81 results about "Spectral radiation" patented technology

The invention discloses a power grid facility safety-oriented forest fire spreading early warning method and system, and particularly relates to the field of cloud edge collaboration and danger prediction.The method comprises the steps of arranging a plurality of monitoring nodes in a power grid protection area, collecting monitoring data of temperature, humidity, wind speed, smoke concentration and spectral radiation, and performing early warning on forest fire spreading; matching the monitoring data of each monitoring node with the corresponding acquisition time, and constructing a multi-node environment data set according to a matching result; according to the method, a time rhythm index and multi-node difference identification mechanism is established under a cloud edge collaborative architecture, and an integrated danger prediction process of data synchronization, difference correction and trend solution is realized, so that the problems of virtual height early warning and response lag caused by misjudgment of node data asynchronization and cloud fusion in existing forest fire monitoring are solved.

The invention discloses a three-dimensional combustion multi-parameter field inversion method based on two-dimensional infrared imaging and hyperspectral light field imaging, and belongs to the technical field of flame combustion detection. The invention aims to solve the problem of low reconstruction precision caused by limited spontaneous radiation information and poor low-temperature region signal sensitivity in the existing combustion flow field temperature field reconstruction. Comprising the following steps: obtaining a flame two-dimensional infrared temperature distribution image and a flame hyperspectral light field image; a two-dimensional blackbody radiation intensity curve and a three-dimensional blackbody radiation intensity curve are obtained through calibration according to the blackbody radiation law; combining the corresponding image gray values to obtain two-dimensional infrared radiation intensity, three-dimensional visible radiation intensity and three-dimensional infrared radiation intensity; determining a temperature threshold value of the high-temperature area; constructing a multispectral radiation source term matrix equation, and reconstructing a three-dimensional temperature field; obtaining a separated flame hyperspectral light field image, and reconstructing a low-temperature region and a reconstructed temperature field; and combining with a high-temperature region reconstruction temperature field to obtain a whole temperature field. The method is used for three-dimensional combustion multi-parameter field inversion.

A method and a system have been developed to calibrate the total spectral radiance factor (TSRF) obtained from different instruments. A broad-band light source covering the whole visible range as well as the fluorescence excitation wavelengths is used to measure the TSRF, and one or more narrow-band light sources outside of the fluorescent band is used to measure fluorescent spectral radiance factor (FSRF) separately. After that, the TSRF is adjusted by the FSRF, and a calibrated TSRF can be obtained. This can be applied to characterize Optical Brightening Agents (OBAs) as well as other fluorescent materials without requiring any moving part of the instrument to do the calibration.

The present application belongs to the technical field of forest fire research, and specifically discloses a forest fire simulation monitoring method and system. The method divides multiple forest fire simulation areas, determines the area where the ignition point is located as a target area; uses a UAV to carry a Fourier infrared spectrometer to collect spectral images in the target area; compares the spectral images with the spectral bands generated by the combustion of existing combustion products to determine the types of combustion products in the target area; based on the spectral images in the target area and the corresponding combustion product types, a flame spectral radiation model is constructed; multiple forest fire danger levels and the corresponding flame spectral radiation ranges of each forest fire danger level are set in advance, and the flame spectral radiation parameters output by the flame spectral radiation model are compared with all flame spectral radiation ranges to determine the forest fire danger level of the target area. By using the flame spectral radiation model, the present application realizes accurate detection and identification of forest fires.

The invention discloses a multi-spectral radiation temperature measurement method and system for improving a quantum particle swarm, relates to the field of radiation temperature measurement and photoelectric signal processing, and solves the problems that when an existing standard PSO algorithm is applied to high-dimensional and nonlinear multi-spectral inversion, local extreme values are likely to be trapped, and the self-adaptive capacity is poor. Setting parameters, generating an initial particle position by using Tent chaotic mapping, calculating the particle fitness of an initialized population, updating initial individual optimum and global optimum, and calculating an average optimal particle position; updating the optimal particle position through a Levy flight mechanism; and repeating the steps, calculating the multispectral radiation temperature measurement target function value of the updated position, updating the initial individual optimum and the global optimum, and if an error threshold value or the maximum number of iterations is met, outputting the global optimum solution. The method is also suitable for the application field of inverting the real temperature and the spectral emissivity of the target from the multi-channel spectral radiation signals and the like.

