Method and system for automatically determining lines of sight beween nodes
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Abstract
The present invention uses data from several sources to determine lines-of-sight between nodes in a FSO network. The present invention provides a three-dimensional neighborhood modeling system that uses aerial image data. Digital Elevation Models, U.S. street map data and address data to automatically map the placement of nodes within a neighborhood or other geographical area.
Method for creating the 3-Dimensional, House and Tree Maps used in the line-of-sight processing are also disclosed. A House Map in the present invention identifies houses in an area of consideration, and a Tree Map in the present invention identifies trees in an area of consideration. A 3-Dimensional Map in the present invention provides an elevation for every pixel for the area under consideration, whereby the elevation is adjusted for the height of trees, houses and other objects
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Citations
90 Claims
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1-42. -42. (Canceled).
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43. In a system for automatically determining line-of-sight configurations between nodes, wherein each node has a node height, a method of determining the elevation of a node, comprising:
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(a) determining the node'"'"'s ground location;
(b) determining the node'"'"'s elevation by reading an elevation from a 3-Dimensional Map at the node'"'"'s ground location; and
(c) adding the node height to the node'"'"'s elevation;
whereby the 3-Dimensional map provides elevations given a ground location, wherein said an elevation in the 3-Dimensional Map was determined by adding the height of any objects at a ground location to the elevation of terrain at the ground location. - View Dependent Claims (44, 45, 46)
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47. In a system for automatically determining line-of-sight configurations between nodes, wherein each node has a node height, a method of determining the elevation of a node, a computer-readable medium containing instructions that cause the system to:
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determine the node'"'"'s ground location;
determine the node'"'"'s elevation by reading an elevation from a 3-Dimensional Map at the node'"'"'s ground location; and
add the node height to the node'"'"'s elevation;
whereby the 3-Dimensional Map provides elevations given a ground location, wherein said an elevation in the 3-Dimensional Map was determined by adding the height of any objects at a ground location to the elevation of terrain at the ground location. - View Dependent Claims (48, 49, 50)
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51. A method of determining a possible alternative line-of-sight between a first node and a second node, wherein said nodes are located in an area for which an aerial image is available, comprising the steps of:
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(a) determining a first degree of freedom line for the first node, and a second degree of freedom line for the second node, such that each degree of freedom line is orthogonal to the straight line between the nodes;
(a) determining a resolution of the aerial image and an alternative position data parameter;
(b) placing the first node at a first placement that is a distance equal to the resolution in a first direction along the first degree of freedom line from the current placement of the first node, and (c) placing the second node at a second placement that is a distance equal to the resolution in the first direction along the second degree of freedom line from the current placement of the second node;
(d) determining if the straight line between the first node at the first placement and the second node at the second placement is a valid, unobstructed line-of-sight;
(e) if the straight line is a valid, unobstructed line-of-sight, saving the line-of-sight; and
if the straight line is not a valid, unobstructed line-of-sight, repeating steps (c) - (e) until the first node has been moved the distance specified in the alternative position data parameter. - View Dependent Claims (52)
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53. A method of identifying pixels in an aerial image that are part of a structure, comprising the steps of:
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(a) obtaining the aerial image;
(b) dividing the image into blocks;
(c) for each block, clustering pixels in the image into small regions of uniform color and texture; and
(d) identifying at least one region as a structure. - View Dependent Claims (54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74)
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75. A computer-readable medium containing instructions that cause a computer to identify pixels in an aerial image that are part of a structure, wherein said instructions cause include instructions to:
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obtain the aerial image;
divide the image into blocks;
for each block, cluster pixels in the image into small regions of uniform color and texture; and
identify at least one region as a structure.
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76. A method of identifying tree pixels in an aerial image, comprising the steps of:
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(a) obtaining the aerial image;
(b) identifying at least one tree in the image;
(c) creating a statistical model of tree color using the at least one identified tree;
(d) for every pixel, using the statistical model to determine the probability that a pixel is a tree; and
(e) for every pixel, if the probability that a pixel is a tree exceeds a predetermined threshold, labeling the pixel as a tree. - View Dependent Claims (77, 78, 79, 80, 81, 82, 83, 84, 85, 86)
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87. A method of creating a 3-Dimensional map of an area, wherein the 3-Dimensional map identifies every pixel in the area as a tree, house or terrain and identifies the elevation of every pixel, comprising the steps of:
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(a) obtaining a tree map of the area, wherein the tree map identifies pixels that have been determined to be trees;
(b) obtaining a house map of the area, wherein the house map identifies pixels that have been determined to be houses;
(c) creating a city map from the tree map and the house map, wherein every pixel has a classification, wherein the classification is selected from the group comprised of tree, house and terrain;
(d) obtaining height data;
(e) obtaining terrain elevation data; and
(f) determining an elevation for every pixel. - View Dependent Claims (88, 89)
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90. A computer-readable medium containing instructions that cause a computer to create a 3-Dimensional map of an area, wherein the 3-Dimensional map identifies every pixel in the area as a tree, house or terrain and identifies the elevation of every pixel, wherein said instruction include instructions to:
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obtain a tree map of the area, wherein the tree map identifies pixels that have been determined to be trees;
obtain a house map of the area, wherein the house map identifies pixels that have been determined to be houses;
create a city map from the tree map and the house map, wherein every pixel has a classification, wherein the classification is selected from the group comprised of tree, house and terrain;
obtain height data;
obtain terrain elevation data; and
determine an elevation for every pixel.
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Specification