47 results about "Solar flare" patented technology

The invention discloses a flare correction method based on Rayleigh correction reflectivity, and the method comprises the steps: determining VIIRS satellite remote sensing data of a target sea area, generating the Rayleigh correction reflectivity, and determining a flare pollution threshold value of a near-infrared band based on the Rayleigh correction reflectivity; determining a flare correction coefficient of a visible light wave band through a baseline index histogram cosine similarity maximization method; correcting the Rayleigh correction reflectivity data influenced by the flare by using the flare pollution threshold and the flare correction coefficient to obtain corrected Rayleigh correction reflectivity data; and calculating a baseline index based on the corrected Rayleigh correction reflectivity data, and inverting ocean water color parameters. By optimizing the flare correction method, the interference of the solar flare on the remote sensing data is effectively eliminated.

The invention discloses a post-processing method based on a remote sensing image fire point identification result, and relates to the technical field of fire point identification, a sliding time window method is used to acquire a fire point set when a T + 0 period task starts, and fire points comprise coordinates, generation time TG and affiliated attributes of a solar flare angle SG. According to the post-processing method based on the fire point recognition result of the remote sensing image, the correlation of fire points in the space-time dimension is fully utilized, the fire points with adjacent geographic positions in the same time phase are aggregated into a'fire scene ', then the fire scene is filtered by utilizing statistical information of a similar fire point set, 'non-fire scenes' caused by most solar flare angles and the like are eliminated, and the fire point recognition result of the remote sensing image is obtained. The false alarm rate of fire point identification is greatly reduced; and overlapping fire scenes in different time phases are aggregated into a fire event by using a space-time aggregation algorithm, and meanwhile, most of accidental non-fire scenes are further eliminated, so that the false alarm rate of fire point identification is further reduced.

The embodiment of the invention provides a remote sensing image atmospheric correction method and system for an ocean near-shore scene, and relates to the technical field of ocean remote sensing image atmospheric correction. According to the method, after remote sensing data is obtained, solar flare correction is executed by extracting a target mask and using a secondary simulation model of a satellite signal in a solar spectrum. And then a multi-band darkness index is calculated, and an optimal aerosol optical thickness value is inverted through a radiation transmission model. And calculating the atmospheric correction coefficient of each wave band according to the optimal aerosol optical thickness value so as to generate correction result data. According to the method, on the basis of robust flare correction of the SWIR proxy, scene-adaptive flare proxy is constructed by utilizing water body reflection and path radiation physical characteristics of the SWIR under a deepwater condition, and flare deduction is realized. Inversion is carried out through multiband combined darkness indexes, and the spectral characteristics of the deep water body reflected in the visible spectrum are utilized, so that single-band random noise is smoothed, and the accuracy of an AOT estimation result is improved.

The invention belongs to the field of satellite remote sensing fire monitoring, and discloses a satellite remote sensing forest fire initial fire point monitoring method, which comprises the following steps: acquiring satellite data as input data; reading the zenith angle of the sun in the satellite data, and judging the time period as a day time period, a night time period and a morning and night junction time period; the solar zenith angle, the sensor zenith angle and the like need to be read in daytime period data so as to filter solar flares; carrying out simple cloud detection on data in all time periods by utilizing 11-micron channel brightness temperature and 11-4-micron channel brightness temperature, expanding an adaptive window by taking a suspected initial fire point pixel as a center, and calculating 4-micron channel brightness temperature difference, 11-micron channel brightness temperature difference and 4-11-micron channel brightness temperature difference of a background pixel by utilizing a time sequence method; and counting the mean value and the standard deviation of the background pixels, and confirming and extracting a forecast initial fire point by using a normal distribution starting point algorithm. According to the method, the timeliness and accuracy of early warning of the fire disaster are improved, and important technical support is provided for forest fire prevention decision making.

