The Boeing Company

Dennis J Yelton

Christian C Witt

Christopher J Musial

John N Sanders-Reed

Kenneth Leonard Bernier

Scott M Peterson

Michael R Abraham

Fred Portigal

James C Hansen

Robert L Wright

Jack Sanders-Reed

Jitter is removed from point cloud data of a target by fitting the data to 3-D models of possible targets. The point cloud data is de-jittered as a group by shifting the point cloud data in its coordinate system until a minimum fit error is observed between the shifted data and a 3-D model under analysis. Different 3-D models may be evaluated in succession until a 3-D model is identified that has the least fit error. The 3-D model with the least fit error most likely represents the identity of the target.

De-jitter of point cloud data for target recognition

The present disclosure relates to imaging systems, aerial refueling aircraft, and methods relating to the processing of images. An example imaging system includes at least one camera, a display, and a controller. The controller includes at least one processor and a memory. The controller is configured to carry out operations. The operations include receiving at least one image from the at least one camera. The operations additionally include adjusting the at least one image to provide at least one adjusted image. Adjusting the at least one image includes applying: a local adaptive histogram equalization filter, a global gamma correction filter, and a local contrast filter. The operations also include outputting the at least one adjusted image to the display.

Augmented contrast limited adaptive histogram equalization

Jitter is removed from point cloud data by processing different groups of data points in the point cloud data in succession to minimize the entropy of the point cloud data. Each group in the point cloud data is generated at either different points in time or from detecting different pulses of reflected laser light from a target. The data points in a selected group are repetitively shifted en masse in the coordinate system of the point cloud data and the entropy of the point cloud data is re-calculated until subsequent shifts of the data points in the selected group does not further reduce the entropy. The remaining groups are subsequently processed in a similar fashion until the entropy of the point cloud data reaches a minimum.

De-jitter of point cloud data

The present disclosure relates to imaging processing devices, aerial refueling aircraft, and methods relating to the processing of images. An example imaging processing device includes a programmable circuit, such as a field-programmable gate array (FPGA), that is reprogrammed based on selected circuit data so as to construct a circuit configured to provide image processing on at least one image. The image processing includes receiving the at least one image. The image processing also includes adjusting the at least one image, to provide at least one adjusted image. Adjusting the at least one image includes applying: a local adaptive histogram equalization filter, a global gamma correction filter, and a local contrast filter.

Low-latency augmented contrast limited adaptive histogram equalization

A method of suppressing background clutter in video imagery of a scene including a foreground target and background clutter includes applying successive images of the video imagery to a clutter suppression process, thereby producing video imagery of a derived scene in which the background clutter is suppressed. This process includes processing the current image to remove a fixed pattern noise associated with the camera, and spatially re-registering the current image to a fixed geolocation or known clutter pattern of the scene in a reference image of the successive images. The process also includes subjecting independent copies of the current image to two infinite impulse response filters having different time constants to produce filtered, time-delayed images, and differencing the filtered images to reduce the background clutter, thereby producing a clutter-suppressed version of the current image in which the background clutter is suppressed with respect to the foreground target.

Suppression of background clutter in video imagery

A method of suppressing clutter in video imagery includes receiving video imagery from a focal plane array, and decomposing the video imagery into independently-moving coordinate transformations corresponding to clutter patterns that are subimages of the video imagery. The method also includes removing the subimages from an image of the video imagery to produce a clutter-suppressed version of the image, and rendering the clutter-suppressed version of the image. Removing the subimages from the image includes generating respective zeroth-order corrections for the subimages, and subtracting the respective zeroth-order corrections from the image. And removing the subimages includes recursively generating respective first-order corrections for the subimages from the respective zeroth-order corrections, and subtracting the respective first-order corrections from the image. The respective zeroth-order corrections are generated and subtracted from the image before the respective first-order corrections are generated and subtracted from the image.

