37 results about "Cirrus cloud" patented technology

The invention discloses a method for processing a millimeter wave cloud radar signal. Under a boundary layer mode, a cirrus cloud mode and a rainfall mode, the millimeter wave cloud radar echo signal is acquired by a data acquiring module; a data preprocessing module is used for preprocessing data of the millimeter wave cloud radar echo signal and outputting power spectral density distribution data; a data processing module is used for processing the power spectral density distribution data and outputting base data; a data synthesizing module is used for synthesizing the base data under three detection modes and outputting final base data; and the millimeter wave cloud radar signal is processed. According to the method, the problem of insufficient detection power caused by low millimeter wave cloud radar emission peak value power of an all-solid or travelling wave mechanism can be effectively solved, the radar detection power is improved, and the method is especially suitable for fixing a vertical millimeter wave cloud radar.

The invention discloses a method for short wave infrared satellite remote sensing of carbon dioxide in the presence of cirrus cloud and relates to the field of atmosphere constituent detection. The method solves the problem that the concentration of carbon dioxide in the atmosphere can not be detected precisely in the presence of cirrus cloud. The method comprises the steps of 1, conducting dimensionality reduction and denoising pretreatment on hyperspectral remote sensing data; 2, building a short wave infrared hyperspectral remote sensing forward modeling radiation transfer model, wherein the radiation transfer and scattering properties of cirrus cloud short wave infrared ray are calculated and straightforward calculation of short wave infrared ray is conducted under the condition of a clear sky and in the presence of cirrus cloud; 3, building a carbon dioxide inversion model and a calculation method in the presence of cirrus cloud. By the adoption of the method, the concentration of carbon dioxide in the atmosphere can be detected precisely in the presence of cirrus cloud.

The invention provides a method for realizing 3D cloud layer simulation, which comprises the following steps of: A. making a 3D sky dynamic background varying with time; B. drawing a plurality of design sketches for a cloud sheet to form cloud form images; C. generating a single cloudlet by arranging a plurality of cloud sheets in a cubic space, carrying out the random sampling from the cloud form images by using random setting of UV coordinates according to different heights of cloud layers; D. setting the position attribution of each cloudlet after generating a plurality of the single cloudlets so as to generate a cloud layer; E. regulating the display of the 3D dynamic sky background in real time and setting real-time colors of the cloud layers according to current time; F. adding the dynamic effect for the cloud layers. By adopting the method, efficient and complicated cloud layer effects can be made by using several 2D design sketches of cirrus clouds or cumulus clouds and regulating the quantity of the cloud sheets and clouds, then more real and natural cloud layers can be simulated by regulation of a light source and addition of the dynamic effects.

The invention provides a cirrus cloud micro-physical parameter calculation method for a terahertz radar. The cirrus cloud micro-physical parameter calculation method is characterized in that by usinga discrete dipole approximation method, particle scattering characteristic data in the terahertz frequency band are calculated, by combining cirrus cloud ice crystal particle spectrum distribution parameters, a radar reflectivity factor is calculated, a corrected forward physical model is established, by minimizing cost functions, an iterative solution of a to-be-inverted parameter is obtained, the sum of a set cirrus cloud ice crystal particle spectrum parameter and a random error is used as an iteration initial value, to-be-inverted cirrus cloud micro-physical parameters are determined through iterative operation, the calculation result is compared with set cirrus cloud micro-physical parameters, so that it is judged that the method can be effectively used for calculating the cirrus cloud micro-physical parameters. The method has the advantages that the steps are simple, the calculation is reliable, moreover, a lot of statistical data is not needed, and the quite good practical application value is achieved.