The invention provides a sea surface dynamic target rapid detection method and device in a polarization change scene, and belongs to the field of photoelectric detection, polarization imaging and target detection, and the method comprises the steps: obtaining the latitude and longitude, attitude angle and world time of a platform through a navigation positioning system; judging whether the current imaging area falls into a solar flare area or not in real time by combining a sun position calculation model; when a flare area is judged, recording the brightness of the image at each angle and locking an optimal polarization angle corresponding to the minimum brightness, and then tracking and adjusting the optimal polarization angle in real time according to the attitude of the platform; when it is judged that the polaroid is a non-flare area, the displacement table is driven to integrally move the polaroid out of the light path; and performing target detection processing based on the deep network on the low-flare image obtained when the polarizer is in the light path, and outputting the position and the category of the ship target. According to the invention, continuous, stable and efficient identification of targets such as ships and warships in the strong flare interference area is realized.

The present invention discloses a method for identifying sudden ionospheric disturbance events based on ionospheric vertical sounding data, comprising the following steps: Step 1, collecting and organizing fmin and foF2 data from each ionospheric observation station during a historical M5.0 solar flare eruption that occurred during daytime in my country; Step 2, calculating the ratio of fmin to foF2 data at each ionospheric observation station at the corresponding time, statistically analyzing the distribution of fmin / foF2, and determining the different intensity levels of ionospheric absorption at each ionospheric observation station; Step 3, determining the intensity level of the sudden ionospheric disturbance event. The method for identifying sudden ionospheric disturbance events disclosed by the present invention utilizes the minimum echo frequency of the ionospheric vertical sounding ionogram and the ionospheric critical frequency to calculate an absorption index representing the degree of ionospheric absorption. This method can simply and directly characterize the degree of ionospheric absorption in a certain region and can provide ionospheric absorption information for different regions of my country for shortwave and other electronic information systems.

The application discloses a flare occurrence position determination method and device, electronic equipment and computer medium. The method comprises the following steps: when it is determined that a flare occurs, a flare peak time, a full-disk image corresponding to the flare peak time and initial disk positions of each solar active region are obtained; according to the flare peak time and the initial disk positions of each solar active region, first disk positions of each solar active region corresponding to the flare peak time are determined; the first disk positions of each solar active region are subjected to coordinate system conversion, and pixel positions of each solar active region in the full-disk image are determined; according to the pixel positions of each solar active region and the full-disk image, first pixel values of regions in which each solar active region is located in the full-disk image are respectively calculated; and the first disk position of a solar active region corresponding to a maximum value is determined as the occurrence position of the flare. The application can accurately determine the occurrence position of the flare when the flare occurs.

The utility model provides an optical lens and an electronic device, the optical lens comprises at least four optical lenses, and the at least four optical lenses comprise a first optical lens, a second optical lens, a third optical lens and a fourth optical lens from the object side to the image side of the optical lens. The at least four optical lenses include a blue glass lens. Therefore, by adding the blue glass material in the optical lens, a blue glass plate is omitted to prevent visible light from being reflected to the photosensitive element, petal-shaped solar flares are reduced, and the imaging quality is improved.

A system for forecasting when solar flares will occur and identifying their possible locations creates a mask to analyze an image of a solar disk. The system also creates an intensity histogram using the solar disk. Additionally, the system stores a resulting full-disk image and a sub-image identifying possible flare signature sites. Further, the system applies a method to filter out false positive detections by using an equation that enhances true positive pre-flare signatures and minimizes false positive signatures.

The invention relates to the technical field of camera lenses, in particular to a flare removal method based on dynamic frequency domain guidance and a contrast learning module. The method comprises the following steps: S1, separating flare artifacts and content information by a global frequency domain dynamic guide module through a global frequency domain weight of a dynamic optimization feature, and guiding a network to retain the content information while removing the artifacts; and S2, guiding the local features of the light source to be aligned with the reference image through a local detail guiding module. According to the solar flare removal method based on the dynamic frequency domain guidance and the contrast learning module, global frequency domain features are dynamically optimized, a network is guided to perceive frequency characteristics of solar flare artifacts, solar flare information and content information are decoupled, and interference of the artifacts on surrounding content information is suppressed while the artifacts are eliminated; and then introducing a contrast learning strategy to guide the local features of the light source to align with the reference image so as to effectively inhibit local detail damage caused by flare removal and further promote the image to realize active-oriented refined recovery.

