18 results about "Cirrus cloud" patented technology

This invention discloses a real-time rendering method and system for physically simulated volumetric clouds. The method includes the following steps: constructing a dynamic noise mixing model, and constructing complex cloud layers by mixing multiple noises based on the dynamic noise mixing model; constructing a multi-scattering illumination model, and using the multi-scattering illumination model to perform single-scattering calculations and multi-scattering approximations on the complex cloud layers to simulate illumination; based on the completed illumination simulation, dividing the cloud density field of the complex cloud layers into several voxel blocks, and performing adaptive light travel processing to complete the real-time rendering of volumetric clouds. This invention, without sacrificing image quality and rendering efficiency, integrates advanced cloud modeling theory with efficient GPU acceleration technology, and uses a mixed noise model to generate diverse cloud structures, accurately reproducing various typical cloud types such as high-altitude cirrus clouds, cumulus clouds, and stratus clouds.

The application discloses a water body extraction method based on combined water body index frequency, comprising the following steps: S1, acquiring remote sensing image data and pre-processing the remote sensing image data; S2, constructing a water body index and constructing an instantaneous water body extraction decision tree model according to the water body index; S3, performing instantaneous water body pixel recognition and extraction according to the instantaneous water body extraction decision tree model, discriminating the water body and preliminarily determining the average water body; S4, extracting the water edge line by using a Canny edge detection method, and determining the average water body extraction result according to the output water body pixel value, the edge detection and the boundary elimination result. The application can realize average water body extraction based on dense long-time sequence images, improve the water body extraction precision, improve the effectiveness of water body extraction in the building shadow and terrain shadow noise environment, resist the interference of the cirrus cloud noise in the single image, and make the large-scale and long-time sequence water body extraction more universal.

The invention discloses a physical simulation volume cloud real-time rendering method and system, and the method comprises the following steps: constructing a dynamic noise mixing model, and constructing a complex cloud layer through mixing a plurality of noises based on the dynamic noise mixing model; constructing a multi-scattering illumination model, performing single-scattering calculation and multi-scattering approximation on the complex cloud layer by using the multi-scattering illumination model, and performing illumination simulation; on the basis that illumination simulation is completed, a cloud layer density field of the complex cloud layer is divided into a plurality of voxel blocks, light advancing self-adaptive processing is carried out, and volume cloud real-time rendering is completed. On the premise of not sacrificing image quality and rendering efficiency, an advanced cloud modeling theory and an efficient GPU acceleration technology are fused, a diversified cloud body structure is generated by adopting a mixed noise model, and various typical cloud types such as high-altitude cirrus cloud, cumulus cloud and layer cloud can be accurately represented.

1. Name of the product in this design: Pot holder (cloud-shaped). 2. Purpose of this design: To support a teapot. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention discloses an overshoot cloud top identification and area calculation method and device based on geostationary satellite data. The method comprises the following steps: acquiring geostationary satellite cloud radiation brightness temperature data and troposphere top temperature data of a target area in a required time period; extracting cloud radiation brightness temperature of water vapor, ozone and infrared channels; after space-time matching, a multi-channel threshold discrimination method is used to identify potential overshoot cloud top pixels; based on the infrared brightness temperature data, utilizing an isotherm analysis method to identify a potential overshoot cloud top area and an anvil cloud area corresponding to each potential overshoot cloud top pixel; identifying an overshoot cloud top region and calculating the area of the overshoot cloud top region by comparing the average brightness temperature difference between the potential overshoot cloud top pixel and the anvil cloud region; the device comprises a data receiving and caching module, a data processing unit and a result output unit, and all the steps in the method are achieved. According to the method, satellite multi-channel brightness temperature data and troposphere top temperature data are combined, interference of cirrus cloud pixels is effectively eliminated, the overshoot cloud top is accurately recognized, and overshoot cloud top area calculation is achieved.

