21 results about "Radiometric correction" patented technology

This invention provides a method and system for constructing a 3D model of a construction site by combining multiple data sources. It relates to the field of data processing technology. The method includes: retrieving satellite imagery at a preset resolution to obtain a full-area stereo image pair dataset; performing radiometric correction to generate a regional surface model and a regional elevation model; performing raster-level modeling defect detection to locate distributed blind zone blocks; fitting obstacle avoidance paths to generate optimized obstacle avoidance flight trajectories; driving a UAV to perform multi-angle surround scanning to directionally collect dense point clouds in the distributed blind zones; constructing a distributed blind zone model; and performing microscopic overlay to output a 3D model of the construction site. This invention solves the technical problems of existing construction site modeling methods, which have limitations in coverage, modeling efficiency, and data real-time performance, and rely on a single data source, failing to provide a comprehensive and accurate 3D model of the construction site, thus affecting construction progress and decision-making.

The application discloses an infrared image adaptive atmospheric correction method and device based on a radiation transmission model, and belongs to the technical field of remote sensing image radiation correction. The method first extracts the spatial range, imaging time and observation geometry parameters of an image scene, constructs a scene-based atmospheric profile grid by distance inverse ratio weighted interpolation based on a reanalysis atmospheric profile, and combines a digital elevation model and a view zenith angle to correct and apply terrain and observation geometry constraints to generate control node input parameters. Then, the atmospheric radiation transmission model is called in batches to obtain the hyperspectral results of each control node, and the transmittance and path radiance parameters of the infrared target band are extracted by spectral response function convolution. Finally, the control node parameters are reprojected to the original image coordinates, the four-neighbor-domain bilinear interpolation and nine-neighbor-domain weighted interpolation results are adaptively fused for each pixel, the full-resolution atmospheric parameter field is recovered, and the observed radiance at the ground is inversed.

This invention relates to the field of detection, and in particular to an online method and system for detecting impurities in calcium carbonate ore. Specifically, it includes: acquiring a continuous multispectral image sequence of calcium carbonate ore on a conveyor belt, and performing radiometric correction and spectral normalization preprocessing; identifying dominant spectral clusters of pure calcium carbonate ore by statistically analyzing the pixel spectra of the preprocessed images, and selecting a subset of high-confidence pixel spectra as the initial background training set; training a background dictionary, applying a set of sparse regularization constraints during training, and using the correlation between spectral bands to constrain the atomic energies of the dictionary to continuous or strongly correlated band groups; for each pixel of the detected image, using a sparse approximation algorithm combined with the background dictionary, calculating a sparse reconstruction coefficient vector and a reconstruction residual vector, and obtaining the reconstruction residual and coefficient activation uncertainty measure, respectively; if the reconstruction residual exceeds a first threshold, or the uncertainty measure exceeds a second threshold, it is determined to be an impurity point, and the location and quantity are summarized to generate an online impurity distribution map.

This invention discloses a fully automated atmospheric and topographic radiometric correction method and device for high-resolution remote sensing imagery, belonging to the field of remote sensing science and technology. The method includes: constructing a fully automated batch processing framework; developing an atmospheric correction module based on the 6S radiative transfer model to automatically retrieve atmospheric parameters and eliminate their influence; and developing a topographic radiometric correction module based on the digital elevation model (DEM) and VECA model to compensate for radiometric distortion caused by complex terrain. The key innovation lies in constructing a joint correction framework and integrating a geomorphic feature recognition algorithm, which can automatically identify and select to execute either single atmospheric correction or a combined atmospheric-topographic correction process based on the degree of topographic relief in the image. This invention achieves fully automated batch processing from data input to result output, requiring no manual intervention, significantly improving the processing efficiency, intelligence level, and adaptability to different terrain scenarios in high-resolution image radiometric correction.

This invention discloses a method and system for space target detection and self-calibration photometry in spaceborne star field imaging. The method includes the following steps: acquiring the raw telemetry data stream from the satellite in spaceborne star field imaging mode, and reconstructing a two-dimensional raw image sequence; performing self-calibration radiometric correction, background noise modeling, multi-frame registration, source parameter extraction, and space target discrimination on the raw image sequence to obtain the corresponding stellar background, space targets, and single-frame artifacts; constructing a standard star candidate set and fitting a mapping model from standard star pixel coordinates to celestial coordinates; converting the pixel coordinates of the space target to the corresponding celestial coordinates; performing photometric zero-point fitting and space target photometry operations; and outputting structured space target observation results. This invention relates to the field of space target observation technology. By introducing multi-frame self-calibration radiometric correction, inter-frame geometric registration and multi-frame consistency discrimination, and robust photometric zero-point fitting, reliable observation of spaceborne space targets is achieved.

