bluuebunny/crossref_metadata_2025_split huggingface dataset:
Invariants under image perspective transformations: Theory and examples
Authors: Barrett Eamon B. , Payton Paul M. , Brill Michael H. , Haag Nils N. 
Published: March 2007

AbstractThe objective of this work is to develop automated techniques for recognizing the same objects in images that differ in scale, tilt, and rotation. Such perspective transformations of images are produced when aerial images of the same scene are taken from different vantage points. The algebraic methods developed previously do not utilize the intensity values of the images, i.e., their pixel gray levels. Since image features essential for object recognition, such as edges and local image textures, may be described in terms of derivatives and integrals of the image intensity, it is necessary to investigate whether certain differential and integral operators applied to different perspective views of the same object are also invariant under the perspective transformation. We proceed to derive new differential operators and their corresponding integral invariants for curves and planar objects. We introduce a variant form of Fourier expansion specially adapted to the projective transformation. Extensions to three dimensions are discussed, as well as applications to other image formation models such as synthetic aperture radar (SAR). These results are steps toward a computational model for perspective‐independent object recognition.
Feature classification techniques in model‐based object recognition
Authors: Acton Scott T. , Bovik Alan C. 
Published: March 2007

AbstractWe describe a system that performs model‐based recognition of the projections of generalized cylinders, and present new results on the final classification of the feature data. Two classification methods are proposed and compared. The first is a Bayesian technique that ranks the object space according to estimated conditional probability distributions. The second technique is a new feed‐forward “neural” implementation that utilizes the back‐propagation learning algorithm. The neural approach yields a 31.8% reduction in classification error for a database of twenty models relative to the Bayesian approach, although it does not provide an ordered ranking of the object space. The accuracy results of the neural approach represent a significant performance advance in feature‐based recognition by perceptual organization without the use of depth information. Examples are provided using the results of a simple segmentation system applied to real image data.
Image motion estimation by clustering
Authors: Bandopadhay Amit , Aloimonos John (Yiannis) 
Published: March 2007

AbstractImage motion is estimated by matching feature “interest” points in different frames of video image sequences. The matching is based on local similarity of the displacement vectors. Clustering in the displacement vector space is used to determine the set of plausible match vectors. Subsequently, a similarity‐based algorithm performs the actual matching. The feature points are computed using a multiple‐filter image decomposition operator. The algorithm has been tested on synthetic as well as real video images. The novelty of the approach is that it handles multiple motions and performs motion segmentation.
Information contained in the motion field of lines and the cooperation between motion and stereo
Authors: Faugeras Olivier D. , Navab Nassir , Deriche Rachid 
Published: March 2007

AbstractWe investigate the relationships that exist between the three‐dimensional structure and kinematics of a line moving rigidly in space and the two‐dimensional structure and kinematics (motion field) of its image in one or two cameras. We establish the fundamental equations that relate its three‐dimensional motion to its observed image motion. We show how this motion field can be estimated from a line‐based token tracker. We then assume that stereo matches have been established between image segments and show how the estimation of the motion field in the two images can be used to compute part of the kinematic screw of the corresponding 3D line. The equations are linear and if several lines belong to the same object provide a very simple way to estimate the full kinematic screw of that object. Finally, we show how the motion field can constrain the stereo matches by establishing necessary conditions that must be satisfied by the motion field of segments which are images of lines belonging to the same object. Only part of this theory has been implemented yet. This part uses Kalman filtering. Several experimental results using synthetic and real data are presented.
Properties of essential matrices
Authors: Maybank S. J. 
Published: March 2007

AbstractWe use essential matrices to show that if the recovery of camera displacement from image correspondences is unstable, then a small perturbation yields an ambiguous set of correspondences. We show that there are at most three camera displacements compatible with a dense set of correspondences, and we show that the symmetric and the antisymmetric parts of an essential matrix are related.
Comparison of statistical methods in MR imaging
Authors: Godtliebsen Fred , Spjsøtvoll Emil 
Published: March 2007

AbstractThe problem of recovering the true underlying scene from a noisy image is considered. Several methods are compared empirically by applying them to magnetic resonance (MR) images. It turns out that a simple method, the Gaussian window filter, gives good results. This method requires only “instantaneous” processing.
Seismic reverberations and the remote estimation of properties of underwater soils
Authors: McGee T. M. 
Published: March 2007

