A remote sensing data real-time processing system

Abstract

The application discloses a kind of remote sensing data real-time processing systems, it is related to remote sensing data processing technical field, it solves the technical problem that internal image exists a lot of noise points and the shadow part of image path is not removed, after removing the noise point to several groups of microimage, line optimization is carried out, the virtual path in microimage is analyzed and optimized, the center point of virtual path is determined, the periphery shadow of virtual path is removed, to improve the overall quality of several groups of microimage, according to the shadow existing in the periphery of single level path according to path solid line is optimized, the overall brightness of shadow is weakened, the overall line width of path solid line is enhanced, to optimize single level path, the hierarchical path after processing is compensated into original microimage, to improve the contour recognition degree of several microimages, improve the overall stereoscopic feeling of several microimages.

Description

Technical Field

[0001] This invention belongs to the field of remote sensing data processing technology, specifically a real-time remote sensing data processing system. Background Technology

[0002] Remote sensing satellite data is generated by remote sensing satellites detecting the reflection of electromagnetic waves by objects on the Earth's surface and the electromagnetic waves emitted by those objects. This allows them to extract information about the objects, identify them over long distances, and convert these electromagnetic waves into visual images, which are satellite images.

[0003] The invention disclosed in patent publication number CN102708156B is a remote sensing data processing system, including a main control unit, multiple computing nodes, and a disk array. The disk array is used to store raw remote sensing data and remote sensing products. The main control unit is used to retrieve the required raw remote sensing data according to the type of remote sensing product being produced, preprocess the raw remote sensing data, and distribute the preprocessed remote sensing data and the raw remote sensing data to the multiple computing nodes. The computing nodes are used to generate remote sensing products from the preprocessed remote sensing data. This invention's remote sensing data processing system can rapidly process massive amounts of remote sensing data at various levels in real time, ensuring efficient processing and enabling the production of various remote sensing products as needed.

[0004] When processing remote sensing image data, because the images are taken by remote sensing satellites, the resolution and texture of the images are very high. However, there are still a lot of noise in the internal images. If the internal noise is not removed, the overall quality of the image is not high. At the same time, because the path is long, there are shadows on the stereo path of the captured image. If these shadows are not removed, the stereo effect of the captured image is not strong, and the overall quality of the image is not high. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a real-time remote sensing data processing system to solve the technical problems of a large amount of noise in internal images and the failure to remove shadow parts of image paths.

[0006] To achieve the above objectives, an embodiment of the first aspect of the present invention provides a real-time remote sensing data processing system, comprising a data image acquisition terminal, an image processing center, and a display terminal;

[0007] The image processing center includes an image noise reduction unit, an image pre-segmentation management unit, a line optimization unit, a micro-image merging unit, and a merging curve removal unit;

[0008] The data image acquisition terminal is used to acquire remote sensing data images taken by satellites and transmit the acquired remote sensing data images to the image processing center.

[0009] The image pre-segmentation management unit inside the image processing center is used to pre-segment the acquired remote sensing data images and divide the original remote sensing data images into several micro-images according to the preset segmentation size.

[0010] The image denoising unit performs denoising processing on several groups of micro-images segmented by the image pre-segmentation management unit. It uses a black and white template merging method to display noise of different colors, then removes the displayed noise, and then transmits the several groups of micro-images after noise removal to the image pre-segmentation management unit.

[0011] The line optimization unit performs line optimization on several sets of micro-images after noise removal, analyzes and optimizes the virtual path within the micro-image, determines the center point of the virtual path, and removes the surrounding shadows of the virtual path, thereby improving the overall quality of several sets of micro-images.

[0012] The micro-image merging unit receives several sets of micro-images and merges and integrates them according to the adjacent edge markers of the micro-images to obtain an optimized remote sensing data image.

[0013] Preferably, the image pre-segmentation management unit performs pre-segmentation management on the acquired remote sensing data images in the following manner:

[0014] The remote sensing data image is segmented according to the preset segmentation size Y1×Y2, where Y1 and Y2 are preset parameters and their specific values ​​are determined by the operator.

[0015] The remote sensing data image is segmented sequentially using one endpoint as the initial point to obtain several micro-images. The adjacent edges of the micro-images are marked, with different adjacent edges using different labels. At the same time, the initially segmented micro-image is marked as the initial image.

[0016] Preferably, the image noise reduction unit removes the displayed noise in the following specific manner:

[0017] Several sets of micro-images are sequentially merged and matched with a pure black template. The micro-images are placed on top of the pure black template. The dark noise points displayed inside the micro-images are marked. After marking, the dark noise points are removed. The micro-images with the dark noise points removed are then processed for the next step.