The invention discloses a wavelet domain fractal infrared volume cloud detection method fusing edge information, belongs to the field of remote sensing image processing, and solves the problem that the false alarm rate is too high when a target is detected in the prior art. The method comprises the following steps: inputting and preprocessing a to-be-processed cirrus cloud image to obtain a preprocessed image; extracting a SUSAN edge feature map from the preprocessed image by using a minimum kernel value similarity region method; performing wavelet transformation on the preprocessed image to obtain a low-frequency coefficient approximation graph; obtaining a fractal dimension feature map and a multi-scale fractal area feature map of the low-frequency coefficient approximation map by usinga step-by-step triangular prism method and a carpet covering method; and calculating the consistency measure of each pixel point in the SUSAN edge feature map, the fractal dimension feature map and the multi-scale fractal area feature map as a fusion weight, carrying out pixel-level fusion on the three feature maps based on the fusion weight, obtaining a feature fusion map, and then processing thefeature fusion map to obtain a final detection result. The method is used for infrared cirrus cloud detection.

The invention discloses a multi-layer cloud and single-layer cloud type integrated classification and identification method in a remote sensing image. The method comprises: step one, carrying out cloud-included pixel element identification; step two, carrying out coarse classification and marking on single-layer and multi-layer clouds; step three, carrying out refined single-layer cloud type classification; and step four, carrying out cloud layer phase-state classification and marking. Therefore, cloud-included pixel element identification and integrated cloud layer classification and identification in a remote sensing image can be completed. According to the invention, a precise cloud layer type identification and classification result can be obtained. Distinguishing of a single-layer cloud pixel element and a multi-layer cloud pixel element can be realized; and a phase state of a multi-layer cloud pixel element and a cloud layer type of a single-layer cloud pixel element can be determined. And thus the pixel elements of the remote sensing image can be identified as thirteen kinds of pixel elements including a cloudless sky (cloud-free pixel element), a multi-layer water cloud, a multi-layer ice cloud, a cirrus cloud, a cirrostratus, a vertical extended cloud, a high cumulus cloud, an altostratus, a nimbostratus, a cumulus cloud, a stratocumulus, a stratus cloud, and a filling value, so that diversified image information can be provided for subsequent processing and application of the remote sensing image.

The invention discloses a cirrus cloud recognition method based on satellite 2.0-micrometer channel data. The cirrus cloud recognition method comprises the steps of simulating satellite observation spectral line simulation values of a 2.0-micrometer channel and an oxygen A belt channel free of scattering factors and with cirrus cloud and aerosol under different observation geometrical conditions through a forward model according to satellite data; analyzing statistical characteristics of the satellite observation spectral line simulation values of the 2.0-micrometer channel and the oxygen A belt channel, wherein the statistical characteristics include spectrum mean values and spectrum variances; reading data of the satellite oxygen A belt channel and the 2.0-micrometer channel to generate satellite actually-measured spectral line values; performing calculation on the statistical characteristics of two satellite actually-measured spectral line values, and contrasting statistical laws of the two satellite actually-measured spectral line values to recognize whether cirrus cloud exists in a satellite observation field of view: judging whether influence of scattering shadow exists according to the spectrum mean value of the satellite actually-measured spectral line value of the oxygen A belt channel and determining the cirrus cloud or the aerosol through the spectrum variance of the satellite actually-measured spectral line value of the 2.0-micrometer channel if influence of scattering shadow exists. By means of the cirrus cloud recognition method based on satellite 2.0-micrometer channel data, the problem of scattering influence of the cirrus cloud during CO2 remote sensing retrieval of a short-wave near-infrared satellite can be solved quickly and effectively.

The invention discloses an automatic cloud detection method for satellite remote sensing images. According to the technical scheme, the automatic cloud detection method is characterized by comprising the following steps of: S1, calibrating multi-spectral data as atmospheric apparent reflectivity, calibrating thermal infrared data as brightness temperature, and calibrating cirrus cloud wave bands as atmospheric apparent reflectivity TOA; S2, classifying an image by using a cloud detection tool, marking pixels of cloud and shadow as MaskedPixels, and rendering and displaying the pixels in dark gray; S3, carrying out embedding by using the resolution ratio M-Band data in two-scene NNPVIIRS to obtain an embedded picture; S4, performing cloud detection on the data to obtain a cloud mask file, and obtaining a reverse mask file by using a Bandmath tool; and S5, automatically detecting a cloud region from the multi-spectral data by using a Fmask algorithm, removing an invalid region in a data processing process, inputting the reverse mask file during classification, and eliminating interference of a non-cloud region during analysis. The automatic cloud detection method for satellite remote sensing images has the advantages of being high in detection precision and accurate in obtained result.

