An image enhancement processing method and system for submarine cable inspection

Abstract

The application provides an image enhancement processing method and system for submarine cable inspection, and belongs to the technical field of image processing, and specifically comprises the following steps: dividing the submarine cable into multiple regions by using the damaged position; determining a recognition processing strategy for image enhancement processing of the regions by using a preset scheme based on the damaged position data of the submarine cable in the later inspection of the regions; performing image enhancement processing of the regions by using an unmanned robot based on the recognition processing strategy and image feature detection results; and determining the regions for image enhancement processing in the later inspection of the regions by using the preset scheme based on the image enhancement processing data of the unmanned robot, so that the efficiency of the inspection processing is improved.

Description

Technical Field

[0001] This invention belongs to the field of image processing technology, and in particular relates to an image enhancement processing method and system for submarine cable inspection. Background Technology

[0002] To achieve the inspection and handling of submarine cables, existing technical solutions often employ robots for inspection. Specific technical solutions are presented in invention patent application CN202510218204.0, "A Method and System for Underwater Robotic Submarine Cable Inspection Based on Two-Dimensional Image Sonar." However, these solutions have the following drawbacks:

[0003] Submarine cable inspection images are subject to numerous interference factors. To ensure the accuracy of fault and defect identification in submarine cable inspection images, image enhancement processing is necessary. Therefore, how to perform adaptive image enhancement processing based on the distribution of damage locations in submarine cables and the detection data of image features, while reducing the power consumption of unmanned robots and improving the reliability of defect feature identification processing, has become an urgent technical problem to be solved.

[0004] To address the aforementioned technical problems, this application specifically provides an image enhancement processing method and system for submarine cable inspection. Summary of the Invention

[0005] To achieve the objectives of this invention, the following technical solution is adopted:

[0006] Specifically, this application provides an image enhancement processing method for submarine cable inspection, which includes:

[0007] S1 determines the partial discharge risk of the submarine cable to meet the requirements based on the load operation data of the submarine cable, and determines the distribution of the damaged locations of the submarine cable based on the inspection data. If it is determined that the unmanned robot cannot use the preset scheme for image enhancement processing throughout the entire process based on the distribution of the damaged locations, proceed to the next step.

[0008] S2 divides the submarine cable into multiple regions based on the location of the damage. Based on the damage location data of the submarine cable during subsequent inspections of the regions, a recognition processing strategy for image enhancement processing of the regions using a preset scheme is determined.

[0009] S3 performs image enhancement processing on the unmanned robot based on the recognition and processing strategy and the image feature detection results. Based on the image enhancement processing data of the unmanned robot, it determines the areas in the later region that will be image enhanced using a preset scheme.

[0010] The beneficial effects of this invention are as follows:

[0011] Based on the data of damaged submarine cables from later inspections of the region, an identification and processing strategy is determined for image enhancement processing of the region using a preset scheme. This avoids the impact on the battery power of the unmanned robot caused by the excessive time required for image enhancement processing at the current moment when there are many damaged locations. At the same time, the reliability of image enhancement processing in the region is also ensured by combining image clarity and image features.

[0012] Based on the image enhancement data of the unmanned robot, the areas to be image enhanced using a preset scheme are determined in the later stages. This enables the assessment of the degree of dirtiness of the unmanned robot by analyzing the changes in inspection time caused by poor image clarity when using the preset scheme for image enhancement. It also enables the determination of areas to be image enhanced using the preset scheme based on both the degree of dirtiness and the remaining battery power, thus ensuring the reliability of the inspection results.

[0013] Furthermore, the load operation data includes the power transmitted by the submarine cable and line loss data.

[0014] Furthermore, it was determined that the partial discharge risk of the submarine cable met the requirements, specifically including:

[0015] The power transmission capacity of the submarine cable is determined based on the load operation data of the submarine cable.

[0016] Based on line loss data under different transmitted power levels, it is determined whether the partial discharge risk of the submarine cable meets the requirements.

[0017] Furthermore, the method for determining the region in the later stage that undergoes image enhancement processing using a preset scheme is as follows:

[0018] Using inspection data that has undergone image enhancement processing with a preset scheme, the composition data of the inspection duration of the image enhancement processing with the preset scheme in different inspection periods is determined. The composition data is used to determine the inspection duration of the image enhancement processing with the preset scheme due to poor image clarity in different inspection periods, and the duration of the image enhancement processing due to the image clarity is determined.

[0019] Based on the changes in the duration of the clarity impact between the inspection period and the previous inspection period, the inspection period in which the duration of the clarity impact increases compared to the previous inspection period is determined and is taken as the additional inspection period;

[0020] Based on the remaining battery power of the unmanned robot and the composition data of the increased inspection period, the areas in the later stage will be determined to undergo image enhancement processing using a preset scheme.

[0021] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described image enhancement processing method for submarine cable inspection when running the computer program.

