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Improved design for reading gate of vertical-Bloch-line magnetic-bubble memory increases reliability of discrimination between binary ones and zeros. Magnetic bubbles that signify binary "1" and "0" produced by applying sufficiently large chopping currents to memory stripes. Bubbles then propagated differentially in bubble sorter. Method of discriminating between ones and zeros more reliable.
S-type and p-type pahoehoe record different mechanisms and vigors of activity within an active flow field. There is some controversy about what these mechanisms are exactly, and this study was undertaken with the idea that an accurate map of the two surfaces within a pahoehoe flow field could be helpful in solving the problem. Thermal Infrared Multispectral Scanner (TIMS) allows discrimination between s-type and p-type pahoehoe, and this ability was used to map the two surface types on the Mauna Iki satellite shield (southwest rift zone, Kilauea Volcano). TIMS was previously used to discriminate a'a from pahoehoe as well as to determine relative age relationships of different flows. Although inter-flow variation was minor in the data published by these authors, a second goal presented is to understand such variations to better constrain intra-flow differences used for age dating.
Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.
The performance and implementation complexity of coherent and of noncoherent QPSK and GMSK modulation/demodulation techniques in a complex mobile satellite systems environment, including large Doppler shift, delay spread, and low C/I, are compared. We demonstrate that for large f(sub d)T(sub b) products, where f(sub d) is the Doppler shift and T(sub b) is the bit duration, noncoherent (discriminator detector or differential demodulation) systems have a lower BER floor than their coherent counterparts. For significant delay spreads, e.g., tau(sub rms) greater than 0.4 T(sub b), and low C/I, coherent systems outperform noncoherent systems. However, the synchronization time of coherent systems is longer than that of noncoherent systems. Spectral efficiency, overall capacity, and related hardware complexity issues of these systems are also analyzed. We demonstrate that coherent systems have a simpler overall architecture (IF filter implementation-cost versus carrier recovery) and are more robust in an RF frequency drift environment. Additionally, the prediction tools, computer simulations, and analysis of coherent systems is simpler. The threshold or capture effect in low C/I interference environment is critical for noncoherent discriminator based systems. We conclude with a comparison of hardware architectures of coherent and of noncoherent systems, including recent trends in commercial VLSI technology and direct baseband to RF transmit, RF to baseband (0-IF) receiver implementation strategies.
Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.
Providing visual information acquired from remote events to various operators, researchers, and practitioners has become progressively more important as the application of special skills in alien or hazardous situations increases. To provide an understanding of the technical parameters required to specify imagery, we have identified, defined, and discussed seven salient characteristics of images: spatial resolution, linearity, luminance resolution, spectral discrimination, temporal discrimination, edge definition, and signal-to-noise ratio. We then describe a generalizing imaging system and identified how various parts of the system affect the image data. To emphasize the different applications of imagery, we have constrasted the common television system with the significant parameters of a televisual imaging system for technical applications. Finally, we have established a method by which the required visual information can be specified by describing certain technical parameters which are directly related to the information content of the imagery. This method requires the user to complete a form listing all pertinent data requirements for the imagery.
Algorithms and techniques for use in the identification and location of large buildings in digitized copies of aerial photographs are developed and tested. The building data would be used in the simulation of objects located in the vicinity of an airport that may be detected by aircraft radar. Two distinct approaches are considered. Most building footprints are rectangular in form. The first approach studied is to search for right-angled corners that characterize rectangular objects and then to connect these corners to complete the building. This problem is difficult because many nonbuilding objects, such as street corners, parking lots, and ballparks often have well defined corners which are often difficult to distinguish from rooftops. Furthermore, rooftops come in a number of shapes, sizes, shadings, and textures which also limit the discrimination task. The strategy used linear sequences of different samples to detect straight edge segments at multiple angles and to determine when these segments meet at approximately right-angles with respect to each other. This technique is effective in locating corners. The test image used has a fairly rectangular block pattern oriented about thirty degrees clockwise from a vertical alignment, and the overall measurement data reflect this. However, this technique does not discriminate between buildings and other objects at an operationally suitable rate. In addition, since multiple paths are tested for each image pixel, this is a time consuming task. The process can be speeded up by preprocessing the image to locate the more optimal sampling paths. The second approach is to rely on a human operator to identify and select the building objects and then to have the computer determine the outline and location of the selected structures. When presented with a copy of a digitized aerial photograph, the operator uses a mouse and cursor to select a target building. After a button on the mouse is pressed, with the cursor fully within the perimeter of the building, the program scans from the position of the cursor to a perimeter position where a shift in grayscale is detected. Once at the perimeter, the process traces along it, around the building, until it eventually returns to the perimeter starting point. Spatial resolution limits cause the perimeter trace to be somewhat course so that a line straightening algorithm is employed. One result is that the building corner positions become more distinctly defined.