The disclosed technology provides solutions for applying a flare detection model to an image for detecting road flares in an environment by an autonomous vehicle (AV). A method comprises accessing a flare detection model that is trained to recognize a bounded outer region and a bounded inner region; and detect a flare object within the bounded inner region and refrain from detecting an object in the bounded outer region; applying the flare detection model to an image of the environment to recognize an outer region corresponding to a glow of a flare and an inner region that corresponds to the flare in the environment; and detecting the flare in the environment within the inner region based on the inner region being recognized by the flare detection model and contained within the outer region that is also recognized by the flare detection model. Systems and machine-readable media are also provided.

This invention relates to the field of image processing technology, providing a method for removing nighttime flares based on the law of illumination and dynamic masking. The method includes: using a pre-trained depth estimation model to process a background image and a flare image based on the law of illumination to obtain a baseline image for the deep learning model; processing the baseline image of the deep learning model through a dynamic masking module to obtain an input image for the deep learning model; inputting the input image of the deep learning model into a neural network model; concatenating the output of the neural network model with the baseline image of the deep learning model; and finally, passing the convolutional layer to obtain an image with the flares removed. This invention constrains the strength relationships between multiple flares through the law of illumination and depth estimation, enabling the synthesis of a flare dataset that better conforms to the physical laws of the real world. Furthermore, the dynamic masking module allows the model to focus more on processing the flare region, achieving excellent image restoration results.

The invention provides a solar flare whole-process observation and analysis method and system, and the method comprises the steps: inputting an obtained coding grayscale image and an interference coding mask into a target spectrum neural network model, and obtaining a plurality of groups of reconstructed three-dimensional hyperspectral data; stacking a plurality of groups of three-dimensional hyperspectral data under the same optical filter wavelength according to the polarization dimension to obtain a plurality of groups of hyperspectral polarization data; performing multi-frame superposition noise reduction processing and space-time registration on the multiple groups of hyperspectral polarization data to obtain processed hyperspectral polarization data; performing dynamic inversion based on the processed hyperspectral polarization data to obtain a first physical parameter and a second physical parameter; and generating early warning information based on an evolution stage division result and an abnormal feature recognition result obtained through the first physical parameter and the second physical parameter. According to the method, the leak detection rate and the whole process delay of the key stage of flare observation are reduced, the analysis accuracy of the core physical parameters of the flare is improved, and the observation integrity, the real-time performance, the precision and the robustness are comprehensively improved.

The application discloses a sunspot region correlation evaluation method based on cross-validation, and comprises the following steps: 1, obtaining a flare dataset, and performing dataset segmentation according to sunspot region numbers to obtain each data subset; 2, performing machine learning algorithm training on each data subset to obtain a machine learning model of the data subset; 3, calculating a corresponding AUC index for each machine learning model to obtain an A matrix; 4, performing correlation analysis by using the A matrix to obtain a correlation index Corr; and 5, judging the correlation index Corr to obtain a given region correlation determination conclusion. The application provides a calculation method of the correlation index, which can simplify the process of establishing a prediction algorithm to a certain extent, and in the process of using federal transfer learning, can aggregate algorithms of sunspot regions with high similarity to speed up the training process and then improve the prediction efficiency.