[0022] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0023] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0024] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0025] Figure 1 This is a flowchart of image enhancement processing for submarine cable inspection;

[0026] Figure 2 This is a flowchart for determining whether the partial discharge risk of submarine cables meets the requirements;

[0027] Figure 3 It is a flowchart of a method for determining a recognition processing strategy for image enhancement processing of a region using a preset scheme;

[0028] Figure 4 It is a framework diagram of a computer system. Detailed Implementation

[0029] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0030] Example 1

[0031] like Figure 1 As shown, this application provides an image enhancement processing method for submarine cable inspection, specifically including:

[0032] S1 determines the partial discharge risk of the submarine cable to meet the requirements based on the load operation data of the submarine cable, and determines the distribution of the damaged locations of the submarine cable based on the inspection data. If it is determined that the unmanned robot cannot use the preset scheme for image enhancement processing throughout the entire process based on the distribution of the damaged locations, proceed to the next step.

[0033] Furthermore, the load operation data includes the power transmitted by the submarine cable and line loss data.

[0034] Specifically, such as Figure 2 As shown, the partial discharge risk of the submarine cable is determined to meet the requirements, specifically including:

[0035] The power transmission capacity of the submarine cable is determined based on the load operation data of the submarine cable.

[0036] Based on line loss data under different transmitted power levels, it is determined whether the partial discharge risk of the submarine cable meets the requirements.

[0037] It is understandable that when the line loss rate of the submarine cable is high under different transmission power, it indicates that the submarine cable is at risk of a high line loss rate due to external damage. Therefore, it is determined that the partial discharge risk of the submarine cable does not meet the requirements.

[0038] It should be noted that when the partial discharge risk of the submarine cable does not meet the requirements, a preset scheme is used for image enhancement processing throughout the entire submarine cable. Specifically, the images collected by the unmanned robot are transmitted to a remote platform for image enhancement and cable damage identification processing.

[0039] In one possible embodiment, when the submarine cable transmits power with a line loss rate greater than 7%, that is, when the line loss rate under the transmitted power is greater than 7%, it is determined that the partial discharge risk of the submarine cable does not meet the requirements.

[0040] Optionally, determining that the partial discharge risk of the submarine cable meets the requirements specifically includes:

[0041] The power transmission capacity of the submarine cable is determined based on the load operation data of the submarine cable.

[0042] Based on the line loss data under different transmission volumes, determine the average line loss rate under different transmission volumes;

[0043] Based on the average line loss rate under different transmitted power, it is determined whether the partial discharge risk of the submarine cable meets the requirements.

[0044] It is understandable that when the average line loss rate under different transmitted power is not up to standard, i.e., too high, the partial discharge risk of the submarine cable is determined to be unsatisfactory.

[0045] Furthermore, the location of the damaged submarine cable is determined based on the historical inspection data of the unmanned robot, specifically based on the image recognition results of the unmanned robot during the historical inspection process.

[0046] Furthermore, it was determined that the unmanned robot could not perform image enhancement processing using a pre-set scheme throughout the entire process, specifically including:

[0047] Based on the distribution of the damaged locations, the distance between the damaged locations is determined;

[0048] The maximum interval distance is determined based on the maximum distance between the damaged locations;

[0049] Using the maximum interval distance and the power consumption of image enhancement processing using the preset scheme throughout the process, it is determined whether the unmanned robot is unable to perform image enhancement processing using the preset scheme throughout the process.

[0050] It is understood that the power consumption of image enhancement processing using the preset scheme throughout the process is determined based on the length of the submarine cable. Specifically, it is determined based on the power consumption of the unmanned robot inspecting the submarine cable of the specified length. It is understood that the power consumption can be determined by multiplying the average power consumption of the unmanned robot inspecting a 1m submarine cable using the preset scheme with the specified length.

[0051] It is understandable that if the power consumption of the unmanned robot in performing image enhancement processing using the preset scheme is greater than the power storage capacity of the unmanned robot, then it is determined that the unmanned robot cannot perform image enhancement processing using the preset scheme.

[0052] It should also be noted that when the power consumption of the unmanned robot in performing image enhancement processing using the preset scheme throughout the entire process is not greater than the power storage capacity of the unmanned robot, and the difference between the power storage capacity of the unmanned robot and the power consumption of the unmanned robot in performing image enhancement processing using the preset scheme throughout the entire process is greater than the preset power threshold, it is determined that the unmanned robot can perform image enhancement processing using the preset scheme throughout the entire process. In one possible embodiment, the preset power threshold is determined based on the length of the submarine cable, specifically based on the power consumption of performing image enhancement processing using the preset scheme with 0.1 times the length of the submarine cable.

