Search results for "GEP"

showing 10 items of 1017 documents

Shaded-Mask Filtering for Extended Depth-of-Field Microscopy

2013

This paper proposes a new spatial filtering approach for increasing the depth-of-field (DOF) of imaging systems, which is very useful for obtaining sharp images for a wide range of axial positions of the object. Many different techniques have been reported to increase the depth of field. However the main advantage in our method is its simplicity, since we propose the use of purely absorbing beam-shaping elements, which allows a high focal depth with a minimum modification of the optical architecture. In the filter design, we have used the analogy between the axial behavior of a system with spherical aberration and the transverse impulse response of a 1D defocused system. This allowed us the…

Spatial filterComputer Networks and Communicationsbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFilter (signal processing)ÒpticaÒptica Aparells i instrumentsTransverse planeSpherical aberrationFilter designOpticsSimplicity (photography)Media TechnologyComputer visionArtificial intelligenceDepth of fieldElectrical and Electronic EngineeringbusinessImpulse responseInformation SystemsMathematics
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Single-channel polychromatic pattern recognition by the use of a joint-transform correlator.

2010

We present a single-channel system for color image recognition that is based on a joint-transform correlator setup. The color images are encoded as phase and amplitude functions, inspired from the Munsell color representation. A real-time implementation of the new codification method can be achieved by the use of a spatial light modulator operating in phase-only modulation mode. We determine the optimal codification for a linear color-phase code. Its performance is compared with a conventional multichannel correlator by means of computer simulations. Experimental results are also presented.

Spatial light modulatorChannel (digital image)Color imageComputer sciencebusiness.industryMaterials Science (miscellaneous)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhase (waves)Industrial and Manufacturing EngineeringOpticsModulationPattern recognition (psychology)Code (cryptography)Business and International ManagementJoint (audio engineering)businessApplied optics
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Super Resolution Methods Implementing Diffractive Masks Having a Certain Degree of Periodicity

2011

This section presents an approach that provides super resolved imaging at the center of the field of view and yet allows to see the remaining of the original field of view with original resolution. This operation resembles optical zooming while the zoomed and the nonzoomed images are obtained simultaneously. This is obtained by taking a single snap-shot and using a single imaging lens. The technique utilizes a special static/still coding element and a postprocessing algorithmic, without any mechanical movements.

Spatial light modulatorbusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONField of viewSuperresolutionGray levelGray codeImaging lensComputer visionArtificial intelligenceZoombusinessCoding (social sciences)
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Salient Pixels and Dimensionality Reduction for Display of Multi/Hyperspectral Images

2012

International audience; Dimensionality Reduction (DR) of spectral images is a common approach to different purposes such as visualization, noise removal or compression. Most methods such as PCA or band selection use either the entire population of pixels or a uniformly sampled subset in order to compute a projection matrix. By doing so, spatial information is not accurately handled and all the objects contained in the scene are given the same emphasis. Nonetheless, it is possible to focus the DR on the separation of specific Objects of Interest (OoI), simply by neglecting all the others. In PCA for instance, instead of using the variance of the scene in each spectral channel, we show that i…

Spectral Images[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingChannel (digital image)Computer scienceMultispectral image0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingProjection (linear algebra)[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringIAPRComputer vision021101 geological & geomatics engineeringSaliencyPixelbusiness.industryDimensionality reductionHyperspectral imagingPattern recognitionDimensionality reductionVisualizationComputer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligenceFocus (optics)business[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Salient Spin Images: A Descriptor for 3D Object Recognition

2018

In the last decades a wide range of algorithms have been devoted to recognize 3D free-from objects under real conditions such as occlusions, clutters, rotation, scale and translation. Spin image is one of these algorithms known to be robust to rotation, translation, occlusions up to 70% and clutters up to 60%, but still suffer from scaling, resolution changes and it is time consuming. In this paper we present a novel approach based on spin images, called salient spin images (SSI). This method enhances spin images algorithm based on its limits. Particularly, it decreases significantly the complexity of the algorithm using DoG detector, it shows a higher performance due to the relevant locali…

Spin imageComputer sciencebusiness.industryDetectorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCognitive neuroscience of visual object recognition[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]02 engineering and technology[INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG]01 natural sciences[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]010309 opticsRobustness (computer science)SalientComputer Science::Computer Vision and Pattern Recognition0103 physical sciences0202 electrical engineering electronic engineering information engineeringClutter020201 artificial intelligence & image processingComputer visionArtificial intelligencebusinessTrue positive rateScalingComputingMilieux_MISCELLANEOUS
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Periodic Orthogonal Wavelets and Wavelet Packets

