Infrared Cloud Image Texture Enhancement Display Method, Device and Equipment

Abstract

The present invention provides an infrared cloud image texture enhancement display method, device and equipment, which relates to the technical field of meteorology, and includes: obtaining infrared cloud image data corresponding to a target area, and determining the brightness temperature data corresponding to the target area; using the brightness temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located; according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determining the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data; generating a shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, so as to perform texture enhancement display on the infrared cloud image data. The present invention can significantly enhance the texture of the infrared cloud image data, thereby making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

Description

Technical Field

[0001] The present invention relates to the field of meteorological technologies, and in particular, to a method, device, and equipment for enhancing the display of infrared cloud image textures. Background Art

[0002] The functions and performances of the new generation of high-resolution geostationary satellites have achieved leapfrog development, and the radiation imaging channels of the satellites cover bands such as visible light, short-wave infrared, mid-wave infrared, and long-wave infrared. Among them, the long-wave infrared channel provides all-weather high spatio-temporal resolution observation capabilities relative to visible light data, providing continuous monitoring data and high-resolution cloud images for typhoons and severe convective weather, etc.

[0003] Although the satellite long-wave infrared cloud image is not affected by sunlight reflection and can relatively truly reflect the temperature and height of the cloud top, due to the fact that weather processes such as convection and typhoons are often accompanied by changes in the cloud top brightness temperature gradient and the divergence and curl of the cloud image optical flow vector, it contains less texture information helpful for analyzing the cloud top structure compared with visible light, and lacks relatively intuitive information for monitoring, identifying, and analyzing weather phenomena such as rapidly developing convection and typhoons. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method, device, and equipment for enhancing the display of infrared cloud image textures, which can significantly enhance the textures of infrared cloud image data, thereby making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection, and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

[0005] In a first aspect, an embodiment of the present invention provides a method for enhancing the display of infrared cloud image textures, including:

[0006] Obtain infrared cloud image data corresponding to a target area, and determine the brightness temperature data corresponding to the target area, where the brightness temperature data includes the cloud top brightness temperature and the surface brightness temperature;

[0007] Use the brightness temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located;

[0008] According to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data;

[0009] Generate a shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to enhance the texture display of the infrared cloud image data to obtain target infrared cloud image data.

[0010] In one embodiment, using the brightness temperature data and the surface elevation data corresponding to the target area, determining the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located, includes:

[0011] Determining the cloud top height based on the brightness temperature data to determine the pixel vertices belonging to the clear-sky sea-land surface and the pixel vertices belonging to the cloud body in the infrared cloud image data;

[0012] Respectively determining the temperature gradient corresponding to the pixel vertices belonging to the clear-sky sea-land surface; and the temperature gradient corresponding to the pixel vertices belonging to the cloud body;

[0013] According to the temperature gradient corresponding to each pixel vertex and the surface elevation data, determining the initial normal vector of the surface where each pixel vertex is located;

[0014] For each pixel vertex, determining a plurality of neighboring pixel vertices corresponding to the pixel vertex from the infrared cloud image data, and taking the mean value of the initial normal vectors corresponding to the neighboring pixel vertices as the first normal vector corresponding to the pixel vertex.

[0015] In one embodiment, according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determining the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data, includes:

[0016] For each pixel vertex, based on the position information of the artificial light source and the position information of the pixel vertex in the infrared cloud image data, determining the light direction vector of the artificial light source relative to the pixel vertex;

[0017] According to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex, determining the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data.

[0018] In one embodiment, according to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex, determining the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data, includes:

[0019] For each pixel vertex, performing an inner product operation on the first normal vector of the surface where the pixel vertex is located and the light direction vector of the artificial light source relative to the pixel vertex to obtain a second normal vector;

[0020] Wherein, the second normal vector is used to characterize the light reflection intensity of the artificial light source relative to the pixel vertex.

[0021] In one embodiment, generating the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, includes:

[0022] For each pixel vertex, perform a dot product operation on the first normal vector and the second normal vector corresponding to the pixel vertex to obtain the dot product result corresponding to the pixel vertex;

[0023] Normalize the dot product result corresponding to each pixel vertex;

[0024] Based on the normalized dot product result, generate the shadow texture corresponding to the target area.

