Johns Hopkins University

Marc A Kolodner

William C Walton

Christopher M Gifford

Edward E Hume, Jr

Donald A Ruffle

Patricia K Murphy

Shea T Hagstrom

Leo A Morris

A method and a system for object detection over water are provided. The method includes acquiring, from a storage system, image data associated with a target area. The image data includes radiance of a plurality of pixels in a first spectral band and in a second spectral band. The method also includes determining a metric corresponding to a pixel of the plurality of pixels as a function of the radiance in the first spectral band and the radiance in the second spectral band and detecting an object in the target area in response to a determination that the metric satisfies a criteria.

Object detection over water using normalized difference vegetation index system and method

A detection system includes processing circuitry configured to receive overhead image data divided into a plurality of image chips and receive metadata associated with the image data. The metadata includes ground sample distance information associated with the image data and provides an indication of ground area represented by each pixel within the image chips. The processing circuitry is further configured to screen the image chips for candidate detections based on a multi-stage screening process and determine whether to classify candidate detections as target detections. The process includes an intensity based screening stage, an object extraction stage that employs binary shape features to extract objects from detect positions identified based on an output of the intensity based screening stage, and a candidate detection identification stage employing template based and structural feature criteria to identify candidate detections from an output of the object extraction stage.

Tactical object finder

A method and structure that inputs atmospheric forecast information from the atmospheric forecast database based on current, real time atmospheric measurements. The hyperspectral detection processing unit also inputs at least one selected reflectance library from the reflectance library database, and data collection and sensor parameters from the sensor. With this information, the hyperspectral detection processing unit employs a model to produce at least one mission radiance library during the mission planning phase. Then, during the actual mission execution, the sensor is used to collect the hyperspectral data and the comparator can immediately compare the hyperspectral data to the mission radiance library to identify features and/or targets.

Radiance library forecasting for time-critical hyperspectral target detection systems

Growing community of inventors

Gaithersburg, MD, United States of America

Marc A Kolodner