AbstractSeismic reflection profiles contain not only primary reflections but also sequences of reverberating events called multiple reflections. Field recordings are presented that demonstrate various types of multiple reflections that commonly occur on marine seismic profiles. Their presence is enhanced by the fact that submarine soils often exhibit so little dip that they approximate horizontal layers. If the recording geometry is such that the seismic wave fronts propagate in a direction perpendicular to the layers, individual wavelets within sequences can be identified on the basis of their record times. Having been identified, the amplitudes and phases of these wavelets can be compared to provide information concerning the material within which they reverberate. The comparison does not rely on knowledge of the source. An example of estimating sea‐floor density by comparing water‐layer multiples is given. Observations in waters that have received industrial effluent indicate that such comparisons could be useful when investigating accumulations of waste material.
The advanced spaceborne thermal emission and reflectance radiometer (Aster)
Authors: Kahle Anne B. , Palluconi Frank D. , Hook Simon J. , Realmuto Vincent J. , Bothwell G. 
Published: March 2007

AbstractThe Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) is the only high‐spatial‐resolution multispectral imager scheduled to fly in Earth orbit on the first platform of NASA's Earth Observation System (EOS‐A). The instrument will nave three bands in the visible near infrared with 15‐m spatial resolution, six bands in the short‐wave infrared with 30‐m spatial resolution and five bands in the thermal infrared with 90‐m spatial resolution. There will be an additional band in the near infrared with 15‐m spatial resolution that will provide same‐orbit stereo data when combined with the corresponding nadir viewing band. The ASTER instrument is being built by the Japanese Government based on the scientific requirements of the ASTER science team. This team consists of Japanese and American scientists, who will also be responsible for the development of algorithms for data reduction and analysis. The ASTER will be able to address a variety of science objectives identified by the EOS global change program. ASTER will provide surface temperatures and emissivity estimates, surface reflected radiances and digital elevation models at a spatial scale that will allow detailed process studies for MODIS and other global monitoring instruments at the subpixel level. Existing aircraft instruments can be used to simulate data that will be provided by ASTER. Examples are shown here of surface temperature mapping, surface compositional mapping, and digital elevation models derived from the NASA Thermal Infrared Multispectral Scanner, the Airborne Visible Infrared Imaging Spectrometer, and aerial photography.
Drawings recognition using two‐dimensional graph grammars
Authors: Matsello V. V. 
Published: March 2007

AbstractA new formal model for description and recognition of strictly defined sets of line drawing images is proposed. The fast image‐parsing algorithm associated with this model is described and its effectiveness is discussed. The algorithm allows one to obtain a structural description of a drawing picture. Using such a description it is possible to perform both the usual classification and a deep structural analysis of the picture.
Unification scheme for 3D surface reconstruction using physically based models
Authors: Wang Y. F. , Lee Jeng‐Feng , Wang Jih‐Fang 
Published: March 2007

AbstractWe propose a unification framework for three‐dimensional shape reconstruction using physically based models. A variety of 3D shape reconstruction techniques have been developed in the past two decades, such as shape from stereopsis, from shading, from texture gradient, and from structured lighting. However, the lack of a general theory that unifies these shape reconstruction techniques into one framework hinders the effort of a synergistical image interpretation scheme using multiple sensors/information sources. Most shape‐from‐Xtechniques use an “observable” (e.g., the stereo disparity, intensity, or texture gradient) and a model, which is based on specific domain knowledge (e.g., the triangulation principle, reflectance function, or texture distortion equation) to predict the observable, in 3D shape reconstruction. We show that all these “observable–prediction‐model” types of techniques can be incorporated into our framework of energy constraint on a flexible, deformable image frame. In our algorithm, if the observable does not confirm to the predictions obtained using the corresponding model, a large “error” potential results. The error potential gradient forces the flexible image frame to deform in space. The deformation brings the flexible image frame to “wrap” onto the surface of the imaged 3D object. Surface reconstruction is thus achieved through a “package wrapping” or a “shape deformation” process by minimizing the discrepancy in the observable and the model prediction. The dynamics of such a wrapping process are governed by the least action principle which is physically correct. A physically based model is essential in this general shape reconstruction framework because of its capability to recover the desired 3D shape, to provide an animation sequence of the reconstruction, and to include the regularization principle into the theory of surface reconstruction.
Use of fourier and hartley transforms in motion estimation: A comparative study
Authors: Mahmoud Sabri A. 
Published: March 2007