The present application relates to the image processing method of optical remote sensing imaging detection, specifically relates to a multi-modal image fusion method and imaging system, in order to solve the existing technical image capture of target scene depends on time-sharing type imaging system or multi-device acquisition, resulting in different modal image registration difficulty, low registration accuracy, image edge details are inconsistent, the deficiency of poor fusion effect, the multi-modal image fusion method of the present application includes the original image and characteristic spectrum of target scene, multi-modal image preprocessing and multi-modal image fusion steps, based on the spectral radiation curve of target scene, spectral image and polarization image realizes multi-modal image fusion.Simultaneously, provide a kind of multi-modal image imaging system, including sub-aperture array compound eye unit, for obtaining the original image of target scene, realize the spectral image and polarization image of target scene are acquired simultaneously.

This application provides a temperature control method and system for vacuum wetting indium in an array field emitter, relating to the field of vacuum electronic device manufacturing technology. The method includes: obtaining the three-dimensional temperature field distribution of the surface of the field emitter using a deep convolutional neural network based on spectral radiation energy; calculating the transverse and longitudinal temperature gradients between the emitter pins based on this distribution data, and inputting this data into an evaluation model to dynamically assess the wetting uniformity; and generating multi-temperature zone heating power control commands based on the uniformity results using a proportional-integral-derivative controller, and adjusting the power output of each temperature zone to ensure the array temperature field meets the requirements for promoting uniform indium wetting. This application improves the control accuracy and reliability of indium wetting uniformity in complex three-dimensional field emitters under vacuum and high-temperature conditions.

The application relates to the technical field of atmospheric detection, and particularly provides a device and a method for measuring atmospheric transmittance, the device comprising a sensing and executing layer and a supporting layer, wherein the sensing and executing layer comprises a long-distance subsystem, a short-distance subsystem and a meteorological detection device; the distance between the long-distance subsystem and a measurement target is equal to a to-be-measured distance of the atmospheric transmittance; the distance between the long-distance subsystem and the measurement target is greater than the distance between the short-distance subsystem and the measurement target; the long-distance subsystem and the short-distance subsystem both comprise a multi-spectrum device; the multi-spectrum device of the long-distance subsystem collects a first multi-spectrum radiation image of the measurement target; at the same time, the multi-spectrum device of the short-distance subsystem collects a second multi-spectrum image of the measurement target; the atmospheric transmittance is calculated based on the radiation path difference of the first and second multi-spectrum radiation images; and the meteorological detection device is used for collecting meteorological data of a measurement environment, and the meteorological data is used for compensating for the environmental error of the atmospheric transmittance.

The application provides a light field multispectral temperature inversion system and method based on a physical information neural network, first constructs a deep learning network infrastructure, adopts a double-layer U-Net architecture to extract radiation and spatial distribution characteristics of data; then designs a physical information embedding module, modularizes a Planck radiation law, and guides the network to establish a physical correlation between radiation information and temperature; subsequently, light field multispectral radiation data are collected through experiments, the network is trained after data division and preprocessing are completed, and a mapping relationship between radiation characteristics and temperature characteristics is established; finally, the trained network is migrated to actual test data, and high-precision and rapid temperature inversion is realized. The application has both the advantages of deep learning in processing complex data and the constraint of a physical model, not only improves the precision and calculation efficiency of light field multispectral temperature inversion, but also enhances the applicability of the light field multispectral temperature inversion in a high-temperature complex environment.