The invention discloses a detection method for a high-altitude cirrus cloud of a remote sensing image, and relates to the technical field of image processing. The method comprises the following stepsof S1, inputting a to-be-detected remote sensing infrared high-altitude cirrus cloud original image; S2, performing median filtering processing on the original image to obtain an original image denoising graph; S3, performing power law transform processing on the original image denoising graph to obtain a contrast enhancement graph; S4, processing the contrast enhancement graph by applying a brightness contrast algorithm to obtain a saliency graph; S5, processing the saliency graph by applying an accelerated segmentation test characteristic detection algorithm to obtain a FAST feature graph with FAST feature points; and S6, performing target frame selection according to the FAST feature points in the FAST feature graph, thereby obtaining a final frame selection detection result graph. Themethod has the advantages of high timeliness, low requirement on imaging equipment and accurate detection result.

The invention discloses a full-polarization laser radar system used for detecting shapes of particles. The laser radar system comprises a polarization light generation system, a receiving system, a polarization analysis system and a data acquisition processor. The invention also discloses a detection method of the full-polarization laser radar system used for detecting shapes of particles. The detection method is characterized in that by use of the full polarization laser radar system to carry out detection, an atmosphere back scattering Miller matrix is obtained; and then the atmosphere backscattering Miller matrix carries out detection on atmosphere particle shapes. According to the invention, by use of all-directional linear polarization laser and circular polarization laser to detectaerosol particles, fine discrimination and detection are performed on the shapes of atmosphere particles; fine measurement is performed on cloud particles in the atmosphere; and the method is used foranalyzing ice water phase states of the cloud particles and particle guidance in cirrus cloud.

The invention provides a cloud image detection method. The method comprises the following steps of: receiving a remote sensing image sequence which comprises N frames of remote sensing images by a detection device; extracting energy features of remote sensing images from the remote sensing image sequence by the detection devices so as to obtain an energy saliency map; calculating a luminance contrast of the energy saliency map by the detection device so as to obtain a luminance contrast image; extracting texture features of the luminance contrast map by the detection device so as to obtain a texture feature map; and carrying out inter-frame association on the texture feature map by the detection device by utilizing image motion information, and extracting an interested area to obtain a cloud detection result. According to the method, the requirements for sensors are reduced, and the positions and sizes of cirrus clouds can be correctly detected at the same time; and meanwhile, the adopted algorithm is simple and high in calculation efficiency and is capable of satisfying the requirement for instantaneity.

The invention discloses a satellite-borne terahertz atmospheric profile detector. The detector comprises an antenna and feed network, a receiver module, two calibration bodies and a data processing unit, wherein the antenna and feed network is used for respectively carrying out reflection and quasi-optical separation on two paths of atmospheric brightness temperature signals, respectively formingtwo paths of high-frequency reflected waves and two paths of low-frequency transmitted waves, and inputting the two paths of high-frequency reflected waves and the two paths of low-frequency transmitted waves into the receiver module; the receiver module comprises receivers of six detection frequency bands; the receivers of two detection frequency bands are combined into a temperature detection channel for detecting vertical distribution of the atmospheric temperature; the receivers of two detection frequency bands are combined into a humidity detection channel for detecting vertical distribution of the atmospheric humidity; the receivers of two detection frequency bands are used for detecting cirrus cloud, liquid water content and heavy rainfall; and the data processing unit is used for providing a normal working time sequence, controlling the reflection angle of the antenna and feed network, and carrying out acquisition quantification, storage and downloading on the data of the receiver module.