The invention provides a cloud and cloud shadow information detection and extraction method based on a Landsat8 remote sensing image. Compared with a traditional cloud and cloud shadow information extraction method, the method innovatively constructs a land brightness temperature threshold empirical linear model according to the three spectral characteristics of high brightness, high whiteness and low brightness temperature of a cloud layer, refines a land brightness temperature threshold, extracts thick cloud, and improves the cloud shadow extraction efficiency. Extracting thin cloud by using a haze optimization transformation method and a cirrus cloud waveband threshold method, and performing superposition processing on the extracted thick cloud information and thin cloud information to obtain cloud information C; the method comprises the following steps: extracting cloud shadow information CS by using a threshold method by using an operation relationship between a darkness index (DI) and a spectrum, constructing an empirical linear model between a mountain shadow threshold and a solar altitude, and removing false information in the cloud shadow information CS caused by the mountain shadow to obtain refined cloud shadow information CS '. And finally, standardizing the shape of the extracted cloud and cloud shadow information by using a corrosion and expansion method, and eliminating holes, thereby improving the precision of the cloud C and cloud shadow information CS '. Compared with a traditional method, the method has the advantages that the extraction precision of thick cloud is improved by constructing the land brightness temperature threshold empirical linear model, and the extraction precision of cloud shadow is improved by constructing the mountain shadow threshold empirical linear model. Therefore, the method has the advantages of rapidness, high efficiency, convenience and high precision.

The application provides a method for generating a remote sensing multispectral image defogging dataset. The method is based on a preset number of cirrus channel images without fog and remote sensing multispectral images, and combines an atmospheric scattering model, so that a relatively realistic remote sensing multispectral image defogging dataset with fog and without fog can be generated. The method can effectively alleviate the condition that a remote sensing multispectral image defogging algorithm based on deep learning lacks a large number of remote sensing multispectral image datasets with fog and without fog.

Embodiments of the present application relate to the technical field of image processing, in particular to a high-altitude cirrus cloud detection method and device, electronic equipment and storage medium. The method comprises: acquiring a first infrared image and a second infrared image, the first infrared image and the second infrared image being adjacent two frames of infrared images; constructing a first image pyramid of the first infrared image and a second image pyramid of the second infrared image, the number of layers of the first image pyramid and the second image pyramid and the size of each layer of image being the same; based on the correlation of the first image pyramid and the second image pyramid in space-time, obtaining the optical flow vector field of the first infrared image by using the optical flow method; performing threshold segmentation and morphological operation on the optical flow vector field of the first infrared image to obtain the detection result of the first infrared image. The scheme can improve the detection accuracy of high-altitude cirrus cloud and has low false detection rate.

The invention discloses a polarization two-channel gain ratio inversion method based on a polarization laser radar, and belongs to the technical field of polarization laser radar inversion methods. The method comprises the following steps: selecting the weather with cirrus clouds, and carrying out vertical detection on the atmosphere by using a polarization laser radar to obtain a first group of data and a second group of data; respectively extracting corresponding total polarization channel data from the two groups of data; performing inversion by using a Klett equation to obtain a volume cloud layer optical thickness corresponding to the second group of data; combining the volume cloud layer part of the second group of polarization channel total data with the non-volume cloud layer part of the first group of polarization channel total data to generate mixed data; the polarization two-channel gain ratio of the volume cloud layer part in the mixed data is adjusted, the optical thickness of the volume cloud layer can be changed, and when the optical thickness of the volume cloud layer obtained by inversion of the mixed data is consistent with a result obtained by using the second group of data, the polarization two-channel gain ratio of the volume cloud layer is the polarization two-channel gain ratio corresponding to the second group of data.

Disclosed is a cirrus image generation method that solves the problem that remote sensing image dehazing datasets are not real and the number of cirrus image features is limited. The present disclosure includes: Obtaining real cirrus images, preprocessing; using a forward process diffusion, constructing a Markov chain, and adding random noise gradually to the cirrus image of the cirrus image dataset. A training dataset is constructed according to the pure noise image and the corresponding real noise. Taking the pure noise image as the input and the corresponding noise as the output, a noise prediction model is established, and the training dataset is used for training, by inputting the randomly generated noise image into the trained noise prediction model, and combining the predicted noise with posterior probability to perform reverse denoising on the image. After a set number of denoising steps, a cirrus image is obtained with real cirrus features.

