A shallow sea depth inversion method and system based on high-resolution remote sensing images

Abstract

The present application relates to the technical field of water depth inversion, and more particularly to a shallow sea water depth inversion method and system based on high-resolution remote sensing images, which comprises the following steps: dividing a target water area to obtain high-resolution remote sensing images of each sub-water area; preprocessing the high-resolution remote sensing images of each sub-water area; obtaining red, green and blue light layers of each sub-water area; assigning a corresponding water depth inversion algorithm to each sub-water area from a plurality of preset water depth inversion algorithms, wherein the water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each sub-water area adjacent to the sub-water area, and the water depth distribution of each sub-water area is obtained by inversion; and when the water depth deviation of each position repeatedly subjected to inversion does not exceed a preset deviation, the water depth distribution of each sub-water area is combined to obtain the water depth distribution of the target water area. The present application can improve the inversion speed and ensure the reliability of the inverted water depth distribution.

Description

Technical Field

[0001] This invention relates to the field of water depth inversion technology, and in particular to a method and system for shallow water depth inversion based on high-resolution remote sensing images. Background Technology

[0002] Ocean depth data measurement is one of the essential basic data for ensuring ship navigation, port and dock construction, and marine engineering. Commonly used visible light depth inversion models mainly include analytical models, semi-analytical and semi-empirical models, and statistical models. Currently, there are problems such as the need to perform overall inversion on a specified water area, which results in a long calculation process. Moreover, since a single inversion model is often used to calculate the entire specified water area, the inverted water depth distribution may have an overall deviation, and the reliability of the inverted water depth distribution cannot be guaranteed. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a method and system for shallow water depth inversion based on high-resolution remote sensing images.

[0004] The technical solution of the shallow water depth inversion method based on high-resolution remote sensing imagery of the present invention is as follows:

[0005] The target water area is divided into multiple sub-water areas, and the high-resolution remote sensing image of the target water area is divided to obtain the high-resolution remote sensing image of each sub-water area.

[0006] High-resolution remote sensing images of each sub-water area are preprocessed;

[0007] Based on the processed high-resolution remote sensing image of each sub-water area, the red, green, and blue light layers of each sub-water area are obtained;

[0008] From a variety of preset water depth inversion algorithms, a corresponding water depth inversion algorithm is assigned to each sub-water area. The water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each of the adjacent sub-water areas. Based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, the water depth distribution of the sub-water area is inverted to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained.

[0009] When the water depth deviation at each repeated inversion location does not exceed the preset deviation, the water depth distributions of all sub-water areas are merged to obtain the water depth distribution of the target water area.

[0010] The beneficial effects of the shallow water depth inversion method based on high-resolution remote sensing imagery of the present invention are as follows:

[0011] Dividing the target water area into multiple sub-water areas and performing water depth inversion separately can improve the inversion speed. Since the deviation between different water depth inversion algorithms calculating the water depth at the same location is small, when the water depth deviation at each location where the inversion is repeated does not exceed the preset deviation, the water depth distribution of each sub-water area is merged to obtain the water depth distribution of the target water area, which can ensure the reliability of the inverted water depth distribution.

[0012] Based on the above scheme, the shallow water depth inversion method based on high-resolution remote sensing images of the present invention can be further improved as follows.

[0013] Furthermore, the high-resolution remote sensing images of each sub-water area are preprocessed, including:

[0014] For each sub-water area, the high-resolution remote sensing image is sequentially subjected to deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations.

[0015] Furthermore, the preset water depth inversion algorithms include: the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, analytical models, semi-analytical and semi-empirical models, and statistical models.

[0016] Furthermore, it also includes:

[0017] An image is generated to characterize the water depth distribution of the target water area according to a preset water depth-color correspondence.

[0018] Furthermore, it also includes:

[0019] The image used to characterize the water depth distribution of the target water area is vectorized to obtain a vector image.

[0020] According to the user's request, a partial vector image is extracted from the vector image and sent to the user's smart terminal.