This invention relates to a dynamic target detection and tracking method for unmanned surface vessel (USV) remote sensing images. It includes the following steps: a) employing adaptive sensor fusion technology to integrate radar, optical, and infrared sensors for all-weather, multimodal target detection; b) using deep learning spatiotemporal fusion technology, employing 3D convolutional neural networks or LSTM to capture the spatiotemporal features of dynamic targets; c) using unsupervised anomaly detection technology to train models for common maritime scenes to identify and track anomalous targets; d) implementing water surface reflection reduction technology to reduce the impact of water surface reflection and solar flare; e) applying an adaptive occlusion handling strategy, using a predictive model to maintain target tracking even when the target is occluded by waves or other objects; f) utilizing a multi-task deep network for target detection, classification, velocity estimation, and orientation prediction; g) implementing wave adaptive correction, using machine learning to correct image distortions caused by water surface waves in real time.

The invention provides a flare-removing water surface target segmentation method and system based on polarization feature fusion, and the method comprises the steps: firstly constructing a polarization multi-feature deep fusion frame, and remarkably improving the recognition capability of a small target in a complex environment, such as strong dazzle light, through the combined utilization of the polarization features of the degree of polarization (DOLP), the polarization angle (AOP) and the parallel polarization radiation (PPR); secondly, designing a GFNet enhanced network based on a Retinex theory, carrying out coding separation and fusion on PPR and AOP images, inhibiting dazzle light, enhancing target details, and outputting a high-quality enhanced image (PPRen); and finally, constructing a CDDFuse fusion network and designing a two-stage training mechanism, firstly training the GFNet to enhance the network and optimize the dazzle light removal capability, and then training the CDDFuse fusion network by adopting PPRen and DOLP to realize frequency domain feature decomposition and fusion, thereby improving the target and background distinguishing capability and remarkably improving the segmentation precision and robustness of the system.

A method of processing a substrate, including generating a mask density map based on a photomask, the mask density map spatially mapping transparent regions of the photomask and blocking regions of the photomask that block radiation at a predetermined wavelength; generating a flare map based on the mask density map, the flare map spatially indicating a projected amount of received radiation in excess of a desired amount of radiation at each coordinate location on the photomask; and generating a critical dimension modification map based on the flare map, the critical dimension modification map including a modification energy dosage for each coordinate location on the photomask.

The invention discloses a flare occurrence position determination method and device, electronic equipment and a computer medium. The method comprises the following steps: when it is determined that a flare occurs, acquiring flare peak time, a full-solar-surface image corresponding to the flare peak time and an initial solar-surface position of each solar active area; according to the solar flare peak time and the initial solar surface position of each solar active area, determining a first solar surface position corresponding to each solar active area at the solar flare peak time; performing coordinate system conversion on the first solar surface position of each solar activity area, and determining the pixel position of each solar activity area in the full solar surface image; according to the pixel position of each solar activity area and the full-solar-surface image, respectively calculating a first pixel value of each solar activity area in an area where the full-solar-surface image is located; and determining the first solar surface position of the solar active area corresponding to the maximum value as the occurrence position of the flare. According to the invention, the occurrence position of the flare can be accurately determined when the flare occurs.

The present application discloses a high-precision airborne remote sensing sea drift garbage monitoring method based on polarization filtering. The steps include: collecting a remote sensing image set of the sea drift garbage area; preprocessing the remote sensing image set to obtain a processed image set; constructing a spatio-temporal information sequence based on the processed image set; performing garbage recognition and garbage annotation on the processed image set; obtaining the information of the garbage according to the spatio-temporal information sequence and sending the information to the cleaning personnel to complete garbage cleaning. By using polarization imaging, the present application filters out the reflected light of the solar flare caused by the undulation of the sea surface waves, reduces the interference light parameters of the solar flare reflection in the remote sensing image, and improves the monitoring accuracy. At the same time, by constructing the spatio-temporal information sequence of the sea surface, the position of the garbage can be quickly and rapidly locked and marked through the spatio-temporal information sequence, greatly improving the monitoring efficiency and reducing the cleaning cost.

