343 results about "Spatiotemporal resolution" patented technology

A system and method for increasing space or time resolution of an image sequence by combination of a plurality input sources with different space-time resolutions such that the single output displays increased accuracy and clarity without the calculation of motion vectors. This system of enhancement may be used on any optical recording device, including but not limited to digital video, analog video, still pictures of any format and so forth. The present invention includes support for example for such features as single frame resolution increase, combination of a number of still pictures, the option to calibrate spatial or temporal enhancement or any combination thereof, increased video resolution by using high-resolution still cameras as enhancement additions and may optionally be implemented using a camera synchronization method.

The invention provides an atmospheric pollution source grading method based on a pollutant source identification technology. The atmospheric pollution source grading method based on a pollutant source identification technology belongs to the technical field of atmospheric environment planning management, and prevention and control of pollution. The atmospheric pollution source grading method based on a pollutant source identification technology comprises the following steps of carrying out high spatio-temporal resolution meteorological simulation of a researched area based on a meteorological model, carrying out grid division of the researched area based on the geographic information system (GIS), arranging concentration contribution evaluation points, collecting pollution source discharge information, building a weather-air quality model coupled system, computing a sensitive factor, identifying sensitive discharge areas, carrying out unitization processing of the sensitive factor, and carrying out grading identification of pollution sources according to pollutant discharge loads and the order of the sensitive discharge areas. The invention aims at providing the atmospheric pollution source grading method based on a pollutant source identification technology so that the evaluation and quantitative grading of sensibility of atmospheric pollution sources are realized and an effective technical support for scientific pollutant-discharge reduction is provided.

A video super-resolution method that combines information from different spatial-temporal resolution cameras by constructing a personalized dictionary from a high resolution image of a scene resulting in a domain specific prior that performs better than a general dictionary built from images.

The invention discloses a multiresolution CNN-based millimeter-wave radar cloud map segmentation method, and belongs to the field of image segmentation. The method comprises the following steps of: obtaining a high-temporal-spatial resolution cloud evolution map of a horizontal / vertical structure by utilizing millimeter wave cloud radar, wherein the information of a context of the cloud map is fully utilized; learning local and global features of the cloud map through respectively inputting three image areas with different resolutions into three CNN networks configured with same parameters; classifying the learned features into cloud features and non-cloud features through classifiers of the neural networks, so as to realize the segmentation of the cloud map; and finally combining the segmentation results of the three networks so as to ensure that the segmentation correctness of the cloud map is up to 99.67%.

The invention discloses a multi-source monitoring technology fusion-based ground subsidence integrated monitoring method. The method comprises laying benchmarks and GPS monitoring points in a ground subsidence focal monitoring area, laying a CR-GPS-benchmark integrated point in a ground stable region, in the same time sequence, acquiring GPS data, ground meteorological data, MODIS data, SAR images and leveling data, calculating GPS data through the combination of synchronous observation data from surrounding CGPS stations and IGS stations and ground meteorological data, calculating atmospheric delay phase information through the combination of GPS data, ground meteorological data and MODIS data, extracting stable PS point and PS point deformation information in an initial differential interferometric phase map, building a ground subsidence vertical deformation field through deformation formation corresponding to the PS points, GPS points, benchmarks and integrated points, constructing a spatial data field through fusion of a horizontal deformation field and a vertical deformation field and acquiring ground subsidence three-dimensional deformation field information having high temporal-spatial resolution. The method can acquire ground three-dimensional deformation information with a large range, a high precision and high temporal-spatial resolution.

The invention discloses a method for constructing high temporal-spatial remote sensing data. A CDSTARFM (combining downscale mixed pixel with spatial and temporal adaptive reflectance fusion model (STARFM)) method performs downscaling treatment on low-resolution data by using a downscale mixed pixel algorithm, replaces direct resample low-resolution data in the STARFM algorithm with the downscaled data, and performs data fusion by using a CDSTARFM algorithm. The method may effectively solve a phenomenon of image spots in downscale mixed pixel data fusion and a problem that it is difficult for the STARFM model to find a pure MODIS pixel. The method constructs the high temporal-spatial-resolution remote sensing data by using Landsat8 and MODIS data. A result manifests that the method has higher fusion precision than the STARFM and downscale mixed pixel algorithms.

Described herein are systems and methods for noninvasive functional brain imaging using low-coherence interferometry (e.g., for the purpose of creating a brain computer interface with higher spatiotemporal resolution). One variation of a system and method comprises optical interference components and techniques using a lock-in camera. The system comprises a light source and a processor configured to rapidly phase-shift the reference light beam across a pre-selected set of phase shifts or offsets, to store a set of interference patterns associated with each of these pre-selected phase shifts, and to process these stored interference patterns to compute an estimate of the number of photons traveling between a light source and the lock-in camera detector for which the path length falls within a user-defined path length range.