This invention relates to the field of SAR image processing technology, specifically disclosing a SAR image topographic radiometric correction method that takes into account overlapping and shadowed areas. The method includes acquiring SAR images, DEM images, and source files within the study area; performing multi-view processing on the original SAR images, resampling the DEM images, and performing radiometric calibration; using an indirect positioning method to perform geometric positioning based on an RD model, generating lookup tables A and B, and registering the images; detecting pixels in overlapping and shadowed areas; calculating the effective scattering area corresponding to each SAR pixel; performing radiometric correction based on the effective scattering area, repairing the backscattering coefficient values ​​in shadowed areas, and finally performing geometric correction. This invention, to a certain extent, eliminates the topographic effects caused by the SAR imaging mechanism and terrain undulations, improving the radiometric correction effect in areas with large topographic undulations. The corrected product can be widely used in fields such as ground feature inversion and classification, deformation detection, and target detection.

This invention relates to a method for achieving high frame rate and ultra-large dynamic range in a single scenario. The method involves determining the radiation characteristics of the target based on the detection task and obtaining the spectral range; determining the detector type based on the obtained spectral range and detection requirements; and determining the integration time increments based on the target's radiation characteristics, the dynamic range requirements of the detection scenario, and the capabilities of the detector devices, and calculating the integration time for each increment. T int_N The invention involves calculating the absolute radiometric calibration coefficients for each time level; performing multi-time integration imaging of the detected scene using a remote sensor; and real-time blind pixel replacement and radiometric correction processing on the integrated time imaging results for each time level using a video processing device. A saturation threshold is set, and the relationship between the image DN value and the saturation threshold is determined pixel-by-pixel. The DN value assignment operation is then performed iteratively to generate a fused image without saturation and rich in detail. This invention achieves ultra-large dynamic range target detection without increasing image data capacity.

This invention relates to the technical field of infrared image denoising and enhancement, and particularly provides a method for removing the "pot lid effect" from infrared images based on Planck radiometric calibration. Applied to an infrared imaging system, the method includes the following steps: S10, acquiring an original infrared image; S20, performing adaptive median filtering on each pixel in the original infrared image to obtain a grayscale image; S30, constructing a calibration model between grayscale values ​​and radiance measurements based on Planck's law, and obtaining a calibration coefficient matrix accordingly; S40, using the calibration coefficient matrix to perform radiometric correction on the grayscale image to obtain a radiance image. This invention, by organically combining adaptive median filtering with Planck radiometric calibration, ensures both the purity of the image input and the accuracy of the physical output, and can remove the "pot lid effect" caused by uneven energy reception between the detector's periphery and central region.

The application discloses a kind of robust digital watermarking method and system of remote sensing image based on template embedding, belong to remote sensing image copyright protection technical field.The method includes three stages: watermark embedding stage, receive the remote sensing image to be protected and copyright watermark information, after encoding, copyright watermark information is encrypted to generate Gaussian circular bit template, and with controllable embedding intensity and template intensity embedding image, generate watermark-containing remote sensing image;Distortion simulation stage, construct the custom distortion layer integrated with atmospheric scattering, sensor noise, radiometric correction and geometric distortion simulation, for generating distorted image;Watermark extraction stage, using watermark-containing remote sensing image, distorted image and its watermark message matrix label training watermark extraction network, using the network after training restores the final copyright watermark information from the remote sensing image to be detected.The application significantly improves the robustness and security of watermark in complex processing flow by simulating the specific distortion of remote sensing image.

The application discloses a kind of unmanned aerial vehicle multispectral image radiometric correction method based on satellite image, comprising the following steps: 1) obtain unmanned aerial vehicle multispectral image and the satellite image of the same area similar to unmanned aerial vehicle flight time, uniform to same coordinate system;2) select a variety of uniform ground objects as sampling area, extract corresponding band satellite image reflectivity and unmanned aerial vehicle multispectral image DN value, as sampling data;3) for each spectral band, with satellite image reflectivity as dependent variable, unmanned aerial vehicle multispectral image DN value as independent variable, establish regression model;4) evaluate regression model goodness of fit, when the determination coefficient R 2 <0.8, return to the second step, resample or increase sampling area, when the determination coefficient R 2 >0.8, evaluation passes;5) each band regression model is applied to corresponding band unmanned aerial vehicle multispectral image original image for radiometric correction, and each pixel is calculated.