AbstractA comparison between the use of Fourier and Hartley transforms for motion estimation of multiple moving objects in image sequences is presented. The spectrum of the two transforms show that the temporal frequencies at the peaks (of the spectrum) is related to the velocity of the moving objects. The analysis shows that the Hartley technique is faster and requires less memory space than the Fourier technique. However, it gives the velocity of the moving objects but not the direction. The Fourier spectrum, on the other hand, gives the velocity and direction. An efficient implementation is possible by using the Hartley transform to estimate the temporal frequencies of the peaks and hence the velocities. The fast Fourier transform is then used to compute the spectrum at those peaks. The direction is easily found from the Fourier spectrum by reversing the sign of the temporal frequency corresponding to the peak.
Orthogonal decomposition technique for ionospheric tomography
Authors: Na Helen , Lee Hua 
Published: March 2007

AbstractThe possibility of reconstructing two‐dimensional electron‐density profiles in the ionosphere with ionospheric tomography is significant. However, due to the nature of the imaging system, there are several resolution degradation parameters. In order to compensate for these degradation parameters, a priori information must be used. This article introduces the orthogonal decomposition algorithm for image reconstruction, which uses the a priori information to generate a set of orthogonal basis functions for the source domain. This algorithm consists of two simple steps: orthogonal decomposition and recombination. In the development of the algorithm, it is shown that the degradation parameters of the imaging system result in correlations among projections of orthogonal functions. Gram–Schmidt orthogonalization is used to compensate for these correlations, producing a matrix that measures the degradation of the system. Any set of basis functions can be used, and depending upon this choice, the nature of the algorithm varies greatly. Choosing the basis functions of the source domain to be the Fourier kernels produces an algorithm capable of isolating individual frequency components of individual projections. This particular choice of basis functions also results in an algorithm that strongly resembles the direct Fourier method, but without requiring the use of inverse Fourier transforms.
New human visual system model and its application for designing image transmission systems
Authors: Krasilnikov N. N. 
Published: March 2007

AbstractThe advantage of the new human visual system model consists in its ability to take visual system properties into account more accurately. Because of this, it guarantees close agreement between subjective image impairment assessment on the one hand, and estimations obtained by this model on the other. This fact gives good grounds to exclude the human observer of the iteration process of parameters optimization for television equipment to be developed.
Prototype machine vision system for segmentation of hide images
Authors: Chetverikov Dmitry , Lerch Attila 
Published: March 2007

AbstractWe give a brief description of the operation principles of LeaVis, a prototype industrial machine vision system aimed at processing and segmentation of the images of hides marked by lines and other symbols that show defects and areas of different quality. The goal of LeaVis is to provide a visual input for a CAD system that sets trajectories for the knife cutting the hides. We discuss the basic motivations of the vision system design, present some of its algorithms, and demonstrate examples of their operation.
Migration and dip‐moveout seismic processes expressed as an invariant two‐dimensional convolution
Authors: Bardan Virgil 
Published: March 2007

AbstractMigration and dip‐moveout (partial prestack migration) are two‐dimensional (space and time) processes of fundamental importance in digital processing of seismic data. Their goal is to make the seismic section appear similar to the geological image along the seismic line subsurface. In this article we study migration and dip‐movement processes from the point of view of their impulse responses. The constant‐velocity migration process is a space‐invariant and time‐variant operator. We demonstrate and illustrate by examples of synthetic and real seismic sections that by transforming the time axis with a square function the constant‐velocity migration operator becomes temporally stationary as well as spatially stationary, that is, it can be expressed as an invariant two‐dimensional convolution. The dip‐moveout seismic process can be applied to constant‐offset seismic sections or to shot seismic profiles. The application of dip‐moveout process to constant‐offset sections is also a temporally varying and spatially stationary operator. By transforming the time axis with a logarithmic function the constant‐offset dip‐moveout operator becomes temporally stationary as well as spatially stationary. The shot dip‐moveout operator is space variant and time variant. After a logarithmic transformation of both the time and the space coordinates, it becomes time invariant and space invariant. Therefore the dip‐moveout seismic processes can be also expressed as an invariant two‐dimensional convolution. We illustrate this by examples of synthetic seismic sections.
Optimum rigid motion with one perspective view
Authors: Holt Robert J. , Netravali Arun N. 
Published: March 2007

AbstractOne of the central problems in dynamic computer vision is the determination of motion from correspondence of points on the visible surface of a moving object obtained at two different times. In the problem we consider, the initial position of several feature points on some object is assumed to be known. Then at some later time instant the corresponding perspective projection of those points is given. The moving body may be nonrigid or the measurements may be corrupted with noise. In either case, we determine the multiplicity of possible solution for the best‐fitting rigid motion. We show that whenever at least three point correspondences are given, there are at most two possible solutions for the best‐fitting rigid motion if the object space is two‐dimensional, while there are at most forty possible solutions if the object space is three‐dimensional. In the latter case the number of possible solutions drops to four if three point correspondence are known, the body is rigid, and the measurements are noise‐free. Several examples are worked out to illustrate our results.©1994 John Wiley & Sons Inc
Neural network approach to segmentation of magnetic resonance head images
Authors: Oshio Koichi , Singh Manbir 
Published: March 2007

