作者：
Mostafa G MostafaAly A FaragEdward EssockComputer Vision and Image Processing Laboratory
Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USAComputer Vision and Image Processing Laboratory Dept. of Electrical and Computer Engineering University of Louisville Louisville KY 40292 USADept. of Psychology University of Louisville Louisville kY 40292 USA
Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty rem...
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Multimodality image registration and fusion are essential steps in building 3-D models from remotesensing data. We present in this paper a neural network technique for the registration and fusion of multimodali-ty remote sensing data for the reconstruction of 3-D models of terrain regions. A FeedForward neural network isused to fuse the intensity data sets with the spatial data set after learning its geometry. Results on real data arepresented. Human performance evaluation is assessed on several perceptual tests in order to evaluate the fusionresults.
This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement...
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This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement...
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This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported.
There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be det...
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The free-form surface registration problem is important in medical imageprocessing and reconstruction. An accurate, robust and fast solution is, therefore, of great significance. Most existing approaches, like iterat...
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A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to...
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The authors briefly describe their new morphological operators of »boundary erosion region dilation (BERD)» and »boundary dilation region erosion (BDRE)». The paper covers definitions, properties, ...
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Edge-based image segmentation is a two-stage process;edge enhancement followed by edge linking. Modern approaches for edge enhancement use either the gradient of the Gaussian operator (VG) or the Laplacian of the Gaus...
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