The invention provides a cloud and cloud shadow information detection and extraction method based on a Landsat8 remote sensing image. Compared with a traditional cloud and cloud shadow information extraction method, the method innovatively constructs a land brightness temperature threshold empirical linear model according to the three spectral characteristics of high brightness, high whiteness and low brightness temperature of a cloud layer, refines a land brightness temperature threshold, extracts thick cloud, and improves the cloud shadow extraction efficiency. Extracting thin cloud by using a haze optimization transformation method and a cirrus cloud waveband threshold method, and performing superposition processing on the extracted thick cloud information and thin cloud information to obtain cloud information C; the method comprises the following steps: extracting cloud shadow information CS by using a threshold method by using an operation relationship between a darkness index (DI) and a spectrum, constructing an empirical linear model between a mountain shadow threshold and a solar altitude, and removing false information in the cloud shadow information CS caused by the mountain shadow to obtain refined cloud shadow information CS '. And finally, standardizing the shape of the extracted cloud and cloud shadow information by using a corrosion and expansion method, and eliminating holes, thereby improving the precision of the cloud C and cloud shadow information CS '. Compared with a traditional method, the method has the advantages that the extraction precision of thick cloud is improved by constructing the land brightness temperature threshold empirical linear model, and the extraction precision of cloud shadow is improved by constructing the mountain shadow threshold empirical linear model. Therefore, the method has the advantages of rapidness, high efficiency, convenience and high precision.

The invention provides an accumulated snow information extraction method and device, electronic equipment and a medium, and the method comprises the steps: obtaining a remote sensing image of to-be-extracted accumulated snow information, and carrying out the preprocessing of the remote sensing image; calculating an accumulated snow index and a cirrus cloud index of a specified wave band of each pixel of the preprocessed remote sensing image; and determining an accumulated snow area based on the accumulated snow index and the cirrus cloud index. According to the method, the accumulated snow information in the emergency disaster reduction second satellite data can be effectively extracted, and the accuracy of accumulated snow extraction is improved.

1. Name of the product in this design: Landscape Street Light (Cloud Reflecting the Jade Wall). 2. Intended use of this design: outdoor lighting. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The rear view is the same as the front view, so the rear view is omitted; the right view is the same as the left view, so the right view is omitted.

The present invention discloses a cloud detection method for optical remote sensing images that combines spectral features and texture features. The method comprises: obtaining a primary common cloud detection result; obtaining texture features of the remote sensing image based on a gray-level co-occurrence matrix; obtaining a secondary common cloud detection result based on the texture features and a first feature threshold; obtaining a common cloud extraction result based on the primary common cloud detection result and the secondary common cloud detection result; performing radiometric calibration on the remote sensing image to obtain reflectivity; obtaining a primary cirrus cloud detection result based on a second feature threshold and the reflectivity; obtaining a secondary cirrus cloud detection result based on the texture features and the second feature threshold; obtaining a cirrus cloud extraction result based on the primary cirrus cloud detection result and the secondary cirrus cloud detection result; and obtaining a target cloud detection result based on the common cloud extraction result and the cirrus cloud extraction result. The present invention can improve the accuracy and efficiency of cloud detection, reduce labor costs, and can be widely applied in the field of image processing technology.

A cirrus cloud image generation method based on unclassified guidance solves the problems of unreliable remote sensing image defogging datasets and a limited number of cirrus cloud image features, belonging to the field of image generation technology. The invention comprises the following steps: obtaining a real cirrus cloud image, and obtaining a cirrus cloud image dataset after preprocessing; constructing a Markov chain using forward process diffusion, and gradually adding random noise that follows a Gaussian distribution to the cirrus cloud image in the cirrus cloud image dataset, so that the cirrus cloud image is noisy to a pure noise image; constructing a training dataset based on the pure noise image and the corresponding real noise; establishing a noise prediction model using the pure noise image as input and the corresponding noise as output, and training using the training dataset; inputting the randomly generated noise image into the trained noise prediction model, and performing reverse denoising on the image using the predicted noise combined with the posterior probability. After a set number of denoising steps, a cirrus cloud image with real cirrus cloud features is obtained.

1. Name of the product in this design: Bracelet (Clouds and Moon). 2. Purpose of this design: For wearing as an ornament. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides a cirrus cloud generation method and device, electronic equipment and a storage medium, and the method comprises the steps: creating a first patch, generating a basic cirrus cloud based on the morphological parameters of the cirrus cloud, and adding texture features to obtain a second cirrus cloud; meanwhile, creating a second patch, generating a cloud sea based on the cloud sea parameters, and performing physical solution processing to obtain dynamic cloud and mist; and finally, combining the second cirrus cloud, the cloud sea and the dynamic cloud to generate a dynamic cirrus cloud. According to the method, cirrus cloud form customization, dynamic cloud simulation and rapid combination are efficiently realized through parameterization staged generation and a multi-level fusion technology, and the generation efficiency and the visual quality are remarkably improved.