2018

In this chapter, we discuss how to derive versatile families of periodic discrete-time orthogonal wavelets and wavelet packets from discrete and discrete-time splines outlined in Chap. 3. These wavelets and wavelet packets, although not having compact supports, are well localized in the time domain. They can have any number of discrete vanishing moments. Their DFT spectra tend to have a rectangular shape when the spline order grows and provide a collection of refined splits of the Nyquist frequency band. The wavelet and wavelet packet transforms are implemented in a fast way using the FFT.

Spline (mathematics)WaveletComputer scienceNetwork packetFast Fourier transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMathematicsofComputing_NUMERICALANALYSISData_CODINGANDINFORMATIONTHEORYTime domainVanishing momentsNyquist frequencyAlgorithmWavelet packet decomposition
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Distance-based functions for image comparison

1999

The interest in digital image comparison is steadily growing in the computer vision community. The definition of a suitable comparison measure for non-binary images is relevant in many image processing applications. Visual tasks like segmentation and classification require the evaluation of equivalence classes. Measures of similarity are also used to evaluate lossy compression algorithms and to define pictorial indices in image content based retrieval methods. In this paper we develop a distance-based approach to image similarity evaluation and we present several image distances which are based on low level features. The sensitivity and eAectiveness are tested on real data. ” 1999 Published…

Standard test imagebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingPattern recognitionImage segmentationAutomatic image annotationImage textureArtificial IntelligenceSignal ProcessingDigital image processingComputer visionComputer Vision and Pattern RecognitionArtificial intelligencebusinessImage retrievalSoftwareMathematicsFeature detection (computer vision)Pattern Recognition Letters
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Spatio‐temporal classification in point patterns under the presence of clutter

2019

We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions o…

Statistics and Probability010504 meteorology & atmospheric sciencesComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONContext (language use)01 natural sciences010104 statistics & probabilitySpatio-temporalpoint patternsClutterExpectation–maximization algorithmEuclidean geometryEarthquakesPoint (geometry)clutter earthquakes EM algorithm features mixtures nearest‐neighbor distances spatio‐temporal point patterns0101 mathematicsEM algorithmFeatures0105 earth and related environmental sciencesspatio-temporal point patternSpatial contextual awarenessEcological Modelingmixturenearest-neighbor distanceComputingMethodologies_PATTERNRECOGNITIONearthquakeMixturesProbability distributionClutterfeatureSettore SECS-S/01 - StatisticaclutterNearest-neighbor distancesAlgorithmEnvironmetrics
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Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach

2017

Summary This paper is concerned with interval estimation for the breakpoint parameter in segmented regression. We present score-type confidence intervals derived from the score statistic itself and from the recently proposed gradient statistic. Due to lack of regularity conditions of the score, non-smoothness and non-monotonicity, naive application of the score-based statistics is unfeasible and we propose to exploit the smoothed score obtained via induced smoothing. We compare our proposals with the traditional methods based on the Wald and the likelihood ratio statistics via simulations and an analysis of a real dataset: results show that the smoothed score-like statistics perform in prac…

Statistics and Probability010504 meteorology & atmospheric sciencesInterval estimationBreakpointinduced smoothingScore01 natural sciencesConfidence intervalchangepoint010104 statistics & probabilitypiecewise linear relationshipconfidence intervalscore inferenceStatistics0101 mathematicsStatistics Probability and UncertaintySegmented regressionSettore SECS-S/01 - StatisticaStatisticSmoothing0105 earth and related environmental sciencesMathematicsAustralian & New Zealand Journal of Statistics
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What we look at in paintings: A comparison between experienced and inexperienced art viewers

2016

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, a…

Statistics and ProbabilityFOS: Computer and information sciencesCoverageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION01 natural sciencesStatistics - Applications050105 experimental psychologyVisual arts010104 statistics & probabilitysilmänliikkeetInformationSystems_MODELSANDPRINCIPLES0501 psychology and cognitive sciencesApplications (stat.AP)0101 mathematicspoint processPaintingPoint (typography)05 social sciencesEye movementCognitioncognitive art researchtransition probabilityGazeTest (assessment)shift functionModeling and Simulationart viewersStatistics Probability and UncertaintyPsychologyintensity
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