Abstract: Methods, devices and non-transitory computer-readable storage medium for processing a sequence of respective top view images of a same terrestrial location are provided. One of the method may comprise choosing one image, called reference image, among the respective top view images, estimating for each respective top view image a respective geometric deformation between the respective top view image and the reference image, computing by the respective geometric deformations respective subpixel positions of the respective top view images relative to one high-resolution coordinate system, interpolating at the respective subpixel positions to sample at least part of at least some of the respective top view images on a prescribed grid to obtain a high-resolution image.

Abstract: A method for detecting and quantifying gas emissions from a satellite image comprises obtaining an image of an area of interest, determining an amount of variation in light intensity within the image, and correlating the amount of variation in light intensity within the image to a gas concentration of a gas emission located in the area of interest.

Abstract: Methods, devices and non-transitory computer-readable storage medium for processing a sequence of respective top view images of a same terrestrial location are provided. One of the method may comprise choosing one image, called reference image, among the respective top view images, estimating for each respective top view image a respective geometric deformation between the respective top view image and the reference image, computing by the respective geometric deformations respective subpixel positions of the respective top view images relative to one high-resolution coordinate system, interpolating at the respective subpixel positions to sample at least part of at least some of the respective top view images on a prescribed grid to obtain a high-resolution image.

Abstract: A method for measuring a liquid volume and/or corresponding fill rate of floating roof tanks includes selecting an Area Of Interest (AOI) to be monitored at the earth's surface, gathering geographical coordinates of tanks in the AOI, and downloading and pre-processing a time series of SAR reference images covering the AOI. The method includes projecting geographical coordinates of the tanks on the time series of the images to determine pixel coordinates of the tanks, and determining tank dimensions through processing of the images at the pixel coordinates. The method includes downloading and pre-processing at least one new SAR image over the AOI and registering it on top of the reference images, and, for each tank of the AOI, detecting in the new SAR image a bright spot corresponding to the roof of the tank and converting its pixel coordinates into liquid volume and/or fill rate information.

Abstract: A method for detecting pad construction and/or drilling and/or for hydraulic fracturing of at least one hydrocarbon well, comprising the steps of: selecting at least one specified well location, obtaining at least one time series of top view images of the specified well location, in which each top view image has a date corresponding to a day of acquisition of the top view image, processing the time series of top view images to detect at least one top view image showing the apparition of a well pad and/or showing drilling activity and/or showing fracturing activity, exporting the date corresponding to the acquisition day of the top view image showing the apparition of the well pad and/or drilling activity and/or fracturing activity, providing, based on export date, an information of pad construction date and/or drilling starting date and/or fracturing starting date and/or a full production forecast for the specified well location.

Abstract: A method for measuring a liquid volume and/or corresponding fill rate of floating roof tanks includes selecting an Area Of Interest (AOI) to be monitored at the earth's surface, gathering geographical coordinates of tanks in the AOI, and downloading and pre-processing a time series of SAR reference images covering the AOI. The method includes projecting geographical coordinates of the tanks on the time series of the images to determine pixel coordinates of the tanks, and determining tank dimensions through processing of the images at the pixel coordinates. The method includes downloading and pre-processing at least one new SAR image over the AOI and registering it on top of the reference images, and, for each tank of the AOI, detecting in the new SAR image a bright spot corresponding to the roof of the tank and converting its pixel coordinates into liquid volume and/or fill rate information.

Abstract: The techniques and device provided herein relate to receiving, via a processor, image data representative of a borehole of a well. The technique may include generating dequantized image data based on the image data, such that the dequantized image data filters one or more artifacts present in a Hough transformed version of the image data. One or more dip orientations (inclination and azimuth) associated with one or more formation dips present in the image data may be determined based on the dequantized image data. The technique may also include performing an a-contration validation algorithm for for the one or more formation dips to verify whether at least a formation dip having the or one of the possible dip orientation is present at a predetermined measured depth in the image data.

Abstract: A method for detecting pad construction and/or drilling and/or for hydraulic fracturing of at least one hydrocarbon well, comprising the steps of: selecting at least one specified well location, obtaining at least one time series of top view images of the specified well location, in which each top view image has a date corresponding to a day of acquisition of the top view image, processing the time series of top view images to detect at least one top view image showing the apparition of a well pad and/or showing drilling activity and/or showing fracturing activity, exporting the date corresponding to the acquisition day of the top view image showing the apparition of the well pad and/or drilling activity and/or fracturing activity, providing, based on export date, an information of pad construction date and/or drilling starting date and/or fracturing starting date and/or a full production forecast for the specified well location.

Abstract: Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Abstract: The techniques and device provided herein relate to receiving, via a processor, image data representative of a borehole of a well. The technique may include generating dequantized image data based on the image data, such that the dequantized image data filters one or more artifacts present in a Hough transformed version of the image data. One or more dip orientations (inclination and azimuth) associated with one or more formation dips present in the image data may be determined based on the dequantized image data. The technique may also include performing an a-contration validation algorithm for for the one or more formation dips to verify whether at least a formation dip having the or one of the possible dip orientation is present at a predetermined measured depth in the image data..

Abstract: Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Abstract: Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Abstract: Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Abstract: A method for the recognition of objects in at least one digital image includes: a) simulating from the digital image a plurality of digital rotations and at least two digital tilts different from 1 in order to develop a simulated image for each rotation-tilt pair; and b) applying an algorithm generating values that are invariant in translation, rotation and zoom onto the simulated images in order to determine so-called SIF (scale invariant features) local characteristics used for recognizing objects. The SIFT method can be used in step b.

Abstract: Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Abstract: The invention relates to the processing of a digital object that comprises: cancelling the noise of an original object (I) of a first type containing noise in order to obtain a noise-free object (J) of the first type; obtaining an object with a quasi-white noise of the first type from a difference (B) between the original object and the noise-free object; applying to the noise-free object (J) a first processing (t1) that comprises a neighboring processing for obtaining a transformed object (K) of a second type, the first processing being such that it would structure the noise contained in the original object if it was applied to said original object; applying to the noise object a second white processing (t2) for obtaining a quasi-white transformed noise object (C) of the second type; and inserting into the transformed object (K) the transformed noise object.

Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?) of the learning zone, evaluating a distance (d,d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.

Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?) of the learning zone, evaluating a distance (d,d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.

Abstract: The invention concerns image data processing, through noise reduction comprising the following steps: associating a learning zone (ZA) with a reference point (Pref) of the image (IM); for each variable point (PC, PC?,) of the learning zone, evaluating a distance (d, d?,) between: values of points in a first window (f1) of the image, centered on the reference point, and values of points in a second window (f2, f?2,), of similar format as the format of the first window and centered on the variable point; repeating said distance calculation for all the points of the learning zone as successive variable points and estimating an average value to assign to the reference point, said average being weighted on the basis of the distances evaluated for each variable point.

Abstract: Methods and systems for grouping video frames. The video frames may be from a multiplexed stream of video frames from a plurality of video sources. In some embodiments video frames are grouped by determining if the video frames share meaningful modes for values representative of features of the video frames.