Abstract: A computer vision method performed by a computing system includes: receiving an image; identifying a light intensity value for each pixel of a set of pixels of the image; defining a light intensity band formed by an upper light intensity threshold and a lower light intensity threshold based on a light intensity distribution of the light intensity values of the set of pixels; for each pixel of the set of pixels, identifying whether that pixel has a light intensity value that is within the light intensity band or outside of the intensity band; and generating a modified image by increasing a light intensity contrast between a first subset of pixels identified as having light intensity values within the light intensity band and a second subset of pixels identified as having light intensity values outside of the light intensity band.

Abstract: A computer vision method performed by a computing system includes: receiving an image; identifying a light intensity value for each pixel of a set of pixels of the image; defining a light intensity band formed by an upper light intensity threshold and a lower light intensity threshold based on a light intensity distribution of the light intensity values of the set of pixels; for each pixel of the set of pixels, identifying whether that pixel has a light intensity value that is within the light intensity band or outside of the intensity band; and generating a modified image by increasing a light intensity contrast between a first subset of pixels identified as having light intensity values within the light intensity band and a second subset of pixels identified as having light intensity values outside of the light intensity band.

Abstract: A computer vision method and computer vision system can be used to process a time-based series of images. For a subject image of the time-based series, a light intensity value is identified for each pixel of a set of pixels of the subject image. A light intensity threshold is defined for the subject image based on a size of a bounding region for an object detected within a previous image of the time-based series captured before the subject image. A modified image is generated for the subject image by one or both of: reducing the light intensity value of each pixel of a lower intensity subset of pixels of the subject image that is less than the light intensity threshold, and increasing the light intensity value of each pixel of a higher intensity subset of pixels of the subject image that is greater than the light intensity threshold.

Abstract: A method for aerial vehicle component networking comprises, for a network-accessible avionics component onboard an aerial vehicle, instantiating a data stream object that specifies a network socket for communication between the network-accessible avionics component and a plurality of other network-accessible aerial vehicle components. A set of outgoing data is defined for transmission over the network socket to one or more onboard unicast aerial vehicle component subscribers of the plurality of other network-accessible aerial vehicle components and two or more onboard or offboard multicast aerial vehicle component subscribers of the plurality of other network-accessible aerial vehicle components. The outgoing data is published to the one or more onboard unicast aerial vehicle component subscribers over the network socket via unicast communication.

Abstract: A method for aerial vehicle component networking comprises, for a network-accessible avionics component onboard an aerial vehicle, instantiating a data stream object that specifies a network socket for communication between the network-accessible avionics component and a plurality of other network-accessible aerial vehicle components. A set of outgoing data is defined for transmission over the network socket to one or more onboard unicast aerial vehicle component subscribers of the plurality of other network-accessible aerial vehicle components and two or more onboard or offboard multicast aerial vehicle component subscribers of the plurality of other network-accessible aerial vehicle components. The outgoing data is published to the one or more onboard unicast aerial vehicle component subscribers over the network socket via unicast communication.

Abstract: A computer vision method performed by a computing system includes: receiving an image; identifying a light intensity value for each pixel of a set of pixels of the image; defining a light intensity band formed by an upper light intensity threshold and a lower light intensity threshold based on a light intensity distribution of the light intensity values of the set of pixels; for each pixel of the set of pixels, identifying whether that pixel has a light intensity value that is within the light intensity band or outside of the intensity band; and generating a modified image by increasing a light intensity contrast between a first subset of pixels identified as having light intensity values within the light intensity band and a second subset of pixels identified as having light intensity values outside of the light intensity band.

Abstract: A computer vision method and computer vision system can be used to process a time-based series of images. For a subject image of the time-based series, a light intensity value is identified for each pixel of a set of pixels of the subject image. A light intensity threshold is defined for the subject image based on a size of a bounding region for an object detected within a previous image of the time-based series captured before the subject image. A modified image is generated for the subject image by one or both of: reducing the light intensity value of each pixel of a lower intensity subset of pixels of the subject image that is less than the light intensity threshold, and increasing the light intensity value of each pixel of a higher intensity subset of pixels of the subject image that is greater than the light intensity threshold.

Abstract: An image analyzer is configured to use an image processing technique to detect coordinates of a region of a first image frame that matches a target template and update the target template by copying a portion of the first image frame corresponding to the coordinates and a first size. The image analyzer is also configured to receive a second image frame and generate a plurality of pixel match counts based on a comparison of the target template with a plurality of regions of the first size of the second image frame. The image analyzer is further configured to determine that a region of the second image frame matches the target template based on a pixel match count of the second region. The image analyzer is configured to generate an output indicating coordinates of the region of the second image frame.

Abstract: An image analyzer is configured to use an image processing technique to detect coordinates of a region of a first image frame that matches a target template and update the target template by copying a portion of the first image frame corresponding to the coordinates and a first size. The image analyzer is also configured to receive a second image frame and generate a plurality of pixel match counts based on a comparison of the target template with a plurality of regions of the first size of the second image frame. The image analyzer is further configured to determine that a region of the second image frame matches the target template based on a pixel match count of the second region. The image analyzer is configured to generate an output indicating coordinates of the region of the second image frame.