[0018] Then, the micro-images with dark noise removed are merged and matched with the pure white template. The micro-images are placed on top of the pure white template, and the light-colored noise inside the micro-images is marked. After marking, the light-colored noise is removed, and the micro-images with light noise removed are retransmitted to the image pre-segmentation management unit.

[0019] Preferably, the route optimization unit analyzes and optimizes the virtual path within the micro-image in the following specific manner:

[0020] The hierarchical paths within each group of micro-images are sequentially acquired. Each individual hierarchical path is segmented into several short paths to be processed according to a preset segmentation size C1, where the segmentation size C1 is a preset parameter.

[0021] The peripheral shadow contours of several short paths to be processed are obtained, and the center point of a single group of short paths to be processed is determined by the obtained peripheral shadow contours.

[0022] Several short paths belonging to a single level path are merged, and according to the determined center points of several groups of short paths to be processed, the center points of several groups of short paths to be processed belonging to the same straight line are connected to determine the overall solid line position of the path. The center points that deviate from this level path are adjusted and placed within the same solid line of the path.

[0023] After the adjustment is completed, the shadows around the single-level path are optimized according to the solid path line, the overall brightness of the shadows is weakened, and the overall line width of the solid path line is enhanced. This optimizes the single-level path. Then, several different level paths are processed in sequence, and the processed level paths are compensated into the original micro-image.

[0024] Preferably, the merging curve removal unit removes merging lines generated during the merging process of the optimized remote sensing data image to improve the overall quality of the entire remote sensing data image. The specific method for removing merging lines is as follows:

[0025] At several micro-image merging route locations, the merging and stitching locations of several micro-images are moved a specific distance towards the adjacent edge marker, where the specific parameters of the specific distance are determined by the operator based on experience;

[0026] The image of a certain micro-image is removed from the overlapping area of ​​the two sets of images at the merged and stitched position, and the processed remote sensing data image is transmitted to the display terminal.

[0027] Preferably, the display terminal displays the optimized remote sensing data image for external personnel to view.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows: remote sensing data images are acquired in advance, and then the acquired remote sensing data images are pre-segmented and managed. According to the pre-set segmentation size, the original remote sensing data images are segmented into several micro-images. Then, several groups of micro-images are subjected to noise reduction processing. By using a black and white template merging method, noise of different colors is displayed. Then, the displayed noise is removed. Then, several groups of micro-images after noise removal are transmitted to the image pre-segmentation management unit. By using a black and white template to remove noise, dark noise and light noise inside the image can be displayed. Then, the displayed noise is removed, which can improve the overall effect of noise removal.

[0029] Next, the circuit optimization is performed on several sets of micro-images after noise removal. The virtual path within the micro-image is analyzed and optimized to determine the center point of the virtual path. The shadows around the virtual path are removed to improve the overall quality of several sets of micro-images. The shadows around the single-level path are optimized based on the solid path line to weaken the overall brightness of the shadows. The overall line width of the solid path line is enhanced to optimize the single-level path. The processed level path is then compensated into the original micro-image to improve the contour recognition of several micro-images and enhance the overall three-dimensionality of several micro-images. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the principle framework of the present invention. Detailed Implementation

[0031] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Please see Figure 1 This application provides a real-time remote sensing data processing system, including a data image acquisition terminal, an image processing center, and a display terminal;

[0033] The data image acquisition terminal is electrically connected to the input terminal of the image processing center, and the image processing center is electrically connected to the input terminal of the display terminal;

[0034] The image processing center includes an image noise reduction unit, an image pre-segmentation management unit, a line optimization unit, a micro-image merging unit, and a merging curve removal unit;

[0035] The image pre-segmentation management unit is bidirectionally connected to the image noise reduction unit and the circuit optimization unit, respectively. The image pre-segmentation management unit is electrically connected to the input terminal of the micro-image merging unit, and the micro-image merging unit is bidirectionally connected to the merging curve removal unit.

[0036] The data image acquisition terminal is used to acquire remote sensing data images taken by satellites and transmit the acquired remote sensing data images to the image processing center.

[0037] The image pre-segmentation management unit inside the image processing center is used to pre-segment the acquired remote sensing data images. According to a pre-set segmentation size, the original remote sensing data images are divided into several micro-images. The specific method of pre-segmentation management is as follows:

[0038] The remote sensing data image is segmented according to the preset segmentation size Y1×Y2, where Y1 and Y2 are preset parameters and their specific values ​​are determined by the operator.