[0025] In one implementation, use the shadow texture to perform texture enhancement display on the infrared cloud map data to obtain the target infrared cloud map data, including:

[0026] Perform color conversion on the infrared cloud map data through a specified enhancement rendering strategy;

[0027] Use the shadow texture to perform texture enhancement display on the color-converted infrared cloud map data to obtain the target infrared cloud map data.

[0028] In one implementation, use the shadow texture to perform texture enhancement display on the color-converted infrared cloud map data to obtain the target infrared cloud map data, including:

[0029] Based on a pre-determined smoothing factor, perform smoothing processing on the shadow texture and the color-converted infrared cloud map data to obtain the infrared cloud map data with the shadow texture;

[0030] Perform mean filtering processing on the infrared cloud map data with the shadow texture to obtain the target infrared cloud map data.

[0031] In a second aspect, an embodiment of the present invention further provides an infrared cloud map texture enhancement display device, including:

[0032] A brightness temperature determination module, configured to obtain the infrared cloud map data corresponding to the target area and determine the brightness temperature data corresponding to the target area, where the brightness temperature data includes cloud top brightness temperature data and surface brightness temperature data;

[0033] A normal vector determination module, configured to use the brightness temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud map data is located;

[0034] A light reflection intensity determination module, configured to determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source;

[0035] A texture enhancement module, configured to generate the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to perform texture enhancement display on the infrared cloud map data to obtain the target infrared cloud map data.

[0036] In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor and a memory. The memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the method according to any one of the first aspect.

[0037] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the method according to any one of the first aspect.

[0038] The infrared cloud image texture enhancement display method, device and equipment provided by the embodiments of the present invention first obtain infrared cloud image data corresponding to a target area, and determine the brightness temperature data corresponding to the target area. The brightness temperature data includes cloud top brightness temperature and surface brightness temperature; then, using the brightness temperature data and the surface elevation data corresponding to the target area, determine the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located; further, according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data; finally, generate a shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to perform texture enhancement display on the infrared cloud image data to obtain target infrared cloud image data. The above method combines the cloud top brightness temperature to simulate a shadow texture similar to a visible light image, and then performs texture enhancement display on the infrared cloud image data by using the shadow texture through enhanced rendering. Therefore, the texture of the infrared cloud image data can be significantly enhanced, making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection, and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

[0039] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention are realized and obtained by the structures specifically pointed out in the specification, claims, and drawings.

[0040] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. Description of the Drawings

[0041] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 Schematic flowchart of an infrared cloud image texture enhancement display method provided by an embodiment of the present invention;

[0043] Figure 2 Overall flowchart of an infrared cloud image texture enhancement display method provided by an embodiment of the present invention;

[0044] Figure 3 Schematic structural diagram of an infrared cloud image texture enhancement display device provided by an embodiment of the present invention;

[0045] Figure 4 Schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0046] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] Currently, infrared cloud images lack relatively intuitive information for monitoring, identifying, and analyzing rapidly developing convective and typhoon weather phenomena. Based on this, the embodiments of the present invention provide an infrared cloud image texture enhancement display method, device, and equipment, which can significantly enhance the texture of infrared cloud image data, making the observation of rapidly developing convective, mesoscale convective, and typhoon and other severe weather phenomena more interpretable, and providing a more effective basis for their identification and early warning.

[0048] For ease of understanding of this embodiment, first, a detailed introduction to an infrared cloud image texture enhancement display method disclosed in the embodiments of the present invention is provided. Refer to Figure 1 The schematic flowchart of an infrared cloud image texture enhancement display method shown below. This method mainly includes the following steps S102 to step S108:

[0049] Step S102, obtain the infrared cloud image data corresponding to the target area and determine the brightness temperature data corresponding to the target area.

[0050] Among them, an infrared cloud image is a temperature distribution map that a satellite measures the infrared radiation emitted by the earth's surface and cloud surface at 10.5 - 12.5 micrometers and represents this radiation in the form of an image; the brightness temperature data includes cloud top brightness temperature and surface brightness temperature. In one example, obtain the infrared cloud image data of the target area CIA remembered by the satellite, and determine the cloud top brightness temperature and surface brightness temperature using the radiation characterized by the infrared cloud image data.