[0021] The technical solution of the shallow water depth inversion system based on high-resolution remote sensing imagery of the present invention is as follows:

[0022] It includes a partitioning module, a preprocessing module, an acquisition module, an inversion module, and a merging module;

[0023] The division module is used to: divide the target water area into multiple sub-water areas, divide the high-resolution remote sensing image of the target water area, and obtain the high-resolution remote sensing image of each sub-water area;

[0024] The preprocessing module is used to preprocess the high-resolution remote sensing images of each sub-water area;

[0025] The acquisition module is used to: obtain the red light layer, green light layer and blue light layer of each sub-water area based on the processed high-resolution remote sensing image of each sub-water area;

[0026] The inversion module is used to: assign a corresponding water depth inversion algorithm to each sub-water area from a variety of preset water depth inversion algorithms, and the water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each adjacent sub-water area; based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, invert the water depth distribution of the sub-water area to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained;

[0027] The merging module is used to merge the water depth distributions of all sub-water areas when the water depth deviation of each repeated inversion location is within a preset deviation, thereby obtaining the water depth distribution of the target water area.

[0028] The beneficial effects of the shallow water depth inversion system based on high-resolution remote sensing imagery of the present invention are as follows:

[0029] Dividing the target water area into multiple sub-water areas and performing water depth inversion separately can improve the inversion speed. Since the deviation between different water depth inversion algorithms calculating the water depth at the same location is small, when the water depth deviation at each location where the inversion is repeated does not exceed the preset deviation, the water depth distribution of each sub-water area is merged to obtain the water depth distribution of the target water area, which can ensure the reliability of the inverted water depth distribution.

[0030] Based on the above scheme, the shallow water depth inversion system based on high-resolution remote sensing images of the present invention can be further improved as follows.

[0031] Furthermore, the preprocessing module is specifically used for:

[0032] For each sub-water area, the high-resolution remote sensing image is sequentially subjected to deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations.

[0033] Furthermore, the preset water depth inversion algorithms include: the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, analytical models, semi-analytical and semi-empirical models, and statistical models.

[0034] Furthermore, it also includes a generation module;

[0035] The generation module is used to generate an image that characterizes the water depth distribution of the target water area according to a preset water depth-color correspondence.

[0036] Furthermore, it also includes a vectorization module and an interception and transmission module;

[0037] The vectorization module is used to: vectorize the image used to characterize the water depth distribution of the target water area to obtain a vector image;

[0038] The capture and send module is used to: capture a partial vector image from the vector image according to the user's requirements and send it to the user's smart terminal. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating a shallow water depth inversion method based on high-resolution remote sensing imagery according to an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of a shallow water depth inversion system based on high-resolution remote sensing imagery, according to an embodiment of the present invention. Detailed Implementation

[0041] like Figure 1 As shown in the figure, a shallow water depth inversion method based on high-resolution remote sensing imagery according to an embodiment of the present invention includes the following steps:

[0042] S1. Divide the target water area into multiple sub-water areas, and divide the high-resolution remote sensing image of the target water area to obtain the high-resolution remote sensing image of each sub-water area.

[0043] For example, the target water area can be divided into 9 sub-water areas using a nine-square grid method, or the target water area can be divided according to the actual situation.

[0044] S2. Preprocess the high-resolution remote sensing images of each sub-water area;

[0045] S3. Based on the processed high-resolution remote sensing image of each sub-water area, obtain the red, green, and blue light layers for each sub-water area, specifically:

[0046] Using the Ostu binarization segmentation algorithm, the near-infrared band in the processed high-resolution remote sensing image of any sub-water area is binarized to obtain the near-infrared layer. Based on the red band, the near-infrared layer is removed by masking, and the Ostu binarization segmentation algorithm is used to binarize the masked red band to obtain the red layer. Based on the green band, the near-infrared and red layers are removed by masking, and the Ostu binarization segmentation algorithm is used to binarize the masked green band to obtain the green layer. Based on the blue band, the near-infrared, red, and green layers are removed by masking to obtain the blue layer, until the red, green, and blue layers of each sub-water area are obtained.

[0047] S4. From the preset multiple water depth inversion algorithms, assign a corresponding water depth inversion algorithm to each sub-water area. The water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each adjacent sub-water area. Based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, invert the water depth distribution of the sub-water area to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained.