The invention relates to a method for evaluating fuel gas jet radiation heating, which comprises the following steps of: defining a jet boundary as a semi-cylindrical outer surface and an arc surface outer surface which have the same diameter as a nozzle outlet according to a flight height, and determining the arc surface outer surface by calculating an initial expansion angle, a radius of an arc, a Mach number of the nozzle outlet and a Prandt-Myer angle; calculating the angle coefficient of each point at the bottom when the jet flow boundary is the semi-cylindrical outer surface; carrying out engine ground test run, measuring the radiation heat flow of the engine, estimating the angle coefficient of the bottom heat flow measuring point position and the jet radiation heat flow, correcting the fuel gas equivalent blackness, and calculating the radiation heat flow of each point when the jet boundary is the semi-cylindrical outer surface and the radiation heat flow of each point when the jet boundary is the arc surface outer surface; according to the method, high-temperature fuel gas jet flow field calculation and high-temperature gas spectrum radiation characteristic and transmission calculation do not need to be carried out, and engineering rapid prediction of radiation heating of the aircraft tail mounting object is realized by utilizing ground engine test run test measurement data association.

The application belongs to the field of image data processing, and particularly relates to a geometric and radiation compensation measurement method applied to farmland extraction, which comprises the following steps: obtaining remote sensing image data of a target area, pre-processing the remote sensing image, constructing a label, cutting and cropping, and dividing a training set and a test set; under the condition of fixed spatial resolution, the application establishes a unified compensation measurement mechanism between spatial resolution and spectral band number, realizes quantitative description of farmland extraction performance, solves the problem that the existing technology cannot uniformly measure the synergistic effect of spectral radiation information and spatial geometric information, and provides method support for two-dimensional quantitative analysis of farmland extraction precision; by constructing an Iso-IoU joint regression model, mathematical expression of the compensation relationship between spectral radiation information and spatial geometric information is realized, and the farmland extraction capability under different remote sensing configuration conditions can be quantitatively evaluated.

This invention discloses a rapid calculation method for the rearward infrared radiation intensity of an S-curve nozzle, belonging to the field of infrared radiation characteristic simulation of aero-engine exhaust systems. The method comprises the following steps: determining the design parameters of the S-curve nozzle and exhaust mixer components; establishing projection models of the key shielding sections of the exhaust mixer and S-curve nozzle; calculating the projected area of ​​each component after shielding by the S-curve nozzle using an image method; calculating the flow field parameter distribution and component surface temperature of the S-curve nozzle; calculating the axial length and volume of the visible region of the exhaust gas in the S-curve nozzle; calculating the spectral transmittance and spectral radiance of the exhaust gas along the nozzle outlet centerline within the visible region of the exhaust gas, as well as the spectral radiance intensity of the exhaust gas; calculating the infrared spectral radiance intensity of the wall surface; and integrating the spectral radiance to obtain the total infrared radiation intensity. This method solves the problems of existing technologies where the simulation calculation of the infrared radiation characteristics of S-curve nozzles is complex and time-consuming, and rapid calculation methods are only applicable to axisymmetric nozzles and cannot simulate the shielding structural characteristics of S-curve nozzles.

The utility model discloses an optical radiometer, relates to the technical field of spectral radiometers, and aims to solve the problems that in the prior art, most of shells of existing spectral radiometers are of integral structures, when internal components of the shells are damaged, a shell cover on the shell needs to be detached by a screwdriver, then an internal circuit board is taken out, and the cost is high. And the use and the operation are very inconvenient. Side sliding plates are slidably connected to the two sides of the shell correspondingly, sliding grooves are formed in the upper sides and the lower sides of the side sliding plates correspondingly, embedded strips are arranged on the inner side of the shell and connected with the sliding grooves in an engaged mode, a protection plate is arranged at one end of each side sliding plate, a handle is welded to the front end face of each protection plate, and a shell cover is fixedly connected to one end of the shell. A heat dissipation groove is formed in the inner side of the side sliding plate, a display screen is arranged on the front end face of the shell cover, a pressing head is slidably connected to the shell, a supporting foot is arranged at the lower end of the pressing head, a clamping leg is fixedly installed at the bottom of the supporting foot, and a clamping groove is formed in the inner side of the side sliding plate.