[0051] Step S104: Using the brightness temperature data and the surface elevation data corresponding to the target area, determine the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located.

[0052] In one example, the cloud top brightness temperature and the surface brightness temperature can be used to identify the pixel vertices belonging to the cloud body and the pixel vertices belonging to the clear-sky sea and land surface in the infrared cloud image data. Then, the temperature gradients can be calculated respectively, and combined with the surface elevation data to determine the first normal vector of the surface where each pixel vertex is located.

[0053] Step S106: According to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data.

[0054] In one example, the artificial light source can be set according to the observation characteristics of the satellite and the key area of concern. According to the position information of the artificial light source, determine the light direction vector of the artificial light source relative to each pixel vertex. Perform an inner product calculation on the first normal vector and the light direction vector corresponding to each pixel vertex to obtain the second normal vector, and this second normal vector can represent the light reflection intensity of the artificial light source relative to the pixel vertex.

[0055] Step S108: Generate the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to perform texture enhancement display on the infrared cloud image data to obtain the target infrared cloud image data.

[0056] In one example, the shadow texture can be generated based on the dot product result of the first normal vector and the second normal vector corresponding to each pixel vertex; then select a reasonable enhancement rendering strategy to perform color conversion on the infrared cloud image data; finally, overlay the shadow texture with the color-converted infrared cloud image data to obtain the target infrared cloud image data.

[0057] The infrared cloud image texture enhancement display method provided by the embodiments of the present invention simulates the shadow texture similar to the visible light image by combining the cloud top brightness temperature, and then uses the shadow texture to perform texture enhancement display on the infrared cloud image data through enhanced rendering. Therefore, the texture of the infrared cloud image data can be significantly enhanced, making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection, and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

[0058] For ease of understanding, the embodiments of the present invention provide an overall process schematic diagram of an infrared cloud image texture enhancement display method as shown in Figure 2 including processes such as data input, pixel normal vector calculation, light source position setting, light source normal vector calculation, texture calculation, color mapping, texture overlay, and product output.

[0059] Based on this, an embodiment of the present invention provides a specific implementation manner of an infrared cloud image texture enhancement display method:

[0060] Step 1: Calculate the cloud top height based on the infrared cloud image data T, including the following steps 1.1 to 1.2:

[0061] Step 1.1: It is necessary to calibrate the radiation received by the satellite to ensure that the measured radiation intensity is proportional to the true radiation intensity emitted by objects on the ground or in the atmosphere. Generally, a known radiation source (such as a blackbody radiation source) is used to calibrate the satellite sensor. Through the calibrated data, the surface brightness temperature and the cloud top brightness temperature are calculated. The brightness temperature refers to the brightness temperature radiated by an object in the infrared band and is usually expressed in temperature units (such as degrees Celsius or Kelvin). During the calibration and processing, quality control and verification are required to ensure the accuracy and reliability of the data. This may involve comparing with data from ground observation stations, processing the same data using different algorithms, and performing statistical analysis and other methods.

[0062] Step 1.2: Determine the cloud top height. The cloud top height is usually related to the temperature of the cloud top. Clouds will show a lower brightness temperature than the surrounding air in the infrared band because the radiation reflected and emitted by the clouds makes their temperature lower than the surrounding environment. By comparing the brightness temperature of the cloud layer with that of the surrounding environment, the cloud top height can be inferred. Usually, there is a certain correspondence between the cloud top height and the cloud top temperature. The temperature profile data of the forecast model can be combined to assist in calculating the cloud top height. However, in the embodiment of the present invention, only the cloud top texture needs to be obtained, and the temperature difference between adjacent pixel vertices is small, and a particularly accurate cloud top height is not required. Therefore, the existence of atmospheric stability can be ignored, that is, it is assumed that the cloud top height is inversely proportional to the cloud top brightness temperature, that is:

[0063] CTH = 50 - T / 6;

[0064] Where, CTH is the cloud top height and T is the cloud top brightness temperature.

[0065] Step 2: Calculate the normal vector of each pixel surface based on the infrared cloud image data T and the surface elevation, and calculate the first normal vector A of the pixel vertex based on the normal vector of the surface. It includes the following steps 2.1 to 2.4:

[0066] Step 2.1: Based on the cloud top height calculated in Step 1, determine the pixel vertices belonging to the clear-sky sea-land surface and the pixel vertices belonging to the cloud body in the infrared cloud image data.