The invention provides a solar flare real-time correction method and system for a low-dip-angle meteorological satellite. The method comprises the following steps: acquiring data of a satellite at a to-be-corrected moment; the read satellite data is preprocessed; pre-processed satellite data are loaded, a judgment threshold value is set, a training sample pair is formed, and a simulation coefficient of a target channel is obtained and output through multiple linear regression; calculating simulated brightness temperature data of the target channel according to the obtained simulation coefficient, and calculating an identification index of solar flare pollution based on the actual observation brightness temperature data and the simulated brightness temperature of the target channel; according to the identification indexes of solar flare pollution, analyzing the relationship between the solar flare angle and the solar flare pollution characteristics so as to determine the critical threshold value of the solar flare angle; and correcting the satellite data polluted by the solar flares according to the critical threshold value of the solar flare angle. According to the invention, the critical threshold value of the solar flare angle is stably and accurately obtained in real time, and the solar flare pollution area is dynamically detected and corrected.

The application discloses a kind of solar flare X-ray full-link simulation method and system based on Geant4, belong to space satellite detection and numerical simulation technical field.The method includes: build high-performance hybrid parallel computing platform based on Geant4;Based on the platform, construct layered magnetized solar atmosphere model, configure physical process list and generate high-energy electron particle source;Through light tracing algorithm and self-defined step action module, the transmission, scattering and polarization evolution of X-ray in layered magnetized solar atmosphere are tracked and simulated;Through pixelated imaging and data output module, photon information is mapped to multiple virtual detector imaging planes, and X-ray imaging, energy spectrum and polarization degree data of different observation angles are output.The application solves the problems of existing model and multi-satellite stereoscopic observation data mismatch, Compton scattering details missing, polarization information deficiency and low computing efficiency, and provides an effective tool for analysis and simulation of multi-satellite joint observation data.

A method for quantifying disorder and extracting a corresponding numerical value of an order parameter from contrast analysis applied to optical images acquired of the solar photosphere. Temporal variation of the order parameter may be utilized to predict events such as solar flares, which have the ability to disrupt both communication systems and satellite orbits. The degree of order of the photosphere may be monitored to predict solar flares and other solar events. The method may utilize a spin-based (Ising / Potts) model of disorder.

The invention belongs to the technical field of remote sensing image processing and computer vision, and discloses a marine oil spill segmentation method and system based on a spatial spectrum frequency constraint diffusion model. Preprocessing the multispectral remote sensing image to obtain reflectivity data after Rayleigh correction; inputting the reflectivity data into a trained spatial-spectral frequency constraint diffusion model, and generating an oil spill segmentation mask through iterative denoising; wherein the spatial spectrum frequency constraint diffusion model is integrated with a double-branch frequency analyzer (DF-P) and a spatial spectrum attention condition coding module (SS-A). Through innovative architecture design, end-to-end oil spill accurate segmentation under the condition of cross-sun flare is realized, the segmentation performance is remarkably improved, and the core design thought also has important reference value for similar optical remote sensing ground feature segmentation tasks; and meanwhile, more powerful technical support can be provided for marine environment protection and oil spill emergency response.

The invention relates to a carbon monitoring satellite ocean flare tracking observation method. The method comprises the following steps: calculating a position vector Rsg of a sea surface solar reflection point under an inertial coordinate system; calculating a solar vector, and obtaining a satellite position vector through a linearized J2 perturbation model; defining a function f (betax) between an included angle beta between a sea surface solar reflection point position vector and a sun vector, an included angle between a sea surface solar reflection point position ellipsoid normal vector and a vector pointing to the satellite from the sea surface solar reflection point, and an included angle between the sea surface solar reflection point position ellipsoid normal vector and a vector pointing to the sun from the sea surface solar reflection point; solving a zero point of the function f (betax) by using a bisection method to determine an included angle beta; calculating a sea surface solar reflection point position vector Rsg by using the included angle beta; and converting the position vector Rsg of the sea surface solar reflection point into an earth fixed connection coordinate system, and calculating the longitude and latitude positions of the sea surface solar reflection point on the earth surface. The solar flare observation method is high in calculation precision and meets the satellite observation requirement.