The invention relates to an active phased array weather radar system based on a full-digital array. The system comprises a signal processing machine which is used for emitting a wave beam, receiving the wave beam and processing echo data; the signal processing machine is in bidirectional communication with a monitoring terminal and a product terminal through network; the signal processing machine is connected with a first high-speed large-capacity wavelength division multiplexing optical fiber communication machine through first optical fibers; the first high-speed large-capacity wavelength division multiplexing optical fiber communication machine is connected with a second high-speed large-capacity wavelength division multiplexing optical fiber communication machine through second optical fibers; a collector ring sleeves the second optical fibers; the second high-speed large-capacity wavelength division multiplexing optical fiber communication machine is in bidirectional communication with a correcting branch and a full-digital array module; the full-digital array module is connected with an antenna array through a correction network. According to the system, a distributive receiving-transmitting assembly is adopted to improve the working reliability of a radar; the electric scanning is performed for the wave beam, so that the flexibility and variation are ensured, a plurality of wave beams can be received at the same time, and the scanning is fast; the system can work in a plurality of working modes, and the temporal-spatial resolution is high.

The invention discloses an ocean buoy platform laser radar three-dimensional wind field cross section detection system which can be used for performing open sea automatic observation and is low in cost, high in measurement accuracy, high in temporal-spatial resolution, continuous in real time and reliable for a long time. The technical scheme is as follows: the detection system is characterized by consisting of a wind measuring laser radar (1), a buoy platform (2), a meteorological data observation module (3), a sea surface data observation module (4), a buoy platform attitude measurement module (5), a laser radar wind field compensation module (6) and an output unit (7), wherein the meteorological data observation module (3), the sea surface data observation module (4), the buoy platform attitude measurement module (5) and the laser radar wind field compensation module (6) are connected with the output unit (7) respectively and transmit signals to a specified client through a communication antenna, and the buoy platform attitude measurement module (5) is also connected with the laser radar wind field compensation module (6). The invention also discloses an ocean buoy platform laser radar three-dimensional wind field cross section detection method.

The invention provides a fusion method and device of a multisource sea surface wind field. The fusion method comprises the following steps: obtaining multisource sea surface wind field data which comprises sea surface wind field data and / or multiple pieces of reanalysis meteorological sea surface wind field data collected by a plurality of satellite borne microwave remote sensors; according to a preset temporal-spatial resolution, independently carrying out meshing processing on the sea surface wind field data obtained by each satellite borne microwave remote sensor to obtain multiple pieces of corresponding sea surface wind field data with the equal longitude and latitude; and utilizing a temporal-spatial interpolation algorithm to carry out interpolation calculation on all sea surface wind field data with the equal longitude and latitude to obtain fusion sea surface wind field data. The fusion method can perform the advantage of the cooperative observation of a multisource satellite, can effectively improve the coverage range and the temporal-spatial resolution of the sea surface wind field data through the fusion sea surface wind field data constructed by the fusion of satellite remote sensing wind field data and / or reanalysis meteorological sea surface wind field data on a premise that meso-and micro-scale characteristic information can be kept, and can better meet the requirements of numerical weather prediction, marine forecasting research and marine meso-and micro-scale system research.

Variable-density (VD), sequentially-interleaved sampling of k-space coupled with the acquisition of reference frames of data is carried out to improve spatiotemporal resolution, image quality, and signal-to-noise ratio (SNR) of dynamic images. In one example, ktSENSE is implemented with a non-static regularization image, such as that provided by RIGR or similar technique, to acquire and reconstruct dynamic images. The integration of ktSENSE and RIGR, for example, provides dynamic images with higher spatiotemporal resolution and lower image artifacts compared to dynamic images acquired and reconstructed using ktSENSE alone.

An efficient method for the extraction of hemodynamic responses in Near-Infrared Spectroscopy (NIRS) systems is proposed to increase the spatial and temporal resolution without hardware overhead. The performance improvement is attributed to high Signal-to-Noise-Ratio (SNR) receivers, a modulation scheme, and a Multi-Input-Multi-Output (MIMO) based data extraction algorithm. The proposed system shows an over 2× increment in the figure of merit (FOM) compared to conventional designs. Experimental results support the validity of the proposed system.