Imaging spectrometry offers a new way of deriving ecological information about vegetation communities from remote sensing. Applications include derivation of canopy chemistry, measurement of column atmospheric water vapor and liquid water, improved detectability of materials, more accurate estimation of green vegetation cover and discrimination of spectrally distinct green leaf, non-photosynthetic vegetation (NPV: litter, wood, bark, etc.) and shade spectra associated with different vegetation communities. Much of our emphasis has been on interpreting Airborne Visible/Infrared Imaging Spectrometry (AVIRIS) data spectral mixtures. Two approaches have been used, simple models, where the data are treated as a mixture of 3 to 4 laboratory/field measured spectra, known as reference endmembers (EM's), applied uniformly to the whole image, to more complex models where both the number of EM's and the types of EM's vary on a per-pixel basis. Where simple models are applied, materials, such as NPV, which are spectrally similar to soils, can be discriminated on the basis of residual spectra. One key aspect is that the data are calibrated to reflectance and modeled as mixtures of reference EM's, permitting temporal comparison of EM fractions, independent of scene location or data type. In previous studies the calibration was performed using a modified-empirical line calibration, assuming a uniform atmosphere across the scene. In this study, a Modtran-based calibration approach was used to map liquid water and atmospheric water vapor and retrieve surface reflectance from three AVIRIS scenes acquired in 1992 over the Jasper Ridge Biological Preserve. The data were acquired on June 2nd, September 4th and October 6th. Reflectance images were analyzed as spectral mixtures of reference EM's using a simple 4 EM model. Atmospheric water vapor derived from Modtran was compared to elevation, and community type. Liquid water was compare to the abundance of NPV, Shade and Green Vegetation (VG) for select sites to determine whether a relationship existed, and under what conditions the relationship broke down. Temporal trends in endmember fractions, liquid water and atmospheric water vapor were investigated also. The combination of spectral mixture analysis and the Modtran based atmospheric/liquid water models was used to develop a unique vegetation community description.
Plant species composition and plant architectural attributes are critical parameters required for the measuring, monitoring, and modeling of terrestrial ecosystems. Remote sensing is commonly cited as an important tool for deriving vegetation properties at an appropriate scale for ecosystem studies, ranging from local to regional and even synoptic scales. Classical approaches rely on vegetation indices such as the normalized difference vegetation index (NDVI) to estimate biophysical parameters such as leaf area index or intercepted photosynthetically active radiation (IPAR). Another approach is to apply a variety of classification schemes to map vegetation and thus extrapolate fine-scale information about specific sites to larger areas of similar composition. Imaging spectrometry provides additional information that is not obtainable through broad-band sensors and that may provide improved inputs both to direct biophysical estimates as well as classification schemes. Some of this capability has been demonstrated through improved discrimination of vegetation, estimates of canopy biochemistry, and liquid water estimates from vegetation. We investigate further the potential of leaf water absorption estimated from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data as a means for discriminating vegetation types and deriving canopy architectural information. We expand our analysis to incorporate liquid water estimates from two spectral regions, the 1000-nm region and the 2200-nm region. The study was conducted in the vicinity of Jasper Ridge, California, which is located on the San Francisco peninsula to the west of the Stanford University campus. AVIRIS data were acquired over Jasper Ridge, CA, on June 2, 1992, at 19:31 UTC. Spectra from three sites in this image were analyzed. These data are from an area of healthy grass, oak woodland, and redwood forest, respectively. For these analyses, the AVIRIS-measured upwelling radiance spectra for the entire Jasper Ridge scene were transformed to apparent surface reflectance using a radiative transfer code-based inversion algorithm.
In this paper we describe weighting techniques used for the optimal coaddition of charge coupled devices (CCD) frames with differing characteristics. Optimal means maximum signal to noise (S/N) for stellar objects. We derive formulas for four applications: (1) object detection via matched filter, (2) object detection identical to DAOFIND, (3) aperture photometry, and (4) ALLSTAR profile-fitting photometry. We have included examples involving 21 frames for which either the sky brightness or image resolution varied by a factor of 3. The gains in S/N were modest for most of the examples, except for DAOFIND detection with varying image resolution which exhibited a substantial S/N increase. Even though the only consideration was maximizing S/N, the image resolution was seen to improve for most of the variable resolution examples. Also discussed are empirical fits for the weighting and the availability of the program, WEIGHT, used to generate the weighting for the individual frames. Finally, we include appendices describing the effects of clipping algorithms and a scheme for star/galaxy and cosmic-ray/star discrimination. scheme for star/galaxy and cosmic-ray/star discrimination.