[0067] In one example, since the infrared cloud image data T may include the pixel vertices of the clear-sky land-sea surface and the pixel vertices of the cloud body, generally the cloud top brightness temperature is lower than the land surface brightness temperature. Using the reciprocal of the brightness temperature as the texture can distinguish the land surface from the cloud top. However, since the elevation of the land-sea surface is generally higher than that of the sea surface, but the temperature is higher than that of the sea surface, using only the brightness temperature for the texture near the coastline will cause texture illusions. Therefore, it is more reasonable to perform cloud monitoring before calculating the texture and appropriately use the surface elevation for the texture calculation of the clear-sky land-sea surface. The algorithms for cloud monitoring are generally complex and may also involve other auxiliary data sources. Here, to ensure the robustness of the algorithm, a simple threshold segmentation algorithm is adopted to separate the pixel vertices belonging to the clear-sky land-sea surface and the pixel vertices belonging to the cloud body in the infrared cloud image data based on the cloud top elevation and the surface elevation. Among them, the surface elevation of each pixel vertex is obtained from data sources such as topographic maps or digital elevation models (DEMs).

[0068] Step 2.2: Determine the temperature gradients corresponding to the pixel vertices belonging to the clear-sky land-sea surface and the temperature gradients corresponding to the pixel vertices belonging to the cloud body, respectively.

[0069] In one example, for the pixel vertices belonging to the cloud body, the infrared brightness temperature data can be used to calculate the temperature gradient. Specifically, the direction and amplitude of the temperature change can be estimated by comparing the temperature values of adjacent pixels.

[0070] In one example, for the pixel vertices belonging to the clear-sky land-sea surface, the temperature gradient can be calculated by combining the surface elevation data.

[0071] Step 2.3: Determine the initial normal vector of the surface where each pixel vertex is located according to the temperature gradient corresponding to each pixel vertex and the surface elevation data.

[0072] Step 2.4: For each pixel vertex, determine a plurality of adjacent pixel vertices corresponding to the pixel vertex from the infrared cloud image data, and use the mean value of the initial normal vectors corresponding to the adjacent pixel vertices as the first normal vector corresponding to the pixel vertex.

[0073] In one example, for each pixel vertex, the first normal vector A of the pixel vertex can be estimated according to the initial normal vectors of its surrounding pixel vertices. For example, in the embodiments of the present invention, the average value of the initial normal vectors of the neighbor pixel vertices of the pixel vertex is used to estimate the first normal vector A of the pixel vertex.

[0074] Step 3: To simulate the lighting conditions during satellite observation for better understanding and analysis of satellite images, the position of the artificial light source can be set according to the observation characteristics of the satellite and the key areas of concern. It includes the following steps 3.1 to 3.4:

[0075] Step 3.1, Understand the satellite observation characteristics: First, it is necessary to understand the satellite observation parameters, including the satellite sub-satellite point, observation resolution, etc. These parameters will affect the selection of the light source position.

[0076] Step 3.2, Determine the key areas of concern: Determine the areas or targets that need to be concerned about, which helps to determine the position of the light source. For example, if the concern is the urban area, the light source may be set directly above or slightly to the west of the satellite observation to simulate the noon lighting conditions; if the concern is the mountainous area or canyon, the light source may be set slightly to the east to simulate the morning or evening lighting conditions.

[0077] Step 3.3, Simulate the lighting conditions: Based on the above considerations, set the position of the light source to simulate the lighting conditions during satellite observation. Virtual light sources or ambient light can be used to simulate the direction and intensity of sunlight.

[0078] Step 3.4, Adjust the parameters and observe the results: After setting the position of the light source, observe the simulated satellite image, adjust the parameters and conduct experiments until satisfactory results are obtained. Parameters such as the color, intensity, and direction of the light source can be considered to further optimize the simulation effect.