The invention relates to the technical field of remote sensing image processing, in particular to a cirrus cloud false alarm source detection method based on multiband characteristics. The cirrus cloud false alarm source detection method comprises the following steps: inputting two cirrus cloud images of different bands and preprocessing the cirrus cloud images; solving the fractal dimension of apreprocessed image by using a covering method, and performing normalization processing to obtain a normalized fractal dimension feature map; enhancing the other preprocessed image by using a saliencymethod to obtain a saliency feature map; performing weighted fusion on the normalized fractal dimension feature map and the saliency feature map; and performing adaptive threshold segmentation on thefused image to obtain a detection result. The cirrus cloud false alarm source detection method method provided by the invention avoids the dependence of a machine learning method on a large amount ofsample data and the limitation of single-waveband image detection, can achieve the quick detection of a small sample, and remarkably improves the detection capability of a cirrus cloud false alarm source.

The invention belongs to the technical field of detection of water content in cloud, particularly relates to a method for measuring the water content in cloud and aims at obtaining an accurate result of the water content in cloud including water drops and ice crystals. The method for measuring the water content in the cloud comprises the steps that cloud and mist gas containing water drops and ice crystals entering a measuring device is heated to form unsaturated mixed wet gas, and then water vapor concentration is performed. The method has the advantages that the method has very high detection accuracy, cirrus cloud completely composed of ice crystals and having very low water content can be also measured in a precision mode, and the measurement result is the water content in cloud containing liquid water and solid water.

The invention relates to an infrared imaging cirrus cloud detection method and device based on visual saliency and a computer readable storage medium. The method comprises the following steps of inputting a to-be-detected infrared image; detecting the infrared image by using a frequency modulation saliency detection method to obtain a saliency feature map; performing gamma change contrast enhancement on the saliency feature map to obtain a contrast enhancement map; performing Laplace high-lift filtering on the contrast enhancement image to obtain an edge enhancement image; carrying out regiongrowth processing on the saliency characteristic graph, and obtaining a region growth graph by taking adopted seed points as points of which the gray values are higher than 99% in the edge enhancementgraph; contour extraction being carried out on the region growth map to obtain a contour binary image; and performing target area labeling on the infrared image according to the contour binary image,and outputting a cirrus cloud detection result image. According to the method, the detection area is more accurate, algorithm complexity is low, the real-time performance is good, and the requirementon imaging equipment is not high.

The invention discloses a method and a device for measuring scattering property of a horizontally oriented particle swarm, and relates to the field of atmospheric radiation, in order to solve the problem that the scattering property of the horizontally oriented particle swarm in cirrus cloud cannot be measured at present. The method takes a xenon search light as a light source and lower cloud as a measurement object, adopts a common long-focus charge coupled device (CCD) camera as recording equipment, utilizes the xenon search light to irradiate the lower cloud towards the zenith direction, and takes horizontally oriented ice crystal particles as a horizontal mirror, wherein a virtual image of the search light appears at the position of which the height is 2h, the angle widths of the ice crystal particles can be obtained according to the relation of the camera, a search light source and a light source virtual image, observable facula is divided into two parts when the direction of the camera is close to the zenith direction, and the angle range of a mirror image reflecting part needs to be constrained in that delta theta is approximately equal to lambda/D +2F. Thus, effective sizes D and vibration parameters F of the ice crystal particles can be derived from the obtained facula radius delta theta and ray wavelength lambda. The method and the device are suitable for measurement of the scattering property of the horizontally oriented particle swarm.

The invention discloses a rapid daytime fog extracting method based on H8/AHI. The rapid daytime fog extracting method comprises the following steps: firstly, synthesizing a clear sky base map by using multi-day visible light data, and removing a clear sky earth surface by a threshold method by using reflectivity difference; removing snow and opaque ice cloud by a normalized snow index method; working out ratios of time series images before and after removal of the clear sky earth surface, the snow and the opaque ice cloud, and removing moving cloud with relatively large type change from the image by using a fixed threshold; through combination with differences in brightness and temperature of an infrared band, further removing the ice cloud, thin cirrus cloud and water cloud from the image by the threshold method; finally, synthesizing a clear sky base map by using multi-day infrared data, and removing low-level cloud from the image by the threshold method. The rapid daytime fog extracting method is a method capable of accurately, efficiently and rapidly achieving daytime fog extraction under the condition of current stationary satellite data with high temporal resolution.