The application discloses an infrared image adaptive atmospheric correction method and device based on a radiation transmission model, and belongs to the technical field of remote sensing image radiation correction. The method first extracts the spatial range, imaging time and observation geometry parameters of an image scene, constructs a scene-based atmospheric profile grid by distance inverse ratio weighted interpolation based on a reanalysis atmospheric profile, and combines a digital elevation model and a view zenith angle to correct and apply terrain and observation geometry constraints to generate control node input parameters. Then, the atmospheric radiation transmission model is called in batches to obtain the hyperspectral results of each control node, and the transmittance and path radiance parameters of the infrared target band are extracted by spectral response function convolution. Finally, the control node parameters are reprojected to the original image coordinates, the four-neighbor-domain bilinear interpolation and nine-neighbor-domain weighted interpolation results are adaptively fused for each pixel, the full-resolution atmospheric parameter field is recovered, and the observed radiance at the ground is inversed.

The application discloses a black land degradation intelligent evaluation method and system based on multi-source remote sensing images, relates to the technical field of land degradation intelligent evaluation, and realizes intelligent evaluation through multi-source remote sensing data fusion and a double-branch attention deep convolutional neural network; the method first carries out pretreatment such as radiation correction and geometric registration on optical, thermal infrared and radar remote sensing images, and constructs a multi-dimensional data set containing time-series spectra, textures and ground surface temperatures; then key features are extracted in parallel through a spatial branch and a time-series branch, and adaptive weighted fusion is carried out, and finally, a pixel-level degradation grade map and a change trend report are output; the system can automatically, widely and at low cost complete dynamic monitoring of black land degradation, has high evaluation precision and strong timeliness, and provides reliable technical support for accurate protection of black land and improvement of farmland quality.

The application discloses a SAR image filtering method based on structure strength joint consistency, and relates to the technical field of radar remote sensing image processing methods.The method comprises the following steps: acquiring double-time-phase SAR images of the same ground surface monitoring area, performing radiation correction and spatial registration to form a double-time-phase SAR image pair to be processed; respectively calculating structure consistency components and strength consistency components of the double-time-phase SAR image pair, and adopting a product strategy to construct a structure-strength joint consistency coefficient; calculating a spatial self-adaptive filtering weight based on the structure-strength joint consistency coefficient, and automatically adjusting filtering strength of flat areas and edge areas; and adopting a consistency-guided self-adaptive weighted fusion filtering to output a final denoising image.The method can capture real geometric features, effectively distinguish the features, and avoid edge blurring and texture loss.

An AI-supported, intelligent and modular system for monitoring plant health for precision agriculture, consisting of: a deployment device configured for field surveillance, the deployment device being selected either as an airborne drone platform for aerial surveillance or as a ground-based rover platform for ground-based surveillance, depending on the field size and terrain; A detachable sensor module attached to the deployment device for acquiring field monitoring data, wherein the detachable transmitting module comprises: an embedded edge computing unit; a red-green-blue (RGB) camera; a near-infrared (NIR) camera; a temperature sensor; a position sensor; calibration reference targets stored on the edge computing unit; and a wireless communication interface, wherein the embedded edge computing unit is configured to: synchronize data acquisition from the RGB camera, the NIR camera, and the temperature sensor; acquire high-resolution images with the RGB camera and the NIR camera; and record temperature data, humidity data, and metadata including timestamps, elevation, orientation, and coordinates; an external storage medium that is connected via the wireless communication interface to the embedded edge computing unit of the detachable sensor module and receives all data captured by multiple sensors and the camera in real time from the embedded edge computing unit; and A desktop application runs on an external computer device with a processor, and this external computer device is connected to an external storage medium. The data stored on the external storage medium is shared with the desktop application.The desktop application includes a computing module that performs the following functions: retrieving the captured data from the external storage medium; preprocessing the captured data through noise reduction, illumination normalization, radiometric correction, and image alignment; calculating vegetation indices, consisting of the Normalized Difference Vegetation Index (NDVI) and the Green Normalized Difference Vegetation Index (GNDVI), from the preprocessed data; applying artificial intelligence models to identify plant stress states based on the vegetation indices; segmenting an agricultural field into multiple health zones based on the identified plant stress states; assigning a severity level to each health zone; and generating recommendations for each health zone based on the severity level.