The utility model relates to the technical field of spectral radiometric calibration, and discloses a high-precision spectral radiometric calibration device. Comprising a machine shell and a base, the base is fixedly connected to the bottom of the machine shell, a conical reflecting cover is fixedly connected to the inner wall of the left side of the machine shell, a pipe body and a protective reflecting cylinder are fixedly connected to the side wall of the conical reflecting cover, the protective reflecting cylinder is arranged on the inner wall of the pipe body, and a plurality of optical fibers are arranged on the inner wall of the protective reflecting cylinder in a surrounding mode. The plurality of optical fibers are in close contact, and a gap is arranged between the tube body and the protective reflective cylinder. The light-emitting surface of the light source is attached to the inner wall of the conical reflecting cover, then the threaded rotating rod is rotated to rotate along the inner wall of the threaded ring so that the clamping plates can be pushed to be clamped on the side wall of the light source, the light source can be kept stable, follow-up calibration treatment is facilitated, the light source irradiates light beams to the ends of the optical fibers, and therefore the light source is more stable. The optical fiber can completely refract the light beam to the spectral radiance meter, and calibration processing can be carried out.

The utility model relates to the technical field of detection devices, in particular to a correction detection device for LED screen production. The device comprises a detection cabinet and a spectrum radiation brightness meter installed at the top of the inner wall of the detection cabinet, a cabinet door is inserted in the upper end of the detection cabinet in a sliding mode, a convenient detection assembly is arranged on the inner wall of the detection cabinet, and the convenient detection assembly comprises a disc arranged on one side of the inner wall of the detection cabinet. When the LED screens need to be detected, workers place the LED screens in the placing grooves, the stepping motor is started through the controller, the stepping motor is connected with the disc through the speed reducer and the coupler, the disc is made to rotate, a new LED screen is placed after the next placing groove is rotated out, and the steps are repeated till all the placing grooves are provided with the LED screens. And then the spectral radiation brightness meter is started for detection, after the detected LED screen is rotated out, a worker takes down and places a new LED screen for detection, and the disc continues to rotate, so that the effect of conveniently and continuously detecting the LED screen is achieved as much as possible.

The application provides a low-altitude unmanned aerial vehicle spectral radiation correction method and system for optimizing a BP neural network, and comprises the following steps: acquiring and preprocessing low-altitude multispectral image data and calibration data; generating an atmospheric transmittance lookup table, wherein the atmospheric transmittance lookup table comprises atmospheric transmittance data under different conditions; generating a low-altitude unmanned aerial vehicle radiation correction training set combined with the atmospheric transmittance; obtaining an optimal BP neural network training model for the optimization of the single input parameter of the BP neural network; and performing radiation correction by using the optimal BP neural network training model. The application solves the problem of unmanned aerial vehicle image radiation correction, and provides an efficient, reliable and feasible scheme for real-time unmanned aerial vehicle ground object identification and ground object surveying.

The invention relates to the technical field of absolute response calculation of in-orbit optical remote sensing satellites, in particular to an in-orbit satellite response calculation method based on a point light source, which comprises the following steps of: calculating entrance pupil radiance and a response value of a remote sensing camera; calculating a spectral response function and a spectral response bandwidth of the remote sensing camera; equivalent entrance pupil radiance is calculated through wavelength infinitesimal elements; performing least square fitting calculation through the equivalent entrance pupil radiation brightness and the response value to obtain an absolute radiation calibration coefficient; calculating the absolute radiation brightness under the equivalent extended light source; the atmospheric upper bound absolute radiation brightness is calculated through the atmospheric transmittance and the absolute radiation brightness under the equivalent extended light source, and the equivalent radiation brightness is calculated through the spectral response bandwidth; and the output response value of the remote sensing camera is calculated according to the equivalent spectral radiation brightness. According to the method, on-orbit satellite response calculation based on the point light source is realized by utilizing a point source target radiation transmission principle and combining a basic principle of optical remote sensing camera radiation calibration.

