Raytheon Company

Corey J Collard

Jody Dale Verret

Richard W Ely

Vernon R Goodman

Stephen J Raif

Joseph C Landry

Grant B Boroughs

Matthew A Schaefer

Jerry O Moore

James G Hayes

Kevin M Grange

Robert M Willer

Robert V Opalecky

Mark J Graebner

Ali J Arik

Robert T Pierce

Erich Hefner

Systems, devices, methods, and computer-readable media for determining planarity in a 3D data set are provided. A method can include receiving or retrieving three-dimensional (3D) data of a geographical region, dividing the 3D data into first contiguous regions of specified first geographical dimensions, determining, for each first contiguous region of the first contiguous regions, respective measures of variation, identifying, based on the respective measures of variation, a search radius, dividing the 3D data into respective second contiguous or overlapping regions with dimensions the size of the identified search radius, and determining, based on the identified search radius, a planarity of each of the respective second contiguous or overlapping regions.

Determining minimum region for finding planar surfaces

Discussed herein are devices, systems, and methods for merging point cloud data with error propagation. A can include reducing a sum aggregate of discrepancies between respective tie points and associated 3D points in first and second 3D images, adjusting 3D error models of the first and second 3D images based on the reduced discrepancies to generate registered 3D images, and propagating an error of the first or second 3D images to the registered 3D image to generate error of the registered 3D images.

Point cloud registration with error propagation

A system receives digital images of a geographic location, associates each digital image with ground control points in a set of reference stereo images, and associates each digital image to each other digital image via image to image tiepoints. The system updates a geometry of each image via a bundle adjustment, and uses a prioritized stacking order to establish piecewise linear seam lines between each of the images. The system finally builds a prioritized map in a mosaic space specifying the source image pixels that are used in each region of the output mosaic, and forms the mosaic image using the prioritized map.

Ortho-image mosaic production system

A system and a method for processing multi-linear image data by measuring a relative oscillatory motion from a first-imaged array of the multi-linear optical array to a second-imaged array of the multi-linear optical array as a first function in time domain via image correlation; transforming the first function from the time domain to a second function in frequency domain; converting real and the imaginary parts of the second function to polar coordinates to generate a magnitude and a phase; correcting the polar coordinates from the second function in the frequency domain to generate a third function; converting the third function to rectangular coordinates to generate a fourth function in the frequency domain; and transforming the fourth function from the frequency domain to a fifth function in the time domain.

Oscillatory motion compensation in frequency domain in image motion sensing systems

A method, in accordance with particular embodiments, includes receiving voxel data for a plurality of voxels. Each voxel is associated with a unique volume of space associated with a geographic area. The voxel data for each respective voxel includes one or more values based on one or more reflections from one or more light pulses from a LIDAR system. The method further includes identifying noise values from among the one or more values for each respective voxel. The method additionally includes determining a baseline threshold comprising a static value that is uniform for each of the voxels. The method additionally includes determining a dynamic threshold that varies between the voxels and is based on the identified noise values. The method further includes applying the baseline and dynamic thresholds to the voxel data to generate filtered voxel data. The method also includes generating a three-dimensional image based on the filtered voxel data.

Noise reduction in light detection and ranging based imaging

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Plano, TX, United States of America

Corey J Collard