The application discloses a kind of small SAR data processing method and system based on PCIe RDMA, it is related to radar signal and information processing technical field, comprising the following steps: S1, data preprocessing: the original echo data received by radar is preprocessed;S2, range compression: the original echo data after preprocessing is compressed in range;S3, azimuth compression: the original echo data compressed in range is compressed in azimuth, and the SAR image of target area is obtained;S4, image post-processing: SAR image is post-processed, and post-processing includes geometric correction, radiation correction and image enhancement.The application adopts the above-mentioned small SAR data processing method and system based on PCIe RDMA, eliminates the data copy overhead of CPU participation in traditional communication model, realizes the direct access of cross-node memory after the interconnection of multiple hosts through PCIe, significantly reduces data transmission delay, and improves system bandwidth.

This invention discloses a water body extraction system and method based on dilated convolution and dynamic serpentine convolution, belonging to the field of remote sensing image processing technology. The method includes: firstly, acquiring historical remote sensing images and performing preprocessing such as radiometric correction, orthorectification, and image fusion to construct a dataset containing water body mask labels; then, constructing a deep learning network model, using a residual multi-scale network for multi-scale feature extraction, integrating features at different levels through a multi-scale feature fusion module, and enhancing the feature extraction capability for narrow water bodies using a dynamic serpentine convolution and attention fusion module; training the network using a training set, and optimizing the model parameters using a cross-entropy loss function and backpropagation algorithm; finally, applying the trained model to the remote sensing image of the water body to be extracted to achieve automatic and accurate extraction of water body information; this invention effectively solves the problems of feature loss in small water bodies and difficulty in extracting narrow water bodies, significantly improving the accuracy and completeness of water body extraction.

This invention discloses an early prevention and warning system for invasive plants driven by UAV multispectral time-series data, belonging to the field of ecological and environmental remote sensing prevention and control technology. It includes a light monitoring module, a radiometric correction module, a spectral stabilization module, a remapping module, and an early warning module. The light monitoring module establishes light monitoring thresholds and cloud shadow mutation capture points during the prevention and warning stage, continuously records illuminance changes, generates illuminance change curves, and marks time periods of abnormal light, forming a preliminary early warning list. This invention weakens the impact of light mutations on multispectral reflectance by linking light monitoring and radiometric correction, maintaining the temporal consistency of images; and achieves temporal and spatial unification through the coordinated processing of spectral stabilization and spatial remapping, enabling UAV monitoring data to possess spectral stability and spatial accuracy in complex environments, thereby improving the accuracy and foresight of invasive plant prevention and warning.

This application discloses a method, apparatus, electronic device, and storage medium for correcting light leakage data, relating to the field of spectral imaging technology. It corrects a first slit image and a second slit image based on dark level correction coefficients and relative radiometric correction coefficients, respectively. A one-dimensional resampling function is used to resample the corrected second slit image and perform relative consistency correction between slits, resulting in a consistent second slit corrected resampled image. The radiometric response value corresponding to the first slit corrected image with light leakage is determined based on the determined target frame number, target band index, and target spatial column index. This radiometric response value is corrected based on a light leakage intensity calibration coefficient. The corrected radiometric response value is subtracted from the radiometric response value of the first slit corrected image with light leakage to obtain the target radiometric response value. This improves the situation where the superposition of spectral information of targets outside the slit affects the spectral data of targets normally imaged within the slit.

This invention relates to the field of remote sensing image recognition technology for Ulva prolifera, specifically a SAR Ulva prolifera remote sensing image monitoring method and system based on maximum likelihood classification. The method includes acquiring the original SAR image of the monitoring area, denoted as the first image; obtaining a second image through radiometric correction, noise reduction, and geometric correction; selecting sample regions from the second image; calculating the image features of each sample region to establish a training sample library; training a maximum likelihood classifier; using the trained maximum likelihood classifier for classification to obtain a preliminary Ulva prolifera classification result image, denoted as the third image; and performing image post-processing on the third image to obtain an optimized Ulva prolifera distribution map. This invention utilizes maximum likelihood classification to classify SAR images, improving the accuracy of Ulva prolifera region identification.

The optical remote sensing satellite image local strip noise fast relative radiation calibration method belongs to the technical field of optical remote sensing images, solves the technical problem that the newly added vertical strip noise of the image cannot be quickly and effectively corrected due to the sudden change of the imaging state of the sensor of the optical remote sensing satellite during the on-orbit operation of the optical remote sensing satellite, and comprises the following steps: searching for a calibration image with a uniform ground object covering strip position; using original calibration coefficients to perform relative radiation correction on the image; calculating strip noise calibration coefficients based on the uniform area image; correcting for two cases of laboratory relative radiation calibration coefficients and on-orbit relative radiation calibration coefficients, and the updated calibration coefficients can adapt to the changed sensor imaging state, and effectively eliminate the newly added local strip noise of the image.