[0048] S5. When the water depth deviation at each repeated inversion location does not exceed the preset deviation, the water depth distribution of each sub-water area is merged to obtain the water depth distribution of the target water area.

[0049] Since adjacent sub-water areas share an edge, which is the location where inversion is repeated, generally, even if different depth inversion algorithms are used for the two sub-water areas, the deviation between the calculated depths at the same location is not significant. Different depth inversion algorithms can be used to calculate the depth distribution of the same water area, and the depth deviation at each location within the same water area can be calculated. The maximum deviation is taken as the preset deviation. When the depth deviation at each repeatedly inverted location does not exceed the preset deviation, it indicates that there will be no overall deviation in the inverted depth distribution. Then, the depth distributions of all sub-water areas are merged to obtain the depth distribution of the target water area, ensuring the reliability of the inverted depth distribution.

[0050] If the water depth deviation at any location where the inversion is repeated exceeds the preset deviation, an alert will be issued so that the user can adjust the water depth inversion algorithm for each sub-water area until the water depth deviation at each location where the inversion is repeated does not exceed the preset deviation.

[0051] This invention divides the target water area into multiple sub-water areas and performs water depth inversion on each sub-water area, which can improve the inversion speed. Since the deviation between different water depth inversion algorithms calculating the water depth at the same location is small, when the water depth deviation at each location where the inversion is repeated does not exceed the preset deviation, the water depth distribution of each sub-water area is merged to obtain the water depth distribution of the target water area, which can ensure the reliability of the inverted water depth distribution.

[0052] Optionally, in the above technical solution, in step S2, the high-resolution remote sensing image of each sub-water area is preprocessed, including:

[0053] S20. For each sub-water area, perform deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations sequentially on the high-resolution remote sensing image. Specifically:

[0054] 1) The process of deep-water area removal is as follows:

[0055] From the nautical chart data, a depth range of 20 meters or less is extracted as a mask file, and high-resolution remote sensing images of each sub-water area are masked to remove deep water areas.

[0056] 2) The specific implementation process of the radiance conversion operation is as follows:

[0057] The DN values ​​of the high-resolution remote sensing images of each sub-water area after the deep water area removal operation are converted into radiance values.

[0058] 3) The specific implementation process of atmospheric correction is as follows:

[0059] Atmospheric correction was performed on the high-resolution remote sensing images of each sub-water area after deep-water region removal and radiometric conversion operations using FLAASH, dark pixel, or 6S atmospheric correction methods.

[0060] 4) The specific implementation process of solar flare removal is as follows:

[0061] Solar flare removal was performed on high-resolution remote sensing images of each sub-water area after deep-water region removal, radiometric conversion, and atmospheric correction operations, using the median method, mean method, or wavelet method.

[0062] Optionally, in the above technical solution, the preset multiple water depth inversion algorithms include: a Stumpf ratio inversion algorithm based on spectral stratification, a Lyzenga polynomial inversion algorithm based on spectral stratification, an analytical model, a semi-analytical and semi-empirical model, and a statistical model. Specifically:

[0063] Reflectance data in the red, green, and blue bands are obtained from the red, green, and blue light layers of each sub-water area. This data is then combined with the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, analytical models, semi-analytical and semi-empirical models, and statistical models to perform water depth inversion.

[0064] Optionally, the above technical solution also includes:

[0065] S6. Generate an image to characterize the water depth distribution of the target water area according to the preset water depth-color correspondence.

[0066] Specifically, the water depth-color correspondence can be as follows: yellow is used to fill the area with a water depth of 0-3 meters, green is used to fill the area with a water depth of 3-6 meters, and red is used to fill the area with a water depth of 3-9 meters. This generates an image representing the water depth distribution of the target water area. The water depth-color correspondence can be set according to the actual situation, and will not be elaborated here.

[0067] Optionally, the above technical solution also includes:

[0068] S7. Vectorize the image used to characterize the water depth distribution of the target water area to obtain a vector image;

[0069] Extract a portion of the vector image from the vector image according to the user's request and send it to the user's smart terminal.