An X-ray solar imaging energy disperse spectroscopy covering Fe characteristic peaks belongs to the technical field of space X-ray detection, and comprises a nested X-ray focusing optical system, an X-ray imaging detection unit and a support shielding structure. The nested X-ray focusing optical system comprises an X-ray collimator assembly and an X-ray grazing incidence lens assembly. The effective observation area of the solar X-rays is enlarged through the multi-layer nesting of the X-ray lenses, and the observation of the solar X-rays with higher energy can be supported. The front end of the X-ray collimator assembly is covered with a shading film, so that solar heat entering the instrument is reduced, and the X-ray transmittance is guaranteed. The X-ray imaging detection unit comprises a shading film, an imaging detector and an imaging reading circuit. X-ray high-resolution imaging of solar flares is realized by adopting the X-ray imaging detector. The dynamic detection range of the instrument is improved through local high-speed reading of the solar flare imaging area.

The invention discloses a solar flare prediction model construction method based on intelligent survival analysis support, and the method comprises the steps: 1, defining main parameters in survival analysis in combination with a solar flare prediction scene; step 2, carrying out data preprocessing on the solar flare observation data; step 3, constructing a hybrid model combining LSTM (Long Short Term Memory) and DeepSurv (DeepSurv); step 4, training of a hybrid model combining LSTM and DeepSurv is carried out; and step 5, performing prediction and visualization after model training. By using the method of the invention, a time sequence characteristic and survival analysis fused extensible network can be constructed, solar flare prediction performance can be evaluated, and outbreak time prediction understanding can be assisted.

The invention discloses a Geant4-based solar flare X-ray full-link simulation method and system, and belongs to the technical field of space satellite detection and numerical simulation. The method comprises the following steps: building a Geant4-based high-performance hybrid parallel computing platform; a layered magnetization solar atmosphere model is constructed based on the platform, a physical process list is configured, and a high-energy electron particle source is generated; through a ray tracing algorithm and a user-defined stepping action module, tracking simulation is carried out on transmission, scattering and polarization evolution of X-rays in the layered magnetized solar atmosphere; and through a pixelated imaging and data output module, the photon information is mapped to imaging planes of a plurality of virtual detectors, and X-ray imaging pictures, energy spectrums and polarization degree data of different observation visual angles are output. The problems that an existing model is not matched with multi-satellite stereoscopic observation data, Compton scattering details are missing, polarization information is insufficient and calculation efficiency is low are solved, and an effective tool is provided for analysis and simulation of multi-satellite combined observation data.

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Automated systems and methods are provided for continuous monitoring of the flaring of waste gas at an industrial facility, which employ an RGB camera operably coupled to a gateway device by a data communication interface. The RGB camera is configured to capture time-series color image frames of a flare and communicate the time-series color image frames to the gateway device. The gateway device includes an image processing module and a flare optimization module executing on the gateway device. The image processing module is configured to process the time-series color image frames to determine at least one flare parameter that provides a qualitative measurement of the combustion efficiency of the flare over time. The flare optimization module is configured to adjust relative amount of waste gas to at least one assist gas for the flare based on the at least one flare parameter to continuously optimize the combustion efficiency of the flare.

Systems, methods, and computer-readable media are disclosed for identifying light flares in images. An example method may involve receiving an image from an imaging device, the image including data indicative of a flare artifact originating from a region of the image. The example method may also involve determining, based on the image data, a first array of pixels extending radially outwards from the region and a second array of pixels extending radially outwards from the region. The example method may also involve creating, based on the image data, a flare array, the flare array including the first array of pixels and the second array of pixels. The example method may also involve determining, based on the flare array, a peak flare artifact value indicative of a size of the flare artifact; and determining, based on the peak flare artifact value, a flare artifact score for the imaging device.