognition. It uses tree graphs for rapid recognition of binary images of known orbiting target vehicles. This technique and others being investigated at MSFC will be evaluated in realistic conditions by the use of MSFC orbital docking simulators. Computer vision is also being applied at MSFC as part of the supporting development for Work Package One of Space Station Freedom.
Transfer of information across disciplines is promoted, while basic and applied researchers are cautioned about the danger of assuming simple relationships between stimulus information, perceptual impressions, and performance including pattern recognition and sensorimotor skills. A theoretical and empirical foundation was developed predicting those relationships.
A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.
An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.
A sensory world modeling system, congruent with a human expert's perception, is proposed. The Experiential Knowledge Base (EKB) system can provide a highly intelligible communication interface for telemonitoring and telecontrol of a real time robotic system operating in space. Paradigmatic acquisition of empirical perceptual knowledge, and real time experiential pattern recognition and knowledge integration are reviewed. The cellular architecture and operation of the EKB system are also examined.
The discovery of an edge enhancement effect in using a Hughes CdS liquid crystal light valve (LCLV) is reported. An edge-enhanced version of the input writing image can be directly obtained by operating the LCLV at a lower bias frequency and bias voltage. Experimental conditions in which this edge enhancement effect can be optimized are described. Experimental results show that the SNR of the readout image using this technique is superior to that obtained using high-pass filtering. The repeatability of this effect is confirmed by obtaining an edge enhancement result using two different Hughes LCLVs. The applicability of this effect to improve discrimination capability in optical pattern recognition is addressed. The results show that the Hughes LCLV can be used in both continuous tone and edge-enhancing modes by simply adjusting its bias conditions.
The problem of data compression is very important in digital photogrammetry, computer assisted cartography, and GIS/LIS. In addition, it is also applicable in many other fields such as computer vision, image processing, pattern recognition, and artificial intelligence. Consequently, there are many algorithms available to solve this problem but none of them are considered to be satisfactory. In this paper, a new method of finding critical points in a digitized curve is explained. This technique, based on the normalized symmetric scattered matrix, is good for both critical points detection and data compression. In addition, the critical points detected by this algorithm are compared with those by zero-crossings.
Recent developments in spatial light modulators have led to devices which are capable of continuous phase modulation, even if only over a limited range. One of these devices, the deformable mirror device is used, to compare the relative merits of binary and partially-continuous phase filters in a specific problem of pattern recognition by optical correlation. Each filter was physically limited to only about a radiation of modulation. Researchers have predicted that for low input noise levels, continuous phase-only filters should have a higher absolute correlator peak output than the corresponding binary filters, as well as having a larger SNR. When continuous and binary filters were implemented on the DMD and they exhibited the same performance; an ad hoc filter optimization procedure was developed for use in the laboratory. The optimized continuous filter gave higher correlation peaks than did an independently optimized binary filter. Background behavior in the correlation plane was similar for the two filters, and thus the SNR showed the same improvement for the continuous filter. A phasor diagram analysis and computer simulation have explained part of the optimization procedure's success.
The operating principles, design, and development histories of three image correlation systems, the Portable Correlator Unit (PCU), the Miniature Correlator Unit (MCU), and the Coherence Interferometer (CI) are reviewed. The PCU and MCU are compact versions of the classical Vander Lught filter optical correlator, essentially parallel optical processors by light valve; the CI is a white-light correlator which functions entirely by interfering light waves, with electronic detection only at the final output, and thus represents a parallel optical processor by rotational-shear interferometer. Details of the design and construction are discussed and illustrated with drawings and photographs. Also considered are applications of the MCU to NASA tasks such as rendezvous and docking on the Mars Rover and Sample Return mission, autonomous robotic exploration of planetary surfaces, and compression and pattern-recognition of remote-sensing data.
Pyramid image transforms have proven useful in image coding and pattern recognition. The hexagonal orthogonal oriented quadrature image pyramid (HOP), transforms an image into a set of orthogonal, oriented, odd and even bandpass subimages. It operates on a hexagonal input lattice and employs seven kernels, each of which occupies a neighborhood consisting of a point and a hexagon of six nearest neighbors. The kernels consist of one lowpass and six bandpass kernels that are orthogonal, self-similar, and localized in space, spatial frequency, orientation, and phase. The kernels are first applied to the image samples to create the first level of the pyramid, then to the lowpass coefficients to create the next level. The resulting pyramid is a compact, efficient image code. Here, a recursive, in-place algorithm for computation of the HOP transform is described. The transform may be regarded as a depth-first traversal of a tree structure. It is shown that the algorithm requires a number of operations that is on the order of the number of pixels.
Experiments show liquid-crystal light valve (LCLV) exhibits operating mode in which it enhances edges in images projected on it. Operates in edge-enhancing mode (or in combination of edge-enhancing and normal modes) by suitably adjusting bias voltage and frequency. Enhancement of edges one of most important preprocessing steps in optical pattern-recognition systems. Incorporated into image-processing system to enhance edges without introducing excessive optical noise.
Simoncelli and Adelson have extended the one dimensional Quadrature Mirror Filter (QMF) to two dimensions with hexagon symmetry and three dimensional spatio-temporal extensions with rhombic-duodecahedray symmetry. Jain and Crochiere presented an excellent QMF design technique in the time domain. It is proposed to extend the design of a two dimensional QMF over a rectangular lattice in the spatial domain based primarily on the extension of the idea of Jain and Crochiere. In addition, the design will investigate the use of two dimensional Z-transformations. Since this proposed QMF is intended for the applications in image processing, all the important and interesting engineering issues will be addressed throughout the development phase. The design of a two dimensional QMF is discussed. The motivation is to achieve an extremely high data compression ratio. It is entirely possible to achieve dramatic results when pattern recognition techniques are employed. The final goal is the demonstration of extremely high data compression ratios using NASA pictures.