The invention discloses a preparation method of a ground-based observation air temperature space-time data set. The method comprises the following steps: firstly determining space-time resolution ratio and area range of a precast data set; preprocessing air temperature observation data so as to form a normative driving data set; preparing a macro geographic factor and microcosmic geographic factor grid data set of a research area so as to enable the macro geographic factor and microcosmic geographic factor grid data set to correspond to the space-time resolution ratio of the research area; constructing a wavelet neural network dynamic combined prediction model in the time dimension, performing simulation prediction on the change characteristics of air temperature data so as to form a future air temperature change time sequence set; calculating air temperature numerical values of grids in a target area one by one in the space dimension, so as to generate a spatial data set of air temperature spatial change trends; performing simulation calculation on air temperature in the time dimension and the space dimension simultaneously based on key influence factors so as to generate an air temperature future space-time change scene predication data set. The preparation method has favorable expansibility and can be popularized and applied to preparation and production of space-time data products of other observation elements of a geoscience station.

The invention discloses a Landsat8 and MODIS fusion-construction high space-time resolution data identification autumn grain crop method. The method mainly comprises the following steps of carrying out data preparation; carrying out data preprocessing; using a STDFA model to construct data; carrying out data filtering processing; carrying out autumn grain crop identification characteristic vector selection; carrying out autumn grain crop identification characteristic combination and carrying out SVM classification to acquire an identification result. By using the method in the invention, autumn grain crop types can be effectively distinguished; a problem that high resolution data is insufficient during an autumn grain crop identification process can be solved to some extent. According to an experiment result, each precision of the autumn grain crop identification reaches high identification precision and a situation that phenological data contributes to the autumn grain crop identification is verified to some extent.

The invention discloses a fine granular scalable coding scheme of motion vectors. Firstly, a motion vector quantization algorithm is adopted to form a motion vector base layer and a motion vector enforcement layer; then by using a fractional bit-plane encoding, the fractional bit-plane encoding is carried out for the motion vector quantization residual to form a feasible truncation point of a motion vector subplane; and then by using a motion vector coding rate optimization, an optimized motion vector truncation point is formed; finally by using a joint rate allocation, allocation of a joint rate is carried out for a motion vector data and a motion estimation residual data to get a code stream fitting with the need of users for the code stream and a temporal and spatial resolution. Therefore, the problem of the video transmission and video application is improved under the condition of low code stream and the ability of scalable video code stream to satisfy different terminal users is strengthened.

The invention discloses a method and system for generating an earth surface albedo product, which relate to the satellite remote sensing field. The method comprises the following steps of: according to classified POLDER BRDF data, obtaining POLDER albedo data and converting the POLDER albedo data to obtain wide waveband earth surface albedo data; according to sample MODIS earth surface albedo data and the wide waveband earth surface albedo data, building a first conversion model to obtain first earth surface albedo data; according to sample MODIS surface appearance albedo data and the wide waveband earth surface albedo data, building a second conversion model to obtain second earth surface albedo data; and integrating the first and second earth surface albedo data and the MODIS earth surface albedo data divided by grids to generate the earth surface albedo product with space-time continuum. According to the invention, the earth surface albedo product with long-time sequence, space-time continuum and high space-time resolution is generated and the inversion accuracy of the earth surface albedo product is improved.

The invention discloses a method for forecasting and warning an accident consequence of a major hazard installation by combining with real-time meteorological information. The accident of the hazard installation is simulated by combining a high-spatial and temporal resolution atmospheric circulation numerical simulation and forecasting method with a gas dispersion simulation method, simultaneously adding an integrated forecasting method of a danger emission estimation method and a simulated data result post-processing method and combining with the real-time meteorological information and the real-time monitoring information of the hazard installation to obtain the quantitative three-dimensional spatial and temporal distribution result of hazardous gas after the accident occurs and the influence scope and the duration of the accident on an ambient environment; the hazard level and the like on a human body is analyzed and forecasted to obtain the three-dimensional spatial distribution condition of the poisonous and hazardous gas after the accident occurs and the quantitative pollutant concentration number of every target point. The invention provides a method which can be used for forecasting the accident consequence and an automatic evaluation method for hazard level of the accident. The method for forecasting and warning the accident consequence of the major hazard installation by combining with the real-time meteorological information has the characteristics that spatial and temporal spacing, such as the meteorological information, results and the like can be read in real time, the computing speed is high, the real-time performance is strong and the like.