[0070] If a partial image is directly cropped from an image, the partial image will be a bitmap, which will be distorted when magnified. The image used to represent the water depth distribution of the target water area is vectorized to obtain a vector image. A partial vector image is cropped from the vector image according to the user's requirements and sent to the user's smart terminal. When the user zooms in to view it, there will be no distortion, thus improving the user experience.

[0071] In the above embodiments, although the steps are numbered S1, S2, etc., they are only specific embodiments given in this application. Those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, which is also within the protection scope of this invention. It can be understood that in some embodiments, some or all of the above embodiments may be included.

[0072] like Figure 2 As shown, a shallow water depth inversion system 200 based on high-resolution remote sensing imagery according to an embodiment of the present invention includes a partitioning module 210, a preprocessing module 220, an acquisition module 230, an inversion module 240, and a merging module 250.

[0073] The segmentation module 210 is used to: divide the target water area into multiple sub-water areas, and divide the high-resolution remote sensing image of the target water area to obtain the high-resolution remote sensing image of each sub-water area;

[0074] Preprocessing module 220 is used to: preprocess the high-resolution remote sensing image of each sub-water area;

[0075] The acquisition module 230 is used to: obtain the red light layer, green light layer and blue light layer of each sub-water area based on the processed high-resolution remote sensing image of each sub-water area;

[0076] The inversion module 240 is used to: assign a corresponding water depth inversion algorithm to each sub-water area from a variety of preset water depth inversion algorithms, and the water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each adjacent sub-water area; based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, invert the water depth distribution of the sub-water area to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained;

[0077] The merging module 250 is used to merge the water depth distributions of all sub-water areas to obtain the water depth distribution of the target water area when the water depth deviation of each repeated inversion location does not exceed the preset deviation.

[0078] Dividing the target water area into multiple sub-water areas and performing water depth inversion separately can improve the inversion speed. Since the deviation between different water depth inversion algorithms calculating the water depth at the same location is small, when the water depth deviation at each location where the inversion is repeated does not exceed the preset deviation, the water depth distribution of each sub-water area is merged to obtain the water depth distribution of the target water area, which can ensure the reliability of the inverted water depth distribution.

[0079] Optionally, in the above technical solution, the preprocessing module 220 is specifically used for:

[0080] For each sub-water area, the high-resolution remote sensing image is sequentially subjected to deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations.

[0081] Optionally, in the above technical solution, the preset multiple water depth inversion algorithms include: the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, the analytical model, the semi-analytical and semi-empirical model, and the statistical model.

[0082] Optionally, the above technical solution also includes a generation module;

[0083] The generation module is used to generate an image that represents the water depth distribution of the target water area according to a preset water depth-color correspondence.

[0084] Optionally, the above technical solution also includes a vectorization module and an interception and transmission module;

[0085] The vectorization module is used to: vectorize images used to characterize the water depth distribution of a target water area to obtain vector graphics;

[0086] The capture and send module is used to capture a portion of the vector image from the vector image according to the user's requirements and send it to the user's smart terminal.

[0087] The parameters and steps for implementing the corresponding functions of each unit module in the shallow water depth inversion system 200 based on high-resolution remote sensing images of the present invention can be referred to the parameters and steps in the embodiments of the shallow water depth inversion method based on high-resolution remote sensing images above, and will not be repeated here.

[0088] An electronic device according to an embodiment of the present invention includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps of a shallow water depth inversion method based on high-resolution remote sensing imagery as described above.

[0089] The electronic device can be a computer, mobile phone, etc., and the corresponding program is computer software or mobile APP, etc. The parameters and steps of the above-mentioned electronic device of the present invention can be referred to the parameters and steps in the embodiment of the shallow water depth inversion method based on high resolution remote sensing image above, and will not be repeated here.

[0090] Those skilled in the art will know that this invention can be implemented as a system, method, or computer program product.

[0091] Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product in one or more computer-readable media, the computer-readable medium containing computer-readable program code.

