14 results about "Image mosaicking" patented technology

The invention provides a three-dimensional image modeling method and device based on plane data, and the method comprises the steps: carrying out the full-color / multispectral band fusion, bit depth adjustment, thin cloud removal, image enhancement, stripe removal and light and color uniformity of a satellite surveying and mapping image, and achieving the real color recovery of the image; performing splicing preprocessing on the plurality of small orthographic satellite surveying and mapping images after real color recovery, performing image registration on the to-be-registered image and a reference image, performing image geometric correction on the registered image, and performing image mosaic processing on the plurality of images after image geometric correction to obtain a single large-scene image; and three-dimensional image matching, building mask extraction, three-dimensional building modeling and three-dimensional building post-processing are carried out on a single large scene image to obtain a three-dimensional digital surface model, and ground three-dimensional real image modeling is completed. By applying the technical scheme of the invention, the technical problem that the existing two-dimensional surveying and mapping data is difficult to meet the increasing application requirements of three-dimensional scenes is solved.

This invention relates to the field of power system image processing technology and discloses a self-attention-based remote sensing method for detecting tree obstacles in power transmission channels. The method first acquires extremely high-resolution remote sensing image data, followed by preprocessing such as image mosaicking and sliding window cropping. A sample library is then constructed, and 5% of the image blocks are randomly selected for manual annotation for training. The annotated categories include tree obstacle areas, power facilities, and other background data. A power facility detection network and a tree obstacle detection network are constructed and trained. Tree obstacle detection within the transmission channel is performed, and the detected power lines and other facilities are superimposed and spliced ​​back to the original image size to obtain the overall tree obstacle detection result. This method extracts data using two single-task networks and then overlays and analyzes the results, avoiding the interference of overlapping regions when using a single network to perform multiple classification tasks, as well as the impact of class imbalance on accuracy.

This application relates to the field of image processing technology, specifically to an orthophoto mosaicking method and system applicable to remote sensing images, which specifically includes: analyzing the similarity of luminance values between data points in multi-spectral remote sensing images, obtaining the ratio relationship between different regions, so as to achieve precise division of different regions in the image, and further obtaining the difference values between these regions. Furthermore, during the image mosaicking process, targeted correction is performed on low-luminance regions according to the obtained difference values to improve the overall effect of image fusion mosaicking; in the orthophoto generated by processing mountain remote sensing images, the luminance difference between the sunny region and the shady region can be further used to determine the adjustment amplitude required for the shady region during HSV fusion mosaicking, so as to be able to adaptively adjust the luminance of the shady region, combine with the high-resolution panchromatic orthophoto to obtain a high-resolution multi-spectral orthophoto with adjusted luminance, and then perform orthophoto mosaicking to improve the fusion effect of the mosaicked image.

This invention, applicable to the field of agricultural information technology, provides a straw index assessment method based on large-scale image stitching. By combining image stitching technology with straw image segmentation technology, this method achieves high-precision estimation of straw coverage within a large area, significantly improving the accuracy of straw coverage estimation for large images. Using image stitching technology, the image resolution is largely preserved on the basis of existing single images, ensuring the integrity of details in large-scale images, thereby improving the accuracy of coverage estimation and effectively enhancing the accuracy and reliability of large-scale straw coverage assessment.

The present invention provides a remote sensing orthoimage seamline generation method, comprising: constructing constrained triangulation networks in effective intersection areas of adjacent orthoimages one by one; transforming an image topology search problem into a polygon selection problem of a triangle to generate a primary seamline network; and optimizing primary seamlines on the basis of building vector data and road vector data to generate an advanced seamline network. The advanced seamline network generated in the present invention can effectively avoid areas such as buildings and roads, and can achieve large-range image mosaicking, a mosaicking result is independent of the processing sequence, the flexibility and high efficiency are achieved during mosaicking processing, and the accumulation of errors is avoided.