[0079] Step 4, Calculate the second normal vector B of the artificial light source relative to each pixel vertex in the infrared cloud image data, including the following steps 4.1 to 4.2:

[0080] Step 4.1, For each pixel vertex, based on the position information of the artificial light source and the position information of this pixel vertex in the infrared cloud image data, determine the light direction vector of the artificial light source relative to this pixel vertex. Specifically:

[0081] 1) Obtain the infrared cloud image data and the first normal vector A of the pixel vertex: First, obtain the infrared cloud image data, including the position and attribute information of each pixel vertex, and the first normal vector A of the pixel vertex.

[0082] 2) Determine the light source position: Determine the position of the artificial light source in the cloud image coordinate system, which can usually be represented by coordinates in three-dimensional space.

[0083] 3) Calculate the light direction vector: For each pixel vertex, connect the light source position and this pixel vertex position to obtain a ray. Calculate the direction vector of this ray, that is, the vector pointing from the light source to the pixel vertex.

[0084] Step 4.2, According to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data.

[0085] In one example, for each pixel vertex, an inner product operation can be performed on the first normal vector of the surface where the pixel vertex is located and the light direction vector of the artificial light source relative to the pixel vertex to obtain a second normal vector, which is used to characterize the light reflection intensity of the artificial light source relative to the pixel vertex.

[0086] Specifically, for each pixel vertex, given its first normal vector A, the second normal vector B can be obtained by performing an inner product operation on the light direction vector and the first normal vector A. The result of the inner product operation is a scalar, and multiplying it by the first normal vector A can obtain the second normal vector B.

[0087] For each pixel vertex in the infrared cloud map data, steps 4.1 to 4.2 are repeated to calculate the corresponding second normal vector B. The second normal vector B can be used for subsequent analysis such as lighting simulation and shadow calculation.

[0088] Step 5, obtain the shadow texture C of the infrared cloud map data by calculating the dot product of the first normal vector A and the second normal vector B. The result of the dot product represents the angle between the light and the surface normal vector, which can be used to simulate the effect of lighting on the surface. It includes the following steps 5.1 to 5.3:

[0089] Step 5.1, for each pixel vertex, perform a dot product operation on the first normal vector and the second normal vector corresponding to the pixel vertex to obtain the dot product result corresponding to the pixel vertex.

[0090] In one example, for each pixel vertex, perform a dot product operation on the first normal vector A and the second normal vector B. The dot product operation can be performed by multiplying the respective components of the vectors and then summing to obtain a scalar value. The result of the dot product represents the angle between the light and the surface normal vector, and its value range is usually between [-1, 1].

[0091] Step 5.2, perform a normalization process on the dot product result corresponding to each pixel vertex.

[0092] In one example, perform a normalization process on the dot product result, mapping it to between [0, 1] to be used as the color value of the shadow texture.

[0093] Step 5.3, generate the shadow texture corresponding to the target area based on the normalized dot product result.

[0094] In one example, use the normalized dot product result as the color value of the shadow texture to generate the shadow texture C of the infrared cloud map data. Specifically, the dot product result can be used as the grayscale value, or color mapping can be performed according to specific requirements to present different visual effects.

[0095] Step 6: Select a reasonable enhancement rendering strategy to perform color conversion on the infrared cloud image data, enhance the display of the infrared cloud image data through color, and also try to retain the brightness temperature information of the infrared cloud image data as much as possible through color after texture overlay, preparing for subsequent texture overlay. It includes the following steps 6.1 to 6.3:

[0096] Step 6.1: Enhancement scheme selection: The embodiment of the present invention adopts the color texture enhancement scheme often used by the typhoon warning center. This scheme has rich colors and color jumps are set at the qualitative change stage of convection, which can retain the brightness temperature information of the cloud image to the greatest extent after subsequent texture overlay. Of course, the rendering scheme can also be arbitrarily changed according to different weather phenomena.

[0097] Step 6.2: Color level setting: The color level setting should be determined according to the distribution of the infrared brightness temperature data and the observation requirements. Lower brightness temperatures can be mapped to warm colors, and higher brightness temperatures can be mapped to cold colors to highlight the temperature difference. Adjusting the color level range can control the color saturation and contrast, thereby affecting the display effect.

[0098] Step 6.3: Color mapping: Select a suitable color mapping scheme to represent data in different brightness temperature ranges. For example, higher brightness temperatures can be mapped to blue or purple, and lower brightness temperatures can be mapped to yellow or orange. The choice of color mapping should consider visual distinguishability and the overall effect after texture overlay.

