The Experts below are selected from a list of 96 Experts worldwide ranked by ideXlab platform
David P Casasent - One of the best experts on this subject based on the ideXlab platform.
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minace filter infrared target tracking recognition and rejection tests with aspect view Depression Angle and scale variations
Automatic Target Recognition XVII, 2007Co-Authors: Rohit Patnaik, David P CasasentAbstract:ABSTRACT We examine the sensitivity of minimum noise and correlation energy (MINACE) filtersto three different types of distortion variations (aspect view, Depression Angle, and scale) that are typically present in in frared (IR) im agery used for automatic target recognition (ATR) and tracking applications. Prior DIF (distortion-invariant filter) ATR work has addressed at most two simultaneous variations aspect view and Depression Angle variations for SAR data, and aspect view and thermal state variations for IR data. No prior Minace ATR work has addressed scale variations. In our tests, we consider all three simultaneous variations aspect view, Depression Angle, and scale. This is new. Our goal is to determine if one Minace filter per object can handle full 360° aspect view variations and can handle small Depression Angle variations, and to determine the range of scales that one Minace filter per object can handle after training on data at one or more scales. This determines when new Minace filters are needed in an image clos ing sequence. In all cases, shifts of the target test inputs are considered. We use ou r autoMinace algorithm that automates selec tion of the Minace filter parameter c and the training set images to be included in the f ilter. We also consider rejection of unseen confuser objects and clutter. No confuser, clutter, or test set data are present in the training or the validation set. We present test results using both real and CAD IR data. Keywords: Automatic target recognition, confuser rejection, co rrelation filter, distortion-invariant filter, IR target recognition, Minace filter, tracking
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a new svm for scale aspect and Depression Angle tolerant ir object recognition
Proceedings of SPIE the International Society for Optical Engineering, 2007Co-Authors: Yuchiang Frank Wang, David P CasasentAbstract:In most ATR applications, objects are not only present with thermal and aspect view Angle variations, its size (range) also changes as the sensor approaches the target, and Depression Angle variations can exist. Therefore, it is important and realistic to know how to handle these variations. We apply our new SVRDM (support vector representation and discrimination machine) classifier to address these problems. The SVRDM classifier has good generalization (like the standard SVM does), and it has the added property of a good rejection ability. In other words, it not only gives very promising recognition results on the true target classes, it is also able to reject other unseen objects (referred to as confusers). We address the following variation issues: the scale range one SVRDM can recognize when trained on data at one or more ranges, the Depression Angle difference one SVRDM can recognize when trained on data at only one (or several) Depression Angles, and the number of aspect views needed to be included in the training set to handle recognition of targets with aspect variations, and the classification and rejection performance. Thus, our results are most unique and worthwhile but are not easily compared to prior work. Recognition and rejection test results are presented on both simulated and real infra-red (IR) data.
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advanced distortion invariant minimum average correlation energy mace filters
Applied Optics, 1992Co-Authors: David P Casasent, Gopalan RavichandranAbstract:The original minimum average correlation energy (MACE) filter is addressed by using a new database (strategic relocatable objects, missile launchers) and including noise performance, Depression Angle, and resolution effects on the number of training set images that are required. Major attention is given to our new MACE filter algorithms for distortion-invariant pattern recognition: shifted-MACE filters (to suppress large false correlation peaks), minimum variance-MACE filters (for improved noise performance), multiple symbolic encoded filters (to reduce the effect of false correlation peaks), and Gaussian-MACE filters (to improve noise performance and intraclass recognition and reduce the training set size).
M Burka - One of the best experts on this subject based on the ideXlab platform.
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application of the rayleigh lidar to observations of noctilucent clouds
Journal of Geophysical Research, 1993Co-Authors: J W Meriwether, R W Farley, R T Mcnutt, Phan D Dao, W Moskowitz, G Davidson, M BurkaAbstract:The feasibility of lidar detection of noctilucent cloud (NLC) returns with the Rayleigh lidar technique was determined by calculations of lidar photocount profiles for the Nd:YAG lidar wavelength of 532 nm (Rayleigh temperature lidar). These results affirm the feasibility of the application of this instrument to study the high-latitude summer phenomenon of NLCs. Rayleigh 532-nm lidar observations were carried out in Greenland for late July and August, 1990. Extended cloudiness hampered these measurements, and a display of NLCs was seen only on August 14–15, 1990, out of a total of 11 nights. Examination of photographs of the NLCs for this night indicates that the spatial distribution of the clouds was patchy and fragmentary. No visual detection of NLCs in the region of the zenith when the solar Depression Angle was 8.6° was noted. At this time the sky was sufficiently dark, and if there had been any NLCs overhead, visual NLC sightings should have been possible. The lidar observations provided measurements of the middle atmosphere temperature from 25 km to about 70 km for times near local midnight. The shapes of these profiles agreed with that of the U.S. 76 standard model profile but with an increase of about 5% at the stratopause. Examination of the results for an indication of lidar Mie returns from NLCs was negative, which was consistent with the lack of visual detection.