This invention discloses an image mosaicking method based on latitude and longitude grid segmentation constraints, belonging to the field of surveying and remote sensing technology. The method includes: acquiring mosaicking range lines, standard map sheet data, and standard map sheet data containing map sheet row and column boundaries and inner map frame inflection points; generating a minimum rectangular range area for the mosaicking region using the mosaicking range lines; filtering image data to be mosaicked from the standard map sheet data; arranging the map sheet row and column boundaries according to row and column boundaries respectively; calculating the median value of adjacent boundaries; and writing the four extreme values ​​of the minimum rectangular range area for the mosaicking region into the sorting endpoints of the median values ​​of adjacent boundaries to obtain row and column segmentation data; generating intermediate segmentation lines based on the row and column segmentation data; and forming small rectangles by the intersection of the intermediate segmentation lines; converting the inner map frame inflection points within the small rectangles into image point coordinates to generate quarter points. This invention can stably constrain a single image source in the overlapping area under the condition of latitude and longitude grid standard map sheet image expansion and overlap.

The present disclosure proposes a remote sensing image mosaicking method, apparatus, device and storage medium, the method comprising: determining a corresponding image mosaicking mode based on an application scenario of a current mosaicking task; obtaining an image data source under the determined image mosaicking mode, screening the image data source, and filtering out image data for image mosaicking from the image data source; constructing mosaicking lines based on the image data using a mosaicking line construction strategy associated with the image mosaicking mode; and mosaicking the image data according to the constructed mosaicking lines, thereby realizing automated operation of remote sensing image mosaicking for different scenarios.

The present invention discloses a remote sensing image mosaicking method based on image quality, which includes the following steps: obtaining evaluation indicators and establishing first, second, and third evaluation criteria respectively according to the evaluation indicators through weighted summation operations; screening images to be mosaicked according to the first and second evaluation standards and determining the mosaicking order to obtain a mosaicking scheme, and performing virtual mosaicking according to the mosaicking scheme to obtain a virtual synthetic image; performing an overall evaluation of multiple virtual synthetic images based on the third evaluation standard to select the optimal mosaicking scheme; and mosaicking the images to be mosaicked using image mosaicking technology according to the optimal mosaicking scheme. This method not only performs local evaluation on the individual images involved in the mosaicking, but also performs an overall evaluation on the virtual mosaicked synthetic image after virtual mosaicking, thereby ensuring that the quality of the images involved in the mosaicking is optimal and that the overall quality of the mosaicked synthetic image is at a high level.

The present invention discloses a mineral index calculation method and system based on global multispectral remote sensing images, which belongs to the field of image data processing technology. The method includes: obtaining original remote sensing image data and parsing metadata; based on the metadata, screening the original remote sensing image data and eliminating invalid data; resampling and slicing the remote sensing image data; performing data preprocessing, converting the resampled and sliced data into data that can directly calculate the mineral index; performing image mosaicking and image color matching, integrating different remote sensing image slices in the same geographical area into a single, continuous image, and reducing the color difference between slices to obtain a global map; calculating the mineral index indicator based on the global map. The present invention realizes the whole process of automatic data screening, data preprocessing, remote sensing mosaicking and color matching to the final mineral index calculation, avoiding the storage, memory and other pressures faced by traditional software; and also uses a lookup table method to greatly save computing time.

This invention relates to an adaptive remote sensing image mosaicking method and system based on semantic understanding, belonging to the field of computer vision technology. The method includes: performing geometrical fine correction on the remote sensing image to be mosaicked, followed by semantic segmentation masking; calculating the fusion cost of pixels within overlapping regions; constructing a graph model using pixels within the overlapping regions as nodes, using the fusion cost as the edge weight between nodes and virtual points, and using the grayscale difference between adjacent nodes as the edge weight between adjacent nodes, to solve for the initial mosaicking line; dividing the overlapping region into multiple uniform sub-regions according to the semantic segmentation mask, adaptively selecting a uniform color algorithm to adjust the pixel values ​​of the remote sensing image to be mosaicked for each uniform color sub-region, obtaining a uniformly adjusted image; constructing a feathered transition region based on the initial mosaicking line, and performing weighted fusion on the uniformly adjusted image; directly mosaicking along the initial mosaicking line in non-transition regions to output a seamless mosaicked image. This invention can preserve spectral physical meaning and has strong adaptability.