[0099] Step 7: Use the shadow texture to perform texture enhancement display on the color-converted infrared cloud image data to obtain the target infrared cloud image data. Specifically, based on the infrared cloud image data T and the shadow texture C, the infrared cloud image data Tc with shadow texture can be obtained by combining the smoothing factor. It includes the following steps 7.1 to 7.3:

[0100] Step 7.1: Define the smoothing factor: Define a smoothing factor to represent the influence degree of the shadow texture C on the infrared cloud image data T. The smoothing factor is usually a value between 0 and 1, indicating the importance of the texture to the infrared brightness temperature. 0 means not considering the texture, and 1 means fully considering the texture.

[0101] Step 7.2: Based on the pre-determined smoothing factor, perform smoothing processing on the shadow texture and the color-converted infrared cloud image data to obtain the infrared cloud image data with shadow texture.

[0102] In one example, for each pixel vertex, the following formula is used to calculate the infrared cloud image data Tc with texture:

[0103] Tc = (1 - smoothing factor) × T + smoothing factor × C

[0104] Wherein, T is the infrared cloud image data, C is the shadow texture, and Tc is the infrared cloud image data with texture.

[0105] Step 7.3: Perform mean filtering on the infrared cloud image data with shadow texture to obtain the target infrared cloud image data.

[0106] In one example, the obtained infrared cloud image data Tc with texture is smoothed using a mean filter to eliminate noise and mutations.

[0107] In summary, the embodiment of the present invention proposes a new method to calculate the texture of an infrared cloud image through a given light source. By combining the cloud top brightness temperature to simulate the texture similar to a visible light image, and then processing through an enhanced rendering technique, not only can the infrared brightness temperature information be maximally retained, but also a texture similar to that of a visible light cloud image is provided for the infrared cloud image data. This method can provide a more intuitive geometric display, making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection, and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

[0108] Based on the foregoing embodiments, the embodiment of the present invention provides an infrared cloud image texture enhancement display device. Refer to Figure 3 the structural schematic diagram of an infrared cloud image texture enhancement display device shown. The device mainly includes the following parts:

[0109] The brightness temperature determination module 302 is used to obtain the infrared cloud image data corresponding to the target area and determine the brightness temperature data corresponding to the target area. The brightness temperature data includes cloud top brightness temperature data and surface brightness temperature data;

[0110] The normal vector determination module 304 is used to determine the first normal vector of the surface where each pixel vertex in the infrared cloud image data is located by using the brightness temperature data and the surface elevation data corresponding to the target area;

[0111] The light reflection intensity determination module 306 is used to determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source;

[0112] The texture enhancement module 308 is used to generate the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and perform texture enhancement display on the infrared cloud image data by using the shadow texture to obtain the target infrared cloud image data.

[0113] The infrared cloud image texture enhancement display device provided by the embodiment of the present invention simulates the shadow texture similar to the visible light image by combining the cloud top brightness temperature, and then enhances and renders the infrared cloud image data with the shadow texture for texture enhancement display. Therefore, the texture of the infrared cloud image data can be significantly enhanced, making the observation of strong weather phenomena such as rapidly developing convection, mesoscale convection, and typhoons more interpretable, and providing a more effective basis for their identification and early warning.

[0114] In one implementation, the normal vector determination module 304 is specifically configured to:

[0115] Determine the cloud top height based on the brightness temperature data to determine the pixel vertices belonging to the clear sky sea-land surface and the pixel vertices belonging to the cloud body in the infrared cloud image data;

[0116] Respectively determine the temperature gradient corresponding to the pixel vertices belonging to the clear sky sea-land surface; and the temperature gradient corresponding to the pixel vertices belonging to the cloud body;

[0117] Determine the initial normal vector of the surface where each pixel vertex is located according to the temperature gradient corresponding to each pixel vertex and the surface elevation data;

[0118] For each pixel vertex, determine a plurality of neighboring pixel vertices corresponding to the pixel vertex from the infrared cloud image data, and use the average value of the initial normal vectors corresponding to the neighboring pixel vertices as the first normal vector corresponding to the pixel vertex.