[0039] The remote sensing data image is segmented sequentially using one endpoint as the initial point to obtain several micro-images. The adjacent edges of the micro-images are marked, and different adjacent edges are marked differently (these micro-images can then be integrated to obtain the original remote sensing data image). At the same time, the initially segmented micro-image is marked as the initial image.

[0040] The image denoising unit performs denoising processing on several groups of micro-images segmented by the image pre-segmentation management unit. It uses a black-and-white template merging method to display noise of different colors, then removes the displayed noise, and finally transmits the noise-removed groups of micro-images to the image pre-segmentation management unit. The specific method for removing the displayed noise is as follows:

[0041] Several sets of micro-images are sequentially merged and matched with a pure black template. The micro-images are placed on top of the pure black template. The dark noise points displayed inside the micro-images are marked. After marking, the dark noise points are removed. The micro-images with the dark noise points removed are then processed for the next step (this method can effectively display and remove dark noise points in micro-images).

[0042] Then, the micro-images with dark noise removed are merged and matched with the pure white template. The micro-images are placed on top of the pure white template, and the light-colored noise inside the micro-images is marked. After marking, the light-colored noise is removed, and the micro-images with light noise removed are retransmitted to the image pre-segmentation management unit.

[0043] The line optimization unit performs line optimization on several sets of micro-images after noise removal. It analyzes and optimizes the virtual paths within the micro-images, determines the center point of the virtual paths, and removes the surrounding shadows of the virtual paths, thereby improving the overall quality of the several sets of micro-images. The specific method for analyzing and optimizing the virtual paths within the micro-images is as follows:

[0044] The hierarchical paths within each set of micro-images are sequentially obtained (which can be understood as multiple edges of a building; the edges are optimized to improve the solid structure of the building). Each hierarchical path is segmented into several short paths to be processed according to a preset segmentation size C1. The segmentation size C1 is a preset parameter, and its specific value is determined by the operator based on experience.

[0045] The peripheral shadow contours of several short paths to be processed are obtained, and the center point of a single group of short paths to be processed is determined by the obtained peripheral shadow contours.

[0046] Several short paths belonging to a single level path are merged, and according to the determined center points of several groups of short paths to be processed, the center points of several groups of short paths to be processed belonging to the same straight line are connected to determine the overall solid line position of the path. The center points that deviate from this level path are adjusted and placed within the same solid line of the path.

[0047] After adjustment, the shadows around the single-level path are optimized according to the solid path line, the overall brightness of the shadows is weakened, and the overall line width of the solid path line is enhanced. This optimizes the single-level path. Then, several different level paths are processed in sequence, and the processed level paths are compensated into the original micro-images. This improves the contour recognition of several micro-images and enhances the overall three-dimensionality of several micro-images. The processed micro-images are then transmitted to the micro-image merging unit.

[0048] The micro-image merging unit receives several sets of micro-images and merges and integrates them according to the adjacent edge markers of the micro-images to obtain an optimized remote sensing data image.

[0049] The merging curve removal unit removes merging lines generated during the merging process of the optimized remote sensing data image, thereby improving the overall quality of the entire remote sensing data image. The specific method for removing merging lines is as follows:

[0050] At several micro-image merging route locations, the merging and stitching locations of several micro-images are moved a specific distance towards the adjacent edge mark. The specific parameters of the specific distance are determined by the operator based on experience, and the specific distance is generally 0.002mm.

[0051] The image of a certain micro-image is removed from the overlapping area of ​​the two sets of images at the merged and stitched position, and the processed remote sensing data image is transmitted to the display terminal.

[0052] The display terminal displays the optimized remote sensing data images for external viewing.

[0053] The data in the above formula are all calculated by removing the dimensions and taking the numerical values. The formula is the closest to the real situation obtained by software simulation of a large amount of collected data. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained through simulation of a large amount of data.

[0054] The working principle of this invention is as follows: Remote sensing data images are acquired in advance, and then the acquired remote sensing data images are pre-segmented and managed. According to the pre-set segmentation size, the original remote sensing data images are segmented into several micro-images. Then, several groups of micro-images are subjected to noise reduction processing. By using a black and white template merging method, noise of different colors is displayed. Then, the displayed noise is removed. Then, several groups of micro-images after noise removal are transmitted to the image pre-segmentation management unit. By using a black and white template to remove noise, dark noise and light noise inside the image can be displayed. Subsequently, the displayed noise is removed, which can improve the overall noise removal effect.

[0055] Next, the circuit optimization is performed on several sets of micro-images after noise removal. The virtual path within the micro-image is analyzed and optimized to determine the center point of the virtual path. The shadows around the virtual path are removed to improve the overall quality of several sets of micro-images. The shadows around the single-level path are optimized based on the solid path line to weaken the overall brightness of the shadows. The overall line width of the solid path line is enhanced to optimize the single-level path. The processed level path is then compensated into the original micro-image to improve the contour recognition of several micro-images and enhance the overall three-dimensionality of several micro-images.