Recursive suppression of clutter in video imagery

An apparatus is provided that includes a processor (e.g., FPGA) configured to cause the apparatus to perform a number of operations. The apparatus may be caused to receive input data for a digital image represented by point samples at respective sample locations, reconstruct the digital image from the input data for presentation by a display including display pixels, and output the reconstructed digital image. The reconstruction may include a number of operations for each of at least some of the display pixels. In this regard, the apparatus may be caused to perform a convolution-based, point-sample encoding of a selected display pixel to generate an encoding that identifies point samples of the digital image nearby the selected display pixel. And the apparatus may be caused to interpolate a value of the selected display pixel from at least some of the identified point samples using the generated encoding.

Real-time image reconstruction

A collision sense and avoidance system and method and an aircraft, such as an Unmanned Air Vehicle (UAV) and/or Remotely Piloted Vehicle (RPV), including the collision sense and avoidance system. The collision sense and avoidance system includes an image interrogator identifies potential collision threats to the aircraft and provides maneuvers to avoid any identified threat. Motion sensors (e.g., imaging and/or infrared sensors) provide image frames of the surroundings to a clutter suppression and target detection unit that detects local targets moving in the frames. A Line Of Sight (LOS), multi-target tracking unit, tracks detected local targets and maintains a track history in LOS coordinates for each detected local target. A threat assessment unit determines whether any tracked local target poses a collision threat. An avoidance maneuver unit provides flight control and guidance with a maneuver to avoid any identified said collision threat.

Aircraft collision sense and avoidance system and method

Method and system for passively detecting wires from a mobile transport system is provided. The method includes, pre-processing a digital image taken from a digital camera of the transport system, wherein the pre-processing is performed by a pre-processing module to reduce non-wire like clutter from the digital image; identifying pixels that can be classified as wire like by using a segment finder module on the digital image that has been pre-processed by the pre-processing module; and linking the identified pixels to determine if a wire like structure is present, wherein a linker module links the pixels that can be classified as wire like, to generate a wire overlay.

System and method for passive wire detection

Apparatus and methods for target detection in hyperspectral images are disclosed. In one embodiment, a method of detecting a target in a hyperspectral image includes spectrally unmixing the hyperspectral image into segments, each segment having at least one of similar spectral composition, similar textural composition, and similar variation, and spectrally unmixing at least one of the segments. The method further includes creating a clutter rejection filter for at least one segment, filtering at least one segment, and calculating target abundances in at least one segment. In alternate embodiments, channel reduction can be performed on the hyperspectral image and also on at least one segment. In further embodiments, data associated with the location of possible targets in the segments may be compiled. In yet another embodiment, this data may be compressed by cross referencing data from all segments and eliminating redundancies.

Methods and apparatus for adaptive foreground background analysis

A hardware system for passively detecting wires from a mobile transportation system is provided. The hardware system includes a main processor in the hardware system that uses plural commands to manage a preprocessor module and a linker module, wherein the pre-processing module pre-processes a digital image taken from a digital camera of the transport system and reduces non-wire like clutter from the digital image and identifies pixels that can be classified as wire like; and the linker module links the identified pixels to determine if a wire like structure is present and a binary output from the linker module is sent to an output select module that allows a user to select a video output.

The systems and methods of the present invention provide an image processor that displays enhanced vision images based on a plurality images sources. The image processor comprises both serial and parallel processors. The serial processor performs low data volume calculations needed by the parallel processor for image display. The serial processor precalculates transformations needed to convert source data from each source to a primary coordinate system. The parallel processor uses these transforms and correlates source data with the display on a pixel by pixel basis as each frame from the sources is received to thereby provide display data with decreased latency. The image processor reduces parallax effect and is capable of:) stitching images of different fields of view to provide a mosaic image;) fusing images taken of the same field of view by different types of sources into a fused image; and) correcting anomalies in the displayed image.

Growing community of inventors

Albuquerque, NM, United States of America

Dennis J Yelton