[0119] In one implementation, the light reflection intensity determination module 306 is specifically configured to:

[0120] For each pixel vertex, determine the light direction vector of the artificial light source relative to the pixel vertex based on the position information of the artificial light source and the position information of the pixel vertex in the infrared cloud image data;

[0121] Determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud image data according to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex.

[0122] In one implementation, the light reflection intensity determination module 306 is specifically configured to:

[0123] For each pixel vertex, perform an inner product operation on the first normal vector of the surface where the pixel vertex is located and the light direction vector of the artificial light source relative to the pixel vertex to obtain a second normal vector;

[0124] Wherein, the second normal vector is used to represent the light reflection intensity of the artificial light source relative to the pixel vertex.

[0125] In one implementation, the texture enhancement module 308 is specifically configured to:

[0126] For each pixel vertex, perform a dot product operation on the first normal vector and the second normal vector corresponding to the pixel vertex to obtain the dot product result corresponding to the pixel vertex;

[0127] Normalize the dot product result corresponding to each pixel vertex;

[0128] Based on the normalized dot product result, generate the shadow texture corresponding to the target area.

[0129] In one implementation, the texture enhancement module 308 is specifically configured to:

[0130] Perform color conversion on the infrared cloud map data through a specified enhancement rendering strategy;

[0131] Use the shadow texture to perform texture enhancement display on the color-converted infrared cloud map data to obtain the target infrared cloud map data.

[0132] In one implementation, the texture enhancement module 308 is specifically configured to:

[0133] Based on a predetermined smoothing factor, perform smoothing processing on the shadow texture and the color-converted infrared cloud map data to obtain the infrared cloud map data with the shadow texture;

[0134] Perform mean filtering on the infrared cloud map data with the shadow texture to obtain the target infrared cloud map data.

[0135] The device provided by the embodiments of the present invention has the same implementation principle and the same technical effects as those of the foregoing method embodiments. For the sake of brief description, for the parts not mentioned in the device embodiments, reference may be made to the corresponding content in the foregoing method embodiments.

[0136] The embodiments of the present invention provide an electronic device. Specifically, the electronic device includes a processor and a storage device; a computer program is stored on the storage device, and the computer program executes the method according to any one of the foregoing implementations when being run by the processor.

[0137] Figure 4 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. The electronic device 100 includes: a processor 40, a memory 41, a bus 42, and a communication interface 43. The processor 40, the communication interface 43, and the memory 41 are connected through the bus 42; the processor 40 is configured to execute an executable module stored in the memory 41, such as a computer program.

[0138] Among them, the memory 41 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between this system network element and at least one other network element is realized through at least one communication interface 43 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0139] The bus 42 can be an ISA bus, a PCI bus, an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of easy representation, Figure 4 only a bidirectional arrow is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0140] Among them, the memory 41 is used to store programs. After receiving an execution instruction, the processor 40 executes the program. The methods executed by the device defined by the flow process disclosed in any embodiment of the foregoing embodiments of the present invention can be applied to the processor 40 or implemented by the processor 40.

[0141] The processor 40 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 40 or the instructions in the form of software. The above-mentioned processor 40 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 41, and the processor 40 reads the information in the memory 41 and combines its hardware to complete the steps of the above method.

[0142] The computer program product of the readable storage medium provided by the embodiments of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For the specific implementation, reference can be made to the foregoing method embodiments and will not be elaborated here.

[0143] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0144] Finally, it should be noted that the above-mentioned embodiments are only specific implementation manners of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting it. The protection scope of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed by the present invention can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An infrared cloud image texture enhancement display method, characterized in that, Including: Obtain the infrared cloud map data corresponding to the target area, and determine the brightness temperature data corresponding to the target area, where the brightness temperature data includes cloud top brightness temperature and surface brightness temperature; Use the brightness temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud map data is located; According to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data; Generate the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to perform texture enhancement display on the infrared cloud map data to obtain the target infrared cloud map data; Using the brightness temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud map data is located, including: Determine the cloud top height based on the brightness temperature data to determine the pixel vertices belonging to the clear sky sea and land surface and the pixel vertices belonging to the cloud body in the infrared cloud map data; Respectively determine the temperature gradient corresponding to the pixel vertices belonging to the clear sky sea and land surface; and the temperature gradient corresponding to the pixel vertices belonging to the cloud body; According to the temperature gradient corresponding to each pixel vertex and the surface elevation data, determine the initial normal vector of the surface where each pixel vertex is located; For each pixel vertex, determine multiple neighboring pixel vertices corresponding to the pixel vertex from the infrared cloud map data, and use the average value of the initial normal vectors corresponding to the neighboring pixel vertices as the first normal vector corresponding to the pixel vertex.