[0056] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A real-time processing system for remote sensing data, characterized in that, The system comprises a data image acquisition terminal, an image processing center and a display terminal. The image processing center comprises an image noise reduction unit, an image pre-segmentation management unit, a line optimization unit, a micro image merging unit and a merged curve removal unit. The data image acquisition terminal is configured to acquire remote sensing data images captured by a satellite and transmit the acquired remote sensing data images to the image processing center. The image pre-segmentation management unit inside the image processing center is configured to pre-segment the acquired remote sensing data images according to a pre-set segmentation size, and divide the original remote sensing data images into a plurality of micro images. The image noise reduction unit is configured to reduce noise of the plurality of micro images segmented by the image pre-segmentation management unit, display different color noise points by using a black and white template merging method, remove the displayed noise points, and transmit the plurality of micro images after the noise points are removed to the image pre-segmentation management unit. The line optimization unit is configured to optimize lines of the plurality of micro images after the noise points are removed, analyze and optimize virtual paths in the micro images, determine center points of the virtual paths, and remove peripheral shadows of the virtual paths, so as to improve the overall quality of the plurality of micro images, in a specific manner as follows: a hierarchical path inside each micro image is acquired from the plurality of micro images, and a single hierarchical path is segmented according to a pre-set segmentation size C1, wherein the segmentation size C1 is a pre-set parameter; peripheral shadow contours of a plurality of to-be-processed short radii are acquired, and center points of the plurality of to-be-processed short radii are determined according to the acquired peripheral shadow contours; the plurality of to-be-processed short radii belonging to a single hierarchical path are merged, and the center points of the plurality of to-be-processed short radii belonging to the same straight line are connected according to the determined center points of the plurality of to-be-processed short radii, so as to determine a position of an overall path solid line, and the center points deviating from the hierarchical path are trimmed and adjusted to be in the same path solid line; after the adjustment, peripheral shadows of a single hierarchical path are optimized according to the path solid line, the overall brightness of the shadows is weakened, the overall line width of the path solid line is enhanced, so as to optimize the single hierarchical path, and a plurality of different hierarchical paths are processed in sequence, and the processed hierarchical paths are compensated to the original micro images; the micro image merging unit is configured to receive the plurality of micro images, merge and integrate the plurality of micro images according to adjacent edge marks of the plurality of micro images, and obtain an optimized remote sensing data image.

2. The real-time processing system of remote sensing data according to claim 1, characterized in that, The image pre-segmentation management unit is configured to pre-segment the acquired remote sensing data images in a specific manner as follows: the remote sensing data images are segmented according to a pre-set segmentation size Y1×Y2, wherein Y1 and Y2 are pre-set parameters, and the specific values are determined by an operator. According to one end point of the remote sensing data image as an initial point, the remote sensing data image is sequentially segmented to obtain a plurality of micro images, and adjacent micro image edges are marked, different edges are marked with different edge markers, and the initial segmented micro image is marked as an initial image.

3. The real-time processing system of remote sensing data according to claim 2, characterized in that, The specific way of removing the displayed noise points by the image denoising unit is: The plurality of groups of micro images are sequentially matched with the pure black template, the micro images are placed above the pure black template, the dark noise points displayed in the plurality of groups of micro images are marked, after the marking is completed, the plurality of dark noise points are removed, and the plurality of groups of micro images from which the dark noise points are removed are subjected to next step processing; The plurality of groups of micro images from which the dark noise points are removed are matched with the pure white template, the micro images are placed above the pure white template, the light noise points displayed in the plurality of groups of micro images are marked, after the marking is completed, the plurality of light noise points are removed, and the plurality of groups of micro images from which the light noise points are removed are transmitted to the image pre-segmentation management unit again.

4. The system of claim 1, wherein, The specific way of removing the plurality of groups of micro images from which the dark noise points are removed is: At the plurality of micro image merging line positions, the merging and splicing positions of the plurality of micro images are moved to the edge markers by a specific distance, wherein the specific distance is determined by the operator according to experience; The image of a certain group of micro images is removed from the two groups of overlapping areas at the merging and splicing positions, and the processed remote sensing data image is transmitted to the display terminal.

5. The real-time processing system of remote sensing data according to claim 4, characterized in that, The display terminal displays the optimized remote sensing data image for external personnel to view. The display terminal displays the optimized remote sensing data image for external personnel to view.

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