The invention discloses a railway line environment multi-mode unmanned aerial vehicle remote sensing data geometric processing method, which comprises the following steps of S1, acquiring images to be matched, and forming a sequence of the images to be matched; acquiring a reference image; s2, carrying out feature point extraction on the to-be-matched image and the reference image, and constructing a high-order multi-dimensional directional feature descriptor; s3, template matching and coarse projection are carried out based on the high-order multi-dimensional directional feature descriptors of the feature points; s4, performing line element extraction and aggregation on the to-be-matched image and the reference image to obtain a corresponding line element set; s5, obtaining a to-be-matched image sequence subjected to orthographic correction through line element matching and fine projection; and S6, taking the to-be-matched image as a newly added image, carrying out incremental image mosaic line rapid calculation and iteration to obtain an optimal mosaic line, and then completing mosaic. According to the method, the coverage rate and the uniformity of the multi-modal matching points are improved; the line element integrity is improved, and the ortho-rectification precision of the multi-mode cross-view-angle unmanned aerial vehicle image is significantly improved.

The invention discloses a lake and reservoir Chl-a concentration multi-modal deep learning remote sensing inversion method considering time factors and environmental characteristics, and the method comprises the following steps: obtaining and processing data, carrying out the atmospheric correction through Sen2Cor software, carrying out the image mosaic, splicing and resampling in SNAP software, converting coordinates in a spatial dimension, calculating the line and column numbers of pixels, and carrying out the remote sensing inversion of the lake and reservoir Chl-a concentration. The method comprises the following steps: extracting and standardizing a digital quantized value, systematically fusing multiband spectrum combination features, time period features and a dynamic environment factor K by adopting a Pearson analysis method, forming a 14-dimensional input system, completely capturing nonlinear correlation between Chl-a concentration and spectral response, time rhythm and environmental suitability, solving the problem of single feature dimension in the prior art, and improving the accuracy of spectral response. The monthly average Chl-a concentration is analyzed, an environmental factor K is dynamically defined, and the driving effect of environmental conditions such as temperature and illumination on algae growth is converted into computable quantitative indexes, so that the cross-seasonal inversion adaptability is remarkably enhanced, and the dependence of a traditional method on fixed environmental parameters is broken through.

This invention provides a method, apparatus, electronic device, and storage medium for real-time mosaicking of satellite remote sensing images, relating to the field of remote sensing image processing technology. The method includes: recursively partitioning a satellite remote sensing image dataset based on a normalized partitioning algorithm to obtain multiple association groups; assigning association groups to all association groups to obtain an association group allocation scheme, where the scheme represents the optimal allocation of association groups to cache nodes; loading data using an asynchronous I / O mechanism based on an adaptive bandwidth control strategy according to the association group allocation scheme to obtain the associated image data cached in each cache node; and performing image data registration and stitching on all cached associated image data to obtain the real-time mosaicking result of the satellite remote sensing images. This invention improves the efficiency of satellite remote sensing image mosaicking processing.

The invention relates to a regional hyperspectral remote sensing image mosaic method, system and device and a medium, and belongs to the technical field of remote sensing image processing. The method comprises the following steps: acquiring a geographic range and an image spatial resolution of a target area, and calculating a row number and a column number of an image of the target area and a geographic reference transformation parameter; calculating a geographic center coordinate of each pixel of the target area image to obtain a center coordinate set; retrieving a hyperspectral image file covering the central coordinate set from a preset data pool, and extracting candidate spectral data of corresponding coordinates to form a spectral set; calculating the goodness of fit of the spectrum dominant mineral corresponding to each spectrum in the spectrum set to obtain a goodness of fit array; selecting candidate spectral data corresponding to the maximum goodness of fit, and assigning the candidate spectral data as current pixel data of the target area image; and generating a regional hyperspectral remote sensing mosaic image file based on the geographic reference transformation parameters and the assigned target region image. The method can improve the overall quality of the remote sensing image and the mineral recognition precision.