T Zakroczymski - One of the best experts on this subject based on the ideXlab platform.
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impedance study of reinforcing steel in simulated pore solution with tannin
Journal of The Electrochemical Society, 1996Co-Authors: J Flis, T ZakroczymskiAbstract:Voltammetric and electrochemical impedance spectroscopy (EIS) measurements were performed to study the corrosion behavior of reinforcing steel in a simulated concrete pore solution with the addition of chloride anions and mimosa tannin. Surface films were analyzed with Auger electron spectroscopy. Under open-circuit conditions, in chloride-containing solutions, the charge-transfer resistance (R ct ) decreased after prolonged immersion, whereas the interfacial capacitance (C if ) and the semicircle Depression Angle increased. These changes were ascribed mainiv to redox reactions involving Fe(II)/Fe(III) species and to the buildup of corrosion products. An addition of tannin slowed down the changes in R et and C if . In the presence of tannin, the sur ace films were much thinner than those in the tannin-free solutions and contained probably a tannin-Fe(III) chelate at the outer surface. It is suggested that the impedance data for corroded reinforcing steel provide information on the accumulation of corrosion products rather than on the instant corrosion rate of the steel.
Wei Wang - One of the best experts on this subject based on the ideXlab platform.
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classification via sparse representation of steerable wavelet frames on grassmann manifold application to target recognition in sar image
IEEE Transactions on Image Processing, 2017Co-Authors: Ganggang Dong, Gangyao Kuang, Na Wang, Wei WangAbstract:Automatic target recognition has been widely studied over the years, yet it is still an open problem. The main obstacle consists in extended operating conditions, e.g. ., Depression Angle change, configuration variation, articulation, and occlusion. To deal with them, this paper proposes a new classification strategy. We develop a new representation model via the steerable wavelet frames. The proposed representation model is entirely viewed as an element on Grassmann manifolds. To achieve target classification, we embed Grassmann manifolds into an implicit reproducing Kernel Hilbert space (RKHS), where the kernel sparse learning can be applied. Specifically, the mappings of training sample in RKHS are concatenated to form an overcomplete dictionary. It is then used to encode the counterpart of query as a linear combination of its atoms. By designed Grassmann kernel function, it is capable to obtain the sparse representation, from which the inference can be reached. The novelty of this paper comes from: 1) the development of representation model by the set of directional components of Riesz transform; 2) the quantitative measure of similarity for proposed representation model by Grassmann metric; and 3) the generation of global kernel function by Grassmann kernel. Extensive comparative studies are performed to demonstrate the advantage of proposed strategy.
J W Meriwether - One of the best experts on this subject based on the ideXlab platform.
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application of the rayleigh lidar to observations of noctilucent clouds
Journal of Geophysical Research, 1993Co-Authors: J W Meriwether, R W Farley, R T Mcnutt, Phan D Dao, W Moskowitz, G Davidson, M BurkaAbstract:The feasibility of lidar detection of noctilucent cloud (NLC) returns with the Rayleigh lidar technique was determined by calculations of lidar photocount profiles for the Nd:YAG lidar wavelength of 532 nm (Rayleigh temperature lidar). These results affirm the feasibility of the application of this instrument to study the high-latitude summer phenomenon of NLCs. Rayleigh 532-nm lidar observations were carried out in Greenland for late July and August, 1990. Extended cloudiness hampered these measurements, and a display of NLCs was seen only on August 14–15, 1990, out of a total of 11 nights. Examination of photographs of the NLCs for this night indicates that the spatial distribution of the clouds was patchy and fragmentary. No visual detection of NLCs in the region of the zenith when the solar Depression Angle was 8.6° was noted. At this time the sky was sufficiently dark, and if there had been any NLCs overhead, visual NLC sightings should have been possible. The lidar observations provided measurements of the middle atmosphere temperature from 25 km to about 70 km for times near local midnight. The shapes of these profiles agreed with that of the U.S. 76 standard model profile but with an increase of about 5% at the stratopause. Examination of the results for an indication of lidar Mie returns from NLCs was negative, which was consistent with the lack of visual detection.