The invention discloses a hyperspectral target recognition method based on machine learning. The method comprises the steps of obtaining a hyperspectral image of a target and extracting to-be-recognized data; secondly, establishing a continuous differentiable mapping relation from space coordinates, observation directions and continuous wavelengths to volume density, spectral radiation intensity and material physical property parameter vectors, constructing a differentiable neural physical field model, and obtaining an initial physical property parameter field through the model; thirdly, calculating the feature similarity between the parameter field and physical property parameters in a historical database to obtain a target recognition result; and finally, performing target information management according to an identification result and notifying a user. According to the method, the physical principle is embedded into the neural network in a differentiable form, the recognition model with strong learning ability and physical interpretability is constructed, and the accuracy, generalization ability and interpretability of hyperspectral target recognition are improved.

The invention provides a temperature control method and system for vacuum infiltration of indium in an array field emitter, and relates to the technical field of vacuum electronic device manufacturing, and the method comprises the steps: obtaining the surface three-dimensional temperature field distribution through the inversion of a deep convolutional neural network based on the spectral radiation energy; calculating transverse and axial longitudinal temperature gradients among the emission needles based on the distribution data, and inputting the transverse and axial longitudinal temperature gradients into an evaluation model to dynamically evaluate the infiltration uniformity; in combination with a proportional integral differential controller, a multi-temperature-zone heating power regulation and control instruction is generated according to a uniformity result, and the array temperature field meets the requirement of promoting uniform infiltration of the indium material by regulating power output of each temperature zone. The control precision and reliability of the indium infiltration uniformity of the complex three-dimensional structure field emitter in the vacuum high-temperature environment are improved.

The invention provides a light field multispectral temperature inversion system and method based on a physical information neural network, and the method comprises the steps: firstly constructing a deep learning network infrastructure, and employing a double-layer U-Net architecture to extract the radiation and spatial distribution characteristics of data; then designing a physical information embedding module, modularizing the Planck's law of radiation, and guiding the network to establish physical association between radiation information and temperature; then, light field multispectral radiation data are collected through experiments, the network is trained after data division and preprocessing are completed, and the mapping relation between radiation characteristics and temperature characteristics is established; and finally, migrating the trained network to actual test data to realize high-precision and rapid temperature inversion. The method has the advantage of processing complex data through deep learning and the constraint of a physical model, the precision and the calculation efficiency of light field multispectral temperature inversion are improved, and the applicability of the method in a high-temperature complex environment is enhanced.

The application discloses an alkali metal visual detection system and method based on flame emission spectrum. The system comprises a flame atomic emission system, a multispectral imaging system and a processing unit. The core of the system is that the multispectral imaging system adopts a single imaging sensor and is provided with a multi-channel optical assembly. Each channel is aimed at a specific alkali metal and innovatively integrates a band-pass filter and an intensity filter with a specific transmittance. The design can project various alkali metals (such as sodium, potassium, lithium and cesium) with great differences in spectral radiation intensity into multiple spatially separated images in a single exposure. The processing unit directly establishes a nonlinear mapping relationship between image data and alkali metal concentration by using a pre-trained machine learning model, thereby realizing direct prediction of the concentration. The application solves the technical problems that the traditional method is difficult to synchronously detect strong and weak signals and needs complex calibration due to the "self-absorption effect".