[0092] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0093] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for shallow water depth inversion based on high-resolution remote sensing imagery, characterized in that, include: The target water area is divided into multiple sub-water areas, and the high-resolution remote sensing image of the target water area is divided to obtain the high-resolution remote sensing image of each sub-water area. High-resolution remote sensing images of each sub-water area are preprocessed; Based on the processed high-resolution remote sensing image of each sub-water area, the red, green, and blue light layers of each sub-water area are obtained; From a variety of preset water depth inversion algorithms, a corresponding water depth inversion algorithm is assigned to each sub-water area. The water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each of the adjacent sub-water areas. Based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, the water depth distribution of the sub-water area is inverted to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained. When the water depth deviation at each repeated inversion location does not exceed the preset deviation, the water depth distributions of all sub-water areas are merged to obtain the water depth distribution of the target water area.

2. The shallow water depth inversion method based on high-resolution remote sensing imagery according to claim 1, characterized in that, Preprocessing of high-resolution remote sensing images for each sub-water area includes: For each sub-water area, the high-resolution remote sensing image is sequentially subjected to deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations.

3. The shallow water depth inversion method based on high-resolution remote sensing imagery according to claim 1, characterized in that, The preset water depth inversion algorithms include: the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, analytical models, semi-analytical and semi-empirical models, and statistical models.

4. A shallow water depth inversion method based on high-resolution remote sensing imagery according to any one of claims 1 to 3, characterized in that, Also includes: An image is generated to characterize the water depth distribution of the target water area according to a preset water depth-color correspondence.

5. The shallow water depth inversion method based on high-resolution remote sensing imagery according to claim 4, characterized in that, Also includes: The image used to characterize the water depth distribution of the target water area is vectorized to obtain a vector image. According to the user's request, a partial vector image is extracted from the vector image and sent to the user's smart terminal.

6. A shallow water depth inversion system based on high-resolution remote sensing imagery, characterized in that, It includes a partitioning module, a preprocessing module, an acquisition module, an inversion module, and a merging module; The division module is used to: divide the target water area into multiple sub-water areas, divide the high-resolution remote sensing image of the target water area, and obtain the high-resolution remote sensing image of each sub-water area; The preprocessing module is used to preprocess the high-resolution remote sensing images of each sub-water area; The acquisition module is used to: obtain the red light layer, green light layer and blue light layer of each sub-water area based on the processed high-resolution remote sensing image of each sub-water area; The inversion module is used to: assign a corresponding water depth inversion algorithm to each sub-water area from a variety of preset water depth inversion algorithms, and the water depth inversion algorithm corresponding to any sub-water area is different from the water depth inversion algorithm corresponding to each adjacent sub-water area; based on the water depth inversion algorithm corresponding to any sub-water area, as well as the red light layer, green light layer and blue light layer of the sub-water area, invert the water depth distribution of the sub-water area to obtain the water depth distribution of the sub-water area, until the water depth distribution of each sub-water area is obtained; The merging module is used to merge the water depth distributions of all sub-water areas to obtain the water depth distribution of the target water area when the water depth deviation of each repeated inversion location does not exceed a preset deviation.

7. A shallow water depth inversion system based on high-resolution remote sensing imagery according to claim 6, characterized in that, The preprocessing module is specifically used for: For each sub-water area, the high-resolution remote sensing image is sequentially subjected to deep water region removal, radiometric conversion, atmospheric correction, and solar flare removal operations.

8. A shallow water depth inversion system based on high-resolution remote sensing imagery according to claim 6, characterized in that, The preset water depth inversion algorithms include: the Stumpf ratio inversion algorithm based on spectral stratification, the Lyzenga polynomial inversion algorithm based on spectral stratification, analytical models, semi-analytical and semi-empirical models, and statistical models.

9. A shallow water depth inversion system based on high-resolution remote sensing imagery according to any one of claims 6 to 8, characterized in that, It also includes a generation module; The generation module is used to generate an image that characterizes the water depth distribution of the target water area according to a preset water depth-color correspondence.

10. A shallow water depth inversion system based on high-resolution remote sensing imagery according to claim 9, characterized in that, It also includes a vectorization module and an interception and transmission module; The vectorization module is used to: vectorize the image used to characterize the water depth distribution of the target water area to obtain a vector image; The capture and send module is used to: capture a partial vector image from the vector image according to the user's requirements and send it to the user's smart terminal.

Images