AbstractA novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three‐layer perceptron‐type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first‐echo intensity and computed T2 values to construct a two‐parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.
Quantitative NMR spectroscopy by matrix pencil methods
Authors: Wang Yi‐Min , Lee Hua , Apte Dipali V. 
Published: March 2007

AbstractThe matrix pencil (MP) method, based on the singular value decomposition (SVD), is applied to quantitative NMR spectroscopy. Its relationship to other SVD‐based methods is also presented. Simulations and applications are given to demonstrate the capability of superior performance.©1993 John Wiley & Sons Inc
On a Bayesian approach to coherent radar imaging
Authors: Styerwalt David , Heidbreder Glenn R. 
Published: March 2007

AbstractIn coherent imaging the object of interest is complex but only its amplitude is to be estimated. The object phase yields nuisance variables and in a proper Bayesian approach it is necessary to obtain a phaseless likelihood function. We investigate a two‐dimensional case in which the target object is modelled as a collection of point scatterers having independent random phases. The phaseless likelihood function is determined exactly for a configuration of data samples in a uniformly spaced square array in spatial frequency when the target scatterers are confined to lattice positions of a “matched” spatial array. It is determined approximately when the target scatterers are arbitrarily positioned, at most one per conventional resolution cell. The relation between maximum likelihood and conventional Fourier transform imaging is explored and the feasibility of a CLEAN algorithmic technique in coherent imaging is considered.©1993 John Wiley & Sons Inc
An application of splines to maximum likelihood radar imaging
Authors: O'Sullivan Joseph A. , Snyder Donald L. , Porter Donald G. , Moulin Pierre 
Published: March 2007

AbstractRecent results in radar imaging using estimation theoretic techniques are applied to forming images from data from a compact radar range. Nonparametric maximum likelihood methods based on spline approximations are used. The object imaged is a one meter diameter sphere covered with wrinkled aluminum foil. This rough sphere approximately fits the diffuse model and the ideal scattering function for a rough rotating sphere is known. The results shown demonstrate that the proposed algorithm is realizable and that the image are comparable to simulations.©1993 John Wiley & Sons Inc
Segmentation of SAR images using the wavelet transform
Authors: Du Li‐Jen , Lee Jong‐Sen , Hoppel Karl , Mango Stephen A. 
Published: March 2007

AbstractMultiresolution representation of images using the wavelet transform is a new approach for the analysis of image information content. The transform can be computed efficiently by a pyramidal algorithm based on convolution with quadrature mirror filters. The result is a set of subband images which consists of a lower resolution version of the original image and a sequence of detail images containing higher frequency spectral information. We used this representation for the supervised segmentation of polarimetric SAR images of the San Francisco Bay area acquired by the airborne JPL system for identifying various terrain covers. Since the wavelet transform generates the localized spatial and spectral information simultaneously, detailed knowledge of the texture variations within an image can be extracted from the data in the spectral subbands. The segmentation algorithm developed in this paper is formulated by taking into consideration both the intensity and the texture information. For polarimetric SAR images, the classification accuracy can be enhanced, if the combined data from copolarized and cross‐polarized images are used in the discrimination process. In contrast to other texture segmentation approaches, this algorithm does not require extensive calculations.©1993 John Wiley & Sons Inc
Inverse scattering of Hz waves using local shape‐function imaging: A T‐matrix formulation
Authors: Otto Gregory P. , Chew Weng Cho 
Published: March 2007

AbstractInverse scattering algorithms for Hz polarized waves are scarce, due to the added difficulties of polarization charges. Nevertheless, the polarization charges cannot be ignored for 3D problems as well as for 2D Hz problems. This work aims to reconstruct arbitrary inhomogeneous dielectric objects from Hz scattering data using a new formulation that abandons the standard integral equation model for a T‐matrix model. This new algorithm, called local shape‐function (LSF) imaging, is modified for dielectric objects with Hz incident fields, where previously the LSF algorithm was applied to metallic objects with Ez incident fields. The advantage of the LSF algorithm is a more accurate modeling of the induced interfacial polarization charges. For comparison, the Hz distorted Born iterative method using integral equations is shown to be valid only for small contrasts, while the LSF algorithm converges for much larger dielectric contrasts.©1994 John Wiley & Sons Inc