This invention provides a method and system for multispectral temperature measurement based on an infrared sensor. The method includes: calculating the optical parameters of a microlens array and a filter array according to optical formulas; then fabricating the microlens array through photolithography, development, pressing, and atomic force scanning; next, constructing an infrared multispectral radiation temperature measurement system; calibrating the system using a blackbody furnace to obtain the correspondence between the camera output signal intensity and the standard temperature; decoupling the multispectral light field image based on the imaging characteristics of the light field camera; and finally, using the decoupled data to sequentially calculate the true temperature of points on the high-temperature component, obtaining the two-dimensional true temperature field of the high-temperature component. This invention overcomes the limitations of visible light multispectral temperature measurement by combining multispectral light field measurement with infrared imaging technology to achieve two-dimensional temperature field measurement, effectively overcoming the shortcomings of existing optical temperature measurement systems, such as complex structure and inability to simultaneously achieve both high measurement accuracy and wide range.

The present application relates to the field of infrared temperature measurement, more particularly to a temperature and humidity attenuation compensation method in infrared radiation temperature measurement, comprising: obtaining the temperature of a target object based on an infrared temperature measurement device, establishing a functional relationship between the spectral radiance, a given wavelength range and the target measured temperature, and calculating the spectral radiance corresponding to the target measured temperature and the ambient temperature respectively; also establishing a functional relationship between the water vapor absorption transmittance and the ambient temperature and humidity, and obtaining the water vapor absorption transmittance under different ambient temperatures and different ambient humidities; also deriving a correction formula of the target infrared radiation after attenuation by the ambient temperature and humidity based on the Kirchhoff's law of thermal radiation, and correcting the measured spectral radiance of the target object; finally inversely solving the real temperature of the target object. The present application can solve the problem of inaccurate infrared temperature measurement caused by inconsistent infrared radiation attenuation rules under different ambient temperature and humidity.

The application belongs to the field of flue gas carbon dioxide concentration determination, and particularly discloses a flue gas carbon dioxide concentration online detection method and system, which comprises the following steps: obtaining the average absorption coefficients of carbon dioxide and water vapor under different temperatures and concentrations respectively, and obtaining the relationship between the flue gas average absorption coefficient and the temperature and concentration; constructing the relationship between the theoretical spectral radiation intensity of the gas layer outward emission and the flue gas average absorption coefficient, and obtaining the relationship between the theoretical spectral radiation intensity and the gas temperature and concentration; collecting the actual spectral radiation intensity of the flue gas emission along the direction perpendicular to the airflow direction in real time through an infrared spectrum measuring device; constructing a target function with the difference between the actual spectral radiation intensity and the theoretical spectral radiation intensity; solving the target function by using an optimization algorithm, and obtaining the temperature and concentration of carbon dioxide and water vapor corresponding to the lowest target function value. The application can realize carbon dioxide concentration measurement without an additional light source emission device, and has simple structure and efficient collection.

The application discloses a kind of photovoltaic module surface dust state monitoring device based on spectral radiation force acquisition;Wherein the detection device includes: detector and controller, in detector, emission system horizontal support rod and dust side receiver support rod are fixed to the upper and lower ends of main mounting rod respectively, laser emitter is installed in the end of emission system horizontal support rod by laser emission system mounting frame, dust side power receiver is fixed to the end of dust side receiver support rod, the laser emission part of laser emitter is opposite the dust side power receiver below, the photovoltaic glass plate to be measured is located between laser emitter and dust side power receiver;Dust side power receiver is connected with signal collection and transfer module in controller.The application uses power receiver to collect the spectral radiation force after laser emitter is vertically shot into dust glass plate, instead of the generated power of photovoltaic panel for monitoring, avoid the influence of environmental factors on monitoring index.