The invention belongs to the field of plasma diagnosis computer processing, in particular to a processing method and device for multi-channel energy spectrum measurement. The processing method includes the following steps: collecting a pulse signal sent by a probe and converting it into a digital pulse signal; counting and classifying the digitized pulse signal to obtain a count spectrum; converting the count spectrum into an energy spectrum; The energy attenuation produced by the beryllium foil is reduced, and the energy spectrum obtained in the third step is restored; the energy spectrum after reduction is smoothed and peaked and fitted to obtain the electron temperature. The processing device includes a pulse signal generation module, a high-speed acquisition card, an analog / digital signal conversion module, a high-speed cache module, and a processor unit with an energy counting module and a temperature calculation module. The problems of common multi-channel energy spectrum measurement and processing methods, such as high hardware cost, strong equipment specificity, limited number of energy channels, low spatial and temporal resolution, and inability to save original signals, are solved.

The invention relates to a synergy self-adaption observing method. 360-degree omnibearing scanning is completed by each radar in a weather radar network within an angle of elevation ranging from 1 degree to 5 degrees; time continuous data of a whole observing region is contained, all radar terminal programs read the data and conduct preprocessing; then an interested key area is found by weather commands and detection arithmetic processing observing data in control; according to AOI information, a weighted value of the AOI is calculated by a method of weighting; priority of the AOI is determined; the AOI information is uploaded to a control center; a region to scan is determined by the control center, and a scanning strategy is formed; at last, an adaptive scan pattern is conducted by all radars according to the scanning strategy. The synergy self-adaption observing method solves the problem that how to select the key region and conduct synergy self-adaption observation by a plurality of radars, deficiency of long-range radars is overcome, and the information with higher temporal-spatial resolution is obtained.

The present invention relates to the quantitative remote sensing data processing technology, and discloses space-time integrated fusion method of remote sensing land surface temperature data. The method comprises first pre-processing the remote sensing land surface temperature data, then solving land surface temperature diurnal change model parameters by using multidate temperature data and corresponding time, thus to realize space seamlessness, screening similar picture elements window by window on polar orbit satellite land surface temperature image data, and in combination with weight factors such as time difference, scale difference, similarity difference and Euclidean distance composed by an multidate motionless satellite and the above model, commonly establishing a space-time integrated fusion model and solving a high temporal-spatial resolution land surface temperature dataset for generating space seamlessness. According to the method provided by the present invention, space-time complementary information of land surface temperature data of the polar orbit satellite and the multidate motionless satellite and diurnal change rules of motionless satellite land surface temperature are fully utilized, and no auxiliary data is required, such that the method is easy to realize, high in practical value and applicable to remote sensing land surface temperature data operational running with seamless space and time.

The present invention provides a method for production of high spatial and temporal resolution NDVI (Normalized Difference Vegetation Index) based on spatial and temporal weight. The method comprises: NDVI data with a low spatial and temporal resolution at t1 time, NDVI data with a high spatial and temporal resolution and NDVI data with a low spatial and temporal resolution at tp time are subjected to mixed pixel decomposition and spatial interpolation to obtain two NDVI increments with the high spatial and temporal resolution data in time domain; employing Bayesian model average method to perform weight combination calculation of the two DNVI increments, and obtaining the NDVI synthesis increment of each pixel; and finally adding the NDVI synthesis increment to the NDVI with the high spatial and temporal resolution to obtain required NDVI with the high spatial and temporal resolution. The two NDVI increments are subjected to Bayesian integration, and the spatial and temporal relationship between geographical data is fully employed to provide an effective method for production of vegetation indexes with the high spatial and temporal resolution.

The present application relates to a meteorological data management method, which comprises the following steps: establishing a spatio-temporal resolution standard of multi-source meteorological data,and establishing a standard unified multi-dimensional grid weather data set; Establishing a data processing and data conversion standard based on the spatio-temporal resolution standard of the multi-dimensional grid weather data set, and carrying out grid conversion on the multi-source weather data; by using Cassandra technology, establishing a distributed centerless database, and the multi-source meteorological data after grid conversion are aggregated and divided into a plurality of nodes, meanwhile, all nodes are uniformly formed into a cluster to uniformly manage the meteorological data.The meteorological data management method of that present application establishes a standard unified and easy-to-fuse multi-dimensional grid weather data set, and establishes a distributed centrallessdatabase based on Cassandra technology, thereby uniformly managing the meteorological data and meet the requirements of various meteorological operational systems in terms of reading, processing, storing and analyzing, information sharing, and the like.

The invention relates to a dual-frequency dual-polarization microwave link joint raindrop spectrum inversion and precipitation type recognition method, which comprises the steps of inversing the path average precipitation intensity based on rain attenuation information of a dual-frequency dual-polarization microwave link, firstly measuring rain attenuation intensities of different frequencies and different polarization directions by using a microwave transmitter and a receiver; then inversing path precipitation spectrum parameters by using the attenuation information; and finally calculating the path precipitation intensity by using the spectrum parameters, and performing precipitation recognition. The method provided by the invention fully exploits the microwave rain attenuation information, converts the rain attenuation information into precipitation information by the means of inversion, and has the characteristic of high temporal-spatial resolution. Meanwhile, influences of non precipitation factors are eliminated because of adoption of joint attenuation difference, and the inversion precision is improved. The method can be put into meteorological observation by acting as a new method for precipitation observation.