We use statistical and topological quantities to test the Cosmic Background Explorer (COBE) Differential Microwave Radiometer (DMR) first-year sky maps against the hypothesis that the observed temperature fluctuations reflect Gaussian initial density perturbations with random phases. Recent papers discuss specific quantities as discriminators between Gaussian and non-Gaussian behavior, but the treatment of instrumental noise on the data is largely ignored. The presence of noise in the data biases many statistical quantities in a manner dependent on both the noise properties and the unknown cosmic microwave background temperature field. Appropriate weighting schemes can minimize this effect, but it cannot be completely eliminated. Analytic expressions are presented for these biases, and Monte Carlo simulations are used to assess the best strategy for determining cosmologically interesting information from noisy data. The genus is a robust discriminator that can be used to estimate the power-law quadrupole-normalized amplitude, Q(sub rms-PS), independently of the two-point correlation function. The genus of the DMR data is consistent with Gaussian initial fluctuations with Q(sub rms-PS) = (15.7 +/- 2.2) - (6.6 +/- 0.3)(n - 1) micro-K, where n is the power-law index. Fitting the rms temperature variations at various smoothing angles gives Q(sub rms-PS) = 13.2 +/- 2.5 micro-K and n = 1.7(sup (+0.3) sub (-0.6)). While consistent with Gaussian fluctuations, the first year data are only sufficient to rule out strongly non-Gaussian distributions of fluctuations.
A prototype user environment is described that enables a user with very limited computer skills to collaborate with a computer algorithm to develop search tools (agents) that can be used for image analysis, creating metadata for tagging images, searching for images in an image database on the basis of image content, or as a component of computer vision algorithms. Agents are learned in an ongoing, two-way dialogue between the user and the algorithm. The user points to mistakes made in classification. The algorithm, in response, attempts to discover which image attributes are discriminating between objects of interest and clutter. It then builds a candidate agent and applies it to an input image, producing an 'interest' image highlighting features that are consistent with the set of objects and clutter indicated by the user. The dialogue repeats until the user is satisfied. The prototype environment, called the Toolkit for Image Mining (TIM) is currently capable of learning spectral and textural patterns. Learning exhibits rapid convergence to reasonable levels of performance and, when thoroughly trained, Fo appears to be competitive in discrimination accuracy with other classification techniques.
Many analysis algorithms for high-dimensional remote sensing data require that the remotely sensed radiance spectra be transformed to approximate reflectance to allow comparison with a library of laboratory reflectance spectra. In maximum likelihood classification, however, the remotely sensed spectra are compared to training samples, thus a transformation to reflectance may or may not be helpful. The effect of several radiance-to-reflectance transformations on maximum likelihood classification accuracy is investigated in this paper. We show that the empirical line approach, LOWTRAN7, flat-field correction, single spectrum method, and internal average reflectance are all non-singular affine transformations, and that non-singular affine transformations have no effect on discriminant analysis feature extraction and maximum likelihood classification accuracy. (An affine transformation is a linear transformation with an optional offset.) Since the Atmosphere Removal Program (ATREM) and the log residue method are not affine transformations, experiments with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were conducted to determine the effect of these transformations on maximum likelihood classification accuracy. The average classification accuracy of the data transformed by ATREM and the log residue method was slightly less than the accuracy of the original radiance data. Since the radiance-to-reflectance transformations allow direct comparison of remotely sensed spectra with laboratory reflectance spectra, they can be quite useful in labeling the training samples required by maximum likelihood classification, but these transformations have only a slight effect or no effect at all on discriminant analysis and maximum likelihood classification accuracy.
Precise measurements of the angular power spectrum of the Cosmic Microwave Background (CMB) anisotropy will revolutionize cosmology. These measurements will discriminate between competing cosmological models and, if the standard inflationary scenario is correct, will determine each of the fundamental cosmological parameters with high precision. The astrophysics community has recognized this potential: the orbital experiments MAP and PLANCK, have been approved to measure CMB anisotropy. Balloon-borne experiments can realize much of this potential before these missions are launched. Additionally, properly designed balloon-borne experiments can complement MAP in frequency and angular resolution and can give the first realistic test of the instrumentation proposed for the high frequency instrument on PLANCK. The MAXIMA experiment is part of the MAXIMA/BOOMERANG collaboration which is doing balloon observations of the angular power spectrum of the Cosmic Microwave Background from l = 10 to l = 800. These experiments are designed to use the benefits of both North American and Antarctic long-duration ballooning to full advantage. We have developed several new technologies that together allow the power spectrum to be measured with unprecedented combination of angular resolution, beam throw, sensitivity, sky coverage and control of systematic effects. These technologies are the basis for the high frequency instrument for the PLANCK mission. Our measurements will strongly discriminate between models of the origin and evolution of structure in the universe and, for many models, will determine the value of the basic cosmological parameters to high precision.