The invention provides a multispectral camera radiance responsivity calibration device and method. The device comprises an integrating sphere, a multispectral camera, a three-dimensional adjusting mechanism, a control system and a data acquisition system. The integrating sphere is used for generating uniform spectral radiation brightness; the multispectral camera is used for image acquisition; the three-dimensional adjusting mechanism is used for moving the multispectral camera; the control system is used for controlling the spectrum output brightness of the integrating sphere and controlling the operation of the three-dimensional adjusting mechanism; and the data acquisition system is used for acquiring and storing image data of each channel of the multispectral camera. According to the invention, the multi-spectral camera pixel-by-pixel radiance responsivity calibration method which can be used under all exposure time and gain coefficient conditions is obtained from the measurement signal and exposure time of the multi-spectral camera and the emergent radiance of the integrating sphere; on the premise of ensuring the accuracy of the radiance responsivity calibration of the multispectral camera, the workload can be effectively reduced, and the calibration working efficiency is improved.

The invention discloses a flame particulate matter particle size distribution reconstruction method based on multispectral radiation. The method comprises the following steps: step 1, measuring flame narrow band radiation intensity under multiple wavelengths by adopting multispectral imaging equipment; 2, iteratively calculating flame multi-wavelength absorption coefficient space distribution based on an L-M algorithm; 3, on the basis of a single-particle absorption efficiency series expansion formula, fitting solving is conducted on polynomial coefficients in the absorption coefficient-particle size function relation; and 4, according to the polynomial coefficient in the absorption coefficient-particle size function relationship of each point in the measured flame space, calculating the particle size space distribution of the measured flame particles. By means of the scheme, non-contact measurement of particle size distribution of particles in flame can be achieved based on the multispectral radiation image, the result is reliable, and precision is high.

The invention discloses a non-contact measurement method and system for emissivity of an ultrahigh-temperature multiband material. The non-contact measurement method comprises the following steps: acquiring a transient multispectral radiance image sequence of the surface of a measured material; constructing a spatio-temporal evolution perception neural network model with an embedded micro-optical calculation layer, and training by adopting a strategy based on physical information constraint; and inputting an image sequence acquired in real time into the trained model, outputting a spectral emissivity estimation value, and calculating the surface true temperature in combination with the measured radiation brightness. According to the method, the deep learning model embedded in the physical mechanism is constructed, the irregular distortion characteristic of the emissivity in the dynamic ablation process of the material is directly learned, the technical problem that a traditional temperature measurement method fails due to model mismatch is solved, and the accuracy and robustness of true temperature and emissivity decoupling are improved.

The invention relates to a method for processing TIR images, which comprises the steps of: generating training data (MDD) from a physical model of a bolometric sensor with a plurality of spectral channels, the physical model providing a radiance measurement according to temperature and emissivity values; training a regression module (TRD) estimating temperature images (TMP) and emissivity images (EMSi) for each spectral channel (i), on the basis of the training data; training a rendering module (MRIR) configured to produce a full-resolution multispectral radiance image; training a processing chain comprising the rendering and regression modules, and a refinement module (PRTR, PSTR); acquiring a radiance image (LM[1-C]) for each spectral channel; and processing the image acquired by the trained processing chain, in order to obtain a temperature image and an emissivity image for each spectral channel.

The application provides a kind of benchmark star interstellar radiation reference value transmission full-link uncertainty evaluation method, device, equipment, storage medium and program product, belongs to space radiation measurement technical field, the method comprises: using class A evaluation method to calculate the transmission repeatability of target star instrument spectral radiance;Using class B evaluation method to calculate the spectral radiance uncertainty of time domain, space domain, spectral domain and angle domain influence;Based on transmission repeatability and the spectral radiance uncertainty of time domain, space domain, spectral domain and angle domain influence, determine the uncertainty caused by transmission process;Based on the uncertainty caused by transmission process, the uncertainty of reference value of benchmark star instrument spectral radiance and the uncertainty of measurement value of target star instrument spectral radiance, and the influence of other factors, determine the reference value transmission uncertainty of target star instrument.The application provides a kind of general interstellar radiation reference value transmission full-link uncertainty accurate evaluation scheme based on GUM.