The invention discloses a rainfall intensity measuring method based on a satellite-ground link attenuation effect. Attenuation characteristics generated when satellite communication signals pass through a rain area are used, and the average rainfall intensity of a satellite-ground link in a propagation path in the rain area is measured; the rainfall intensity measuring method comprises the following steps that firstly, a satellite signal receiving antenna is set up on the ground, the frequency and a polarization method of the satellite signals are determined, and the signal intensity is recorded by a satellite receiver; then rain-caused signal attenuation quantity is extracted according to changes of the signal intensity in rainy weather and non-rainy weather; and finally a relationship between rain-caused attenuation and the rainfall intensity are used for inversion to obtain the average rainfall intensity in the propagation path. The rainfall intensity measuring method based on the satellite-ground link attenuation effect has the characteristics that measuring points are many, the covered range is wide, the temporal-spatial resolution is high, the erection and maintenance costs are low and the like, areas with erected satellite antennae can be used for measuring the rainfall intensity, and the deficiencies that the temporal-spatial resolution of a meteorological satellite islow, scanning of a weather radar has a blind area, rain gauge stations are sparse and the like can be overcome.

The invention discloses a probe assembly suitable for a strong-shearing unsteady flow test of an aeroengine and provides the probe assembly (1). The probe assembly (1) comprises a conjunction box (2) and a probe rod portion (3) in the shape of an elongated rod, wherein the probe rod portion (3) is configured to be inserted into the conjunction box (2). The probe rod portion (3) comprises a first section (31), a second section (32) and a third section (33) whose diameters are successively decreased in a stepwise manner, wherein the third section (33) is provided with a sensing portion (34) disposed at the end portion of the probe rod portion (3), the sensing portion (34) is in the shape of an index finger and comprises a cylindrical surface (341) and an end portion curved surface (342), the cylindrical surface (341) and the end portion curved surface (342) are each provided with a measurement hole (343), and pressure sensors (4) are respectively arranged at positions, which are disposed at the inner-side wall of the hollow-tubular-shaped tube wall of the probe rod portion (3), at the two measurement holes (343). The probe assembly has high precision and high time-space resolution.

The invention discloses a method of using high-resolution terrain and meteorology factors for multi-source precipitation fusion. The method comprises the steps of: extracting DEM grid data of a targetwatershed, and obtaining a mask file of the watershed; calculating a slope, an aspect, surface roughness and a to-shoreline distance of the target watershed by the DEM grid data of the target watershed; extracting wind speed data of the watershed according to the mask file; using the mask file to extract satellite precipitation data of the watershed; carrying out downscaling on original satelliteprecipitation to obtain satellite precipitation of Rkm; calculating deviation of satellite precipitation after downscaling and actually measured site precipitation; using a geographically weighted regression model to calculate precipitation deviation of Rkm grids; and obtaining an Rkm fusion precipitation product. According to the method, site data and the satellite precipitation product are fused, downscaling is carried out on the satellite precipitation, the high-time / space-resolution precipitation product is obtained, conversion of precipitation data from points to a surface can be realized, and data support is provided for an input of a refined hydrological model.

A magnetic resonance temperature measurement method comprises the following steps of sparsely sampling to obtain a navigation data set and an image data set, and rebuilding to obtain corresponding phase pictures; obtaining phase change values of an area to be tested through the phase pictures; and obtaining temperature change values of the area to be tested through the phase change values. In the magnetic resonance temperature measurement method and a magnetic resonance temperature measurement system, two groups of data can be collected through view, images with high space-time resolution ratio can be rebuilt, simultaneously phase information in the images is not affected in the rebuilding process, and corresponding phase pictures can be obtained. Therefore, temperature change values can be measured according to the phase pictures, real-time monitoring on temperature change in magnetic resonance is achieved, and simultaneously requirements of high time resolution ratio and high space resolution ratio for the images are met.

The present invention is directed to various methods involving nonlinear microscopy and dyes that are sensitive to fast cellular membrane potential signals and capable of generating nonlinear optical signals. The present invention includes methods of producing high spatiotemporal resolution images of electrical activity in cellular tissue, as well as methods of detecting and investigating disease within a particular cellular tissue of a living organism. The present invention further relates to methods of detecting membrane potential signal changes in a neuron or a part of a neuron, as well as in a population of cells.