[0053] When the difference between the stored power of the unmanned robot and the power consumption of the unmanned robot for image enhancement processing using the preset scheme throughout the process is not greater than the preset power threshold, and when the maximum interval distance does not meet the requirements, the distribution of the damaged locations is relatively discrete. Therefore, if the preset scheme is used for image enhancement processing throughout the process, the robot needs to pause at the inspection location before obtaining the image enhancement and cable damage identification results from the remote platform. Thus, it is determined that the unmanned robot cannot use the preset scheme for image enhancement processing throughout the process. In other cases, the preset scheme can be used for image enhancement processing throughout the process.

[0054] In one possible embodiment, if the maximum spacing distance is greater than three-quarters of the length of the submarine cable, then the maximum spacing distance is determined to be non-compliant.

[0055] Optionally, it can be determined that the unmanned robot cannot perform image enhancement processing using a pre-set scheme throughout the process, specifically including:

[0056] Based on the distribution of the damaged locations, the distribution location of the damaged locations is determined;

[0057] Based on the distribution of the damaged locations, the number of damaged locations in different sections of the submarine cable is determined;

[0058] By using the number of damaged locations in different sections of the submarine cable and the power consumption of image enhancement processing using a preset scheme throughout the process, it can be determined whether the unmanned robot is unable to perform image enhancement processing using the preset scheme throughout the process.

[0059] It should be noted that the intervals are divided according to unit length. Specifically, the submarine cable is divided into 20 intervals at equal intervals. When there are damaged locations in different intervals and the difference between the energy stored in the unmanned robot and the energy consumed by the unmanned robot to perform image enhancement processing using the preset scheme throughout the process is not greater than the preset energy threshold, it is determined that the unmanned robot cannot perform image enhancement processing using the preset scheme throughout the process.

[0060] S2 divides the submarine cable into multiple regions based on the location of the damage. Based on the damage location data of the submarine cable during subsequent inspections of the regions, a recognition processing strategy for image enhancement processing of the regions using a preset scheme is determined.

[0061] Furthermore, the submarine cable is divided into multiple zones, specifically including:

[0062] Submarine cables between adjacent damaged locations are classified as the same area.

[0063] Specifically, such as Figure 3As shown, the method for determining the recognition processing strategy for image enhancement processing of the region using a preset scheme is as follows:

[0064] Based on the data on the location of damage to submarine cables during subsequent inspections in the area, the number of locations of damage to submarine cables during subsequent inspections in the area is determined.

[0065] Based on the number of damaged locations of submarine cables identified during subsequent inspections in the area, a recognition processing strategy for image enhancement processing of the area using a preset scheme is determined.

[0066] It is understandable that the number of damaged locations of submarine cables in the later inspection of the area is determined based on the number of damaged locations of submarine cables that need to be inspected in the later inspection of submarine cables in the area.

[0067] It should be noted that when the number of damaged locations of submarine cables in the later inspection of the area is large, the image enhancement processing using the preset scheme in the area may result in insufficient power at the damaged locations of the submarine cables in the later inspection. Therefore, image enhancement processing is only required according to the preset scheme when there are specific image feature detection results. Specifically, when the proportion of the number of damaged locations of submarine cables in the later inspection to the total number of damaged locations is greater than 0.9, it is determined that the number of damaged locations of submarine cables in the later inspection of the area is large.

[0068] Furthermore, it is understood that when the number of damaged locations of submarine cables during the later inspections of the area is not large, in one possible embodiment, when the number of damaged locations is within a preset range, image enhancement processing of the monitoring images is performed using an unmanned robot according to a preset cycle. Image enhancement processing is only required according to a preset scheme when the difference between the image clarity after image enhancement processing and the image clarity before enhancement processing is greater than a preset clarity threshold or when there are specific image feature detection results.

[0069] It should be noted that when the proportion of the number of damaged locations to the total number of damaged locations is between 0.3 and 0.9, the number of damaged locations is determined to be within the preset range. Image clarity is determined using the signal-to-noise ratio (SNR). When the deviation rate between the SNR after image enhancement and the SNR before enhancement is greater than 0.2, that is, when the ratio of the deviation to the SNR after enhancement is greater than 0.2, it is determined to be greater than the preset clarity threshold.

[0070] It should be noted that the image enhancement processing of the monitoring images by the unmanned robot is determined by mean filtering, median filtering or sharpening filtering. The image enhancement of the remote platform is performed by using a convolutional neural network (CNN) to construct an end-to-end learning mapping function to perform image enhancement processing. That is, the monitoring images acquired by the unmanned robot are used as input to the convolutional neural network, and the enhanced image is determined based on the output results.

[0071] Additionally, it is understandable that when the number of damaged locations is not within the preset range, if the remaining power of the unmanned robot is sufficient (i.e., the remaining power is sufficient for the inspection of 1.5 times the length of the remaining cable), then the preset scheme is used for image enhancement processing. In other cases, if the remaining power is sufficient for the inspection of less than 1 times the length of the remaining cable, then the preset scheme is used only for image enhancement processing at the damaged locations. However, when the power is between 1 and 1.5 times the length of the cable, the unmanned robot is used to perform image enhancement processing on