The invention belongs to the field of environment simulation, and specifically relates to a cirrus cloud infrared image simulation method based on a power spectrum, for the purpose of enabling a generated cirrus cloud to be more real and be provided with a direction characteristic. The method comprises the following steps: selecting an initial power spectrum function, and describing the directivity of the power spectrum by use of a directivity factor; constructing a power spectrum model according with a cirrus cloud characteristic; constructing the frequency spectrum function of a cirrus cloud infrared simulation image; establishing the image gray scale matrix of a space domain, and preliminarily forming the cirrus cloud infrared simulation image; and performing histogram planning on the image, and correcting the cirrus cloud infrared simulation image to enable the output cirrus cloud infrared simulation image to be more realistic. Values of parameters in a power spectrum model are given so that cirrus cloud infrared simulation images in different forms are constructed. By using the method provided by the invention, a generated image is provided with a direction distribution characteristic and has similar frequency domain and spatial domain characteristics as a real cirrus cloud image.

The invention relates to a cirrus cloud detector based on an image variable field of view. The cirrus cloud detector comprises an upper industrial personal computer, a lower computer control system, amotor driving system, a temperature control system and a CCD imaging acquisition system. The upper industrial personal computer is in two-way communication connection with the lower computer controlsystem. The lower computer control system is in two-way communication connection with the temperature control system. The output end of the lower computer control system is connected with the input end of the motor driving system. The motor driving system is used for driving the CCD imaging acquisition system to rotate, and the temperature control system is used for providing a set temperature environment for the CCD imaging acquisition system. The motor driving system comprises a horizontal pitching stepping motor and an optical filter rotating disc motor. The output end of the lower computercontrol system is connected with the control input end of the horizontal pitching stepping motor and the control input end of the optical filter rotating disc motor. The horizontal pitching steppingmotor is used for driving the CCD imaging acquisition system to rotate. The optical path design is simple, and the detection time is short. Meanwhile, the detection precision of the cirrus cloud is improved.

The invention discloses a first-order scattering calculation method suitable for long-distance laser to pass through spherical cirrus cloud. The method comprises the following steps: in atmosphere with a proper distance from a target, laser is emitted, the upper surface and the lower surface of cirrus cloud in the model are set to be spherical planes, extinction coefficients of any point in the atmosphere are set, the direct component of the laser passing through the atmosphere is calculated, and in an ideal state, namely, factors of atmospheric molecules and aerosol are not considered, an n-medium scattering model of a successive scattering method is utilized to obtain first-order scattering power; when the first-order scattering effect of atmospheric molecules and aerosol factors on laser is increased, the first-order scattering power considering the atmospheric molecules and aerosol is obtained through calculation, and then an expression of first-order scattering of atmospheric attenuation is derived. According to the calculation method, the plane of the cirrus cloud is changed into the spherical plane from the original plane, and the factors of atmospheric molecules and aerosolare considered in the original ideal state, so that the calculation result is more accurate, and the calculation method has a very good practical value.

The invention discloses an infrared imaging volume cloud detection method based on fractal dictionary learning in technical field of infrared image processing which aims to solve the problem that a large amount of false alarm sources with very high radiation energy exist in an infrared imaging wave band, and the false alarm sources can interfere the detection of a target. The method for solving the false alarm source interference target detection problem comprises the following specific steps: 1, inputting a to-be-detected volume cloud infrared image, and carrying out filtering and denoising on the to-be-detected volume cloud infrared image to obtain a preprocessed volume cloud image; 2, acquiring a Hurst index value of the preprocessed volume cloud image; 3, solving a random fractal imagebased on the Hurst index value obtained in the step 2 and a rhombus-square subdivision method, and constructing an over-complete dictionary D based on the random fractal image; 4, performing sparse coding and dictionary updating on the over-complete dictionary D by using a K-SVD algorithm to obtain a sparse representation image; and 5, performing morphological filtering and image segmentation processing on the sparse representation image to obtain a detection result image. The method is easy to implement, high in detection effect accuracy and short in algorithm calculation time.