G06T2207/30192

Estimation of Atmospheric Turbulence Parameters using Differential Motion of Extended Features in Time-lapse Imagery

A system and method provide improved remote turbulence measurement. The system includes an image capturing device that captures time-lapse images of a distant target anywhere from a km to more than a 100 km away. A processor of the system tracks relative motion due to atmospheric turbulence of some number of patches of definite size on each of these images using a subpixel accurate correlation technique. The processor computes differential tilt variances between every pair of patches from the image collection and evaluates the theoretical weighting functions between turbulence along the path and differential tilt variances. The processor determines weights to linearly combine the weighting functions such that the combined weighting function closely resembles the weighting function corresponding to a turbulence parameter of interest. The processor then combines the differential tilt variances using the determined weights to obtain the desired turbulence parameter.

Requesting weather data based on pre-selected events

A ground weather center may transmit information requests that carry at least one meteorological specific triggering command. An airborne system may translate the triggering command into detectable meteorological conditions and may arm the trigger(s) for specific weather sensors accordingly and downlink information upon the airborne system detects the triggering conditions. By using such a triggering command, the airborne system may be able transmit the same amount of valuable information with less bandwidth by reducing the number of redundant downlinked packets.

Generation of synthetic high-elevation digital images from temporal sequences of high-elevation digital images

Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.

Systems and methods for detecting thermodynamic phase of clouds with optical polarization

A method and system for imaging thermodynamic phase of clouds includes obtaining a spatially-resolved polarimetric image of a region of the sky containing a cloud using a multipixel image sensor having multiple channels corresponding to different wavelength bands, determining a value of the Stokes S.sub.1 polarization parameter of incident light on each pixel corresponding to a portion of the image containing the cloud for multiple channels corresponding to different wavelength bands, and determining the thermodynamic phase of the cloud within the image based on the values of the Stokes S.sub.1 polarization parameter. The Stokes S.sub.1 polarization parameter values determined for a first channel corresponding to a first wavelength band is used to determine a liquid thermodynamic phase, and the Stokes S.sub.1 polarization parameter values determined for a second channel corresponding to a second, shorter wavelength band is used to determine an ice thermodynamic phase.

GENERATION OF SYNTHETIC HIGH-ELEVATION DIGITAL IMAGES FROM TEMPORAL SEQUENCES OF HIGH-ELEVATION DIGITAL IMAGES
20230045607 · 2023-02-09 ·

Implementations relate to detecting/replacing transient obstructions from high-elevation digital images, and/or to fusing data from high-elevation digital images having different spatial, temporal, and/or spectral resolutions. In various implementations, first and second temporal sequences of high-elevation digital images capturing a geographic area may be obtained. These temporal sequences may have different spatial, temporal, and/or spectral resolutions (or frequencies). A mapping may be generated of the pixels of the high-elevation digital images of the second temporal sequence to respective sub-pixels of the first temporal sequence. A point in time at which a synthetic high-elevation digital image of the geographic area may be selected. The synthetic high-elevation digital image may be generated for the point in time based on the mapping and other data described herein.

APPARATUS AND METHOD FOR DETECTING INTERSECTION EDGES
20230098480 · 2023-03-30 · ·

A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.

Computing device and method of removing raindrops from video images

A method of removing raindrops from video images is provided. The method includes the steps of: training a raindrop image recognition model using a plurality raindrop training images labeled in a plurality of rainy-scene images; recognizing a plurality of raindrop images from a plurality of scene images in a video sequence using the raindrop image recognition model; and in response to a specific raindrop image in a current scene image satisfying a predetermined condition, replacing the specific raindrop image in the current scene image with an image region corresponding to the specific raindrop image in a specific scene image prior to the current scene image to generate an output scene image.

Image processing apparatus, image processing system, imaging apparatus, image processing method, and storage medium
11488279 · 2022-11-01 · ·

An image processing apparatus includes an image acquisition unit configured to acquire a plurality of temporally different images each of which has degraded by a turbulence, a parameter acquisition unit configured to acquire a learned network parameter, and a measurement unit configured to measure a turbulence strength from the plurality of images using the network parameter and a neural network.

PREDICTING VISIBLE/INFRARED BAND IMAGES USING RADAR REFLECTANCE/BACKSCATTER IMAGES OF A TERRESTRIAL REGION
20220335715 · 2022-10-20 ·

The present invention relates to a method and apparatus that can predict the visible-infrared band images of a region of the Earth's surface that would be observed by an Earth Observation (EO) satellite or other high-altitude imaging platform, using data from radar reflectance/backscatter of the same region. The method and apparatus can be used to predict images of the Earth's surface in the visible-infrared bands when the view between an imaging instrument and the ground is obscured by cloud or some other medium that is opaque to electromagnetic (EM) radiation in the visible-infrared spectral range, approximately spanning 400-2300 nanometres (nm), but transparent to EM radiation in the radio-/microwave part of the spectrum. Regular, uninterrupted monitoring of the Earth's surface is important for a wide range of applications, from agriculture to defence.

PREDICTION SYSTEM FOR SOLAR PHOTOVOLTAIC GENERATION

A prediction system for solar photovoltaic generation includes a region setter that sets a target region where a solar panel is installed and an adjacent region adjacent to the target region, a first data collector that collects numerical weather data of the target region and adjacent region and an amount of the solar photovoltaic generation obtained from the solar panel, a second data collector that collects weather image data of the target region and adjacent region by using a satellite image, a controller that determines whether the target region is affected by wind by comparing the weather image data to each other, and a deep learner that predicts the weather image data of the target region, and predicts the amount of the solar photovoltaic generation by using the amount of the solar photovoltaic generation, the numerical weather data and weather image data of the target region.