Lockheed Martin Corporation

Drs Rsta, Inc.

Real 3-d

Intel Corporation

Harry Charles Lee

Larry Phurrough

Colleen Flynn Gratsch

Richard Skoblick

Melissa Wiedemann

Jason A Sefcik

Teresa Lorae Pace

Marlon Javier Fuentes

Teresa Olson

Dat Nguyen

Richard Economy

Walter Robert Steiner

James Joseph Slaski

Eugene L Cloud

Richard A Manville

Stuart Krupnik

Teresa Lorae Pace Olson

Johnnie J Sanders

Jamie Cannon

Robert Stanfill

A method for reducing scintillation in an image of a scene includes receiving an input sequence of images of the scene and grouping a first plurality of images of the sequence of images into a first subset of images comprising a first number of images that occur in sequence within the input sequence of images of the scene. The method also includes grouping a second plurality of images of the sequence of images into a second subset of images comprising a second number of images that occur in sequence within the input sequence of images of the scene. The method further includes generating a set of averaged images comprising an averaged image for the first subset of images and an averaged image for the second subset of image and outputting a composite image based at least the set of averaged images.

Method for minimizing scintillation in dynamic images

A high resolution image of a scene or object is generated by collecting a plurality of images, enhancing the plurality of images to produce a sequence of enhanced images, registering the sequence of enhanced images, accumulating the intensities of the registered sequence of enhanced images to produce a composite image, and enhancing the composite image.

Method and system for enhancing short wave infrared images using super resolution (SR) and local area processing (LAP) techniques

A method and system for processing image data to identify objects in an image. Terrain types are identified in the image. A second image is generated identifying areas of the image which border regions of different intensities by identifying a gradient magnitude value for each pixel of the image. A filtered image is generated from the second image, the filtered image identifying potential objects which have a smaller radius than the size of a filter and a different brightness than background pixels surrounding the potential objects. The second image and the filtered image are compared to identify potential objects as an object. A potential object is identified as an object if the potential object has a gradient magnitude greater than a threshold gradient magnitude, and the threshold gradient magnitude is based on the terrain type identified in the portion of the image where the potential object is located.

Automatic image object identification using threshold gradient magnitude based on terrain type

A method and system for processing image data to identify objects in an image. A gradient vector image is generated from the image, the gradient vector image identifying a gradient magnitude value and a gradient direction for each pixel of the image. Lines are identified in the gradient vector image. It is determined whether the identified lines are perpendicular, whether more than a predetermined number of pixels on each of the lines identified as perpendicular have a gradient magnitude greater than a predetermined threshold, and whether the individual lines which are identified as perpendicular are within a predetermined distance of each other. A portion of the image is identified as an object if the identified lines are perpendicular, more than the predetermined number of pixels on each of the lines have a gradient magnitude greater than the predetermined threshold, and are within a predetermined distance of each other.

Method and apparatus for automatic object identification using identified perpendicular lines, gradient magnitudes and distances

A scintillation removal in an image of a scene is provided by collecting a plurality of images, dividing the plurality of images into subsets of images, averaging each of the subsets of images to produce corresponding averaged images, differencing the averaged images, masking the difference images, and combining the masked images to produce a composite image.

A method of tracking a moving object by an emissivity of the moving object including receiving first frame data containing emissivity image data of an emissivity from the moving object within a scene, extracting characterization image data from the first frame data that represents edges and gradients of the emissivity, and analyzing the characterization image data for tracking information.

Method of tracking a moving object by an emissivity of the moving object

A method and system for processing image data to identify objects in an image. The method and system operate using various resolutions of the image to identify the objects. Information obtained while processing the image at one resolution is employed when processing the image at another resolution. The method and system identify objects in the image based on the information obtained at the various resolutions of the image.

Method and apparatus for automatic object identification

A method and apparatus are provided for identifying linear objects in an image. Terrain types in the image are identified, and a gradient vector image, which identifies a gradient magnitude value and a gradient direction value for each pixel of the image, is generated from the image. Lines in the gradient vector image are identified using the identified terrain types in each portion of the image. It is determined whether the identified lines are perpendicular, collinear, or parallel to another line among the identified lines in the gradient vector image. Lines among the identified line are eliminated which are determined to not be perpendicular, collinear, or parallel to another line among the identified lines in the gradient vector image. Linear objects are identified using the remaining identified lines which have not been eliminated.

Method and apparatus for automatic linear object identification using identified terrain types in images

Methods and apparatus for identifying objects in an image include processing the image with a gradient operator to produce a gradient magnitude and direction for each pixel. A number of different gradient directions in a portion of the processed image is determined. The portion of the processed image is identified as an object if the number of different gradient directions exceeds a threshold number of gradient directions. The determination of the gradient directions can be simplified by employing a lookup table.

Method and system for identifying objects in an image

The present invention discloses a target detection process that acquires imagery from a target; compares the acquired imagery with image metric data; applies criteria to eliminate false detections and reduce clutter; applies morphological operators on the acquired imagery; probability rank orders the target imagery; divides the imagery into a series of detected target windows; and displays the detected target windows. The imagery undergoes light target detection, dark target detection or both. A morphological operator isolates targets from their background. Two concatenated morphological filter patterns are used to screen imagery data. Spatial discontinuities at the pixel level can be detected. The detected target window images are presented to a user in a mosaic format.

Two dimension autonomous isotropic detection technique

Method and apparatus for automatic identification of bodies of water

A method and system for processing image data to identify objects in an image. The method and system operate using various resolutions of the image to identify the objects. Information obtained while processing the image at one resolution is employed when processing the image at another resolution.

Method and apparatus for automatic identification of objects in an image

Method and apparatus for automatic identification of linear objects in an image

A method and apparatus for tracking an object in an image. An image of a scene comprising an object is received. The image is processed with a first tracker to produce a first estimate of a position of the object in the image and a first confidence value. The image is processed with a second tracker to produce a second estimate of the position of the object in the image and a second confidence value. The second tracker processes the image concurrently with the first tracker. An estimate of the position of the object in the image is selected using the first and second confidence values. The object is then tracked using the selected estimate.

Growing community of inventors

Maitland, FL, United States of America

Harry Charles Lee