2. The infrared cloud image texture enhancement display method according to claim 1, wherein According to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data, including: For each pixel vertex, based on the position information of the artificial light source and the position information of the pixel vertex in the infrared cloud map data, determine the light direction vector of the artificial light source relative to the pixel vertex; According to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data.

3. The infrared cloud image texture enhancement display method according to claim 2, wherein, According to the first normal vector of the surface where each pixel vertex is located and the light direction vector of the artificial light source relative to each pixel vertex, determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data, including: For each pixel vertex, perform an inner product operation on the first normal vector of the surface where the pixel vertex is located and the light direction vector of the artificial light source relative to the pixel vertex to obtain a second normal vector; Wherein, the second normal vector is used to represent the light reflection intensity of the artificial light source relative to the pixel vertex.

4. The infrared cloud image texture enhancement display method according to claim 3, wherein, Generating the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, including: For each of the pixel vertices, perform a dot product operation on the corresponding first normal vector and the second normal vector of the pixel vertex to obtain the dot product result corresponding to the pixel vertex; Perform a normalization process on the dot product result corresponding to each of the pixel vertices; Generate the shadow texture corresponding to the target area based on the dot product result after the normalization process; 5. The infrared cloud image texture enhancement display method according to claim 1, characterized in that Use the shadow texture to perform texture enhancement display on the infrared cloud map data to obtain target infrared cloud map data, including: Perform color conversion on the infrared cloud map data through a specified enhancement rendering strategy; Use the shadow texture to perform texture enhancement display on the infrared cloud map data after color conversion to obtain target infrared cloud map data.

6. The infrared cloud image texture enhancement display method according to claim 5, wherein Use the shadow texture to perform texture enhancement display on the infrared cloud map data after color conversion to obtain target infrared cloud map data, including: Based on a pre-determined smoothing factor, perform smoothing processing on the shadow texture and the infrared cloud map data after color conversion to obtain the infrared cloud map data with the shadow texture; Perform mean filtering processing on the infrared cloud map data with the shadow texture to obtain target infrared cloud map data.

7. An infrared cloud image texture enhancement display device, characterized in that Including: A bright temperature determination module, configured to obtain infrared cloud map data corresponding to a target area and determine the bright temperature data corresponding to the target area, where the bright temperature data includes cloud top bright temperature data and surface bright temperature data; A normal vector determination module, configured to use the bright temperature data and the surface elevation data corresponding to the target area to determine the first normal vector of the surface where each pixel vertex in the infrared cloud map data is located; A light reflection intensity determination module, configured to determine the light reflection intensity of the artificial light source relative to each pixel vertex in the infrared cloud map data according to the first normal vector of the surface where each pixel vertex is located and the position information of the artificial light source; A texture enhancement module, configured to generate the shadow texture corresponding to the target area based on the first normal vector and the light reflection intensity, and use the shadow texture to perform texture enhancement display on the infrared cloud map data to obtain target infrared cloud map data; The normal vector determination module is specifically configured to: Determine the cloud top height based on the bright temperature data to determine the pixel vertices belonging to the clear sky sea and land surface and the pixel vertices belonging to the cloud body in the infrared cloud map data; Respectively determine the temperature gradients corresponding to the pixel vertices belonging to the clear sky sea and land surface; and the temperature gradients corresponding to the pixel vertices belonging to the cloud body; Determine the initial normal vector of the surface where each pixel vertex is located according to the temperature gradient corresponding to each pixel vertex and the surface elevation data; For each of the pixel vertices, determine a plurality of adjacent pixel vertices corresponding to the pixel vertex from the infrared cloud map data, and use the average value of the initial normal vectors corresponding to the adjacent pixel vertices as the first normal vector corresponding to the pixel vertex.

8. An electronic device, characterized in that, Including a processor and a memory, the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when called and executed by a processor, cause the processor to implement the method according to any one of claims 1 to 6.

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