A quasiperiodic oscillation (QPO) in the flux of this transient x-ray source is seen in power spectra of the BATSE 20-50-keV discriminator rates. On Sept. 9.0 UT, the QPO was centered on 271 +/- 2 mHz, and it had a FWHM of 30 +/- 5 mHz and a fractional rms of 19.2 +/- 2.5 percent. The QPO was first detected on Sept. 7.45 near 55 mHz and has been steadily increasing in frequency, reaching 350 mHz by Sept. 9.3. The QPO appears to have reached the Nyquist frequency (488 mHz) of our discriminator rates before the end of Sept. 9, and is no longer detectable in them.
In this article, the author proposes a new pair of sensitivity and response bias indices and compares them to other measures currently available, including d' and Beta of signal detection theory. Unlike d' and Beta, these new performance measures do not depend on specific distributional assumptions or assumptions about the transformation from stimulus information to a discrimination judgment with simulated and empirical data, the new sensitivity index is shown to be more accurate than d' and 16 other indices when these measures are used to compare the sensitivity levels of 2 experimental conditions. Results from a perceptual discrimination experiment demonstrate the feasibility of the new distribution-free bias index and suggest that biases of the type defined within the signal detection theory framework (i.e., the placement of a decision criterion) do not exist, even under an asymmetric payoff manipulation.
Motion information is critical for human locomotion and scene segmentation. Currently we have excellent neurophysiological models that are able to predict human detection and discrimination of local signals. Local motion signals are insufficient by themselves to guide human locomotion and to provide information about depth, object boundaries and surface structure. My research is aimed at understanding the mechanisms underlying the combination of motion signals across space and time. A target moving on an extended trajectory amidst noise dots in Brownian motion is much more detectable than the sum of signals generated by independent motion energy units responding to the trajectory segments. This result suggests that facilitation occurs between motion units tuned to similar directions, lying along the trajectory path. We investigated whether the interaction between local motion units along the motion direction is mediated by contrast. One possibility is that contrast-driven signals from motion units early in the trajectory sequence are added to signals in subsequent units. If this were the case, then units later in the sequence would have a larger signal than those earlier in the sequence. To test this possibility, we compared contrast discrimination thresholds for the first and third patches of a triplet of sequentially presented Gabor patches, aligned along the motion direction. According to this simple additive model, contrast increment thresholds for the third patch should be higher than thresholds for the first patch.The lack of a measurable effect on contrast thresholds for these various manipulations suggests that the pooling of signals along a trajectory is not mediated by contrast-driven signals. Instead, these results are consistent with models that propose that the facilitation of trajectory signals is achieved by a second-level network that chooses the strongest local motion signals and combines them if they occur in a spatio-temporal sequence consistent with a trajectory. These results parallel the lack of increased apparent contrast along a static contour made up of similarly oriented elements.
A multi-gas sensor is provided which modulates a polarized light beam over a broadband of wavelengths between two alternating orthogonal polarization components. The two orthogonal polarization components of the polarization modulated beam are directed along two distinct optical paths. At least one optical path contains one or more spectral discrimination element, with each spectral discrimination element having spectral absorption features of one or more gases of interest being measured. The two optical paths then intersect, and one orthogonal component of the intersected components is transmitted and the other orthogonal component is reflected. The combined polarization modulated beam is partitioned into one or more smaller spectral regions of interest where one or more gases of interest has an absorption band. The difference in intensity between the two orthogonal polarization components is then determined in each partitioned spectral region of interest as an indication of the spectral emission/absorption of the light beam by the gases of interest in the measurement path. The spectral emission/absorption is indicative of the concentration of the one or more gases of interest in the measurement path. More specifically, one embodiment of the present invention is a gas filter correlation radiometer which comprises a polarizer, a polarization modulator, a polarization beam splitter, a beam combiner, wavelength partitioning element, and detection element. The gases of interest are measured simultaneously and, further, can be measured independently or non-independently. Furthermore, optical or electronic element are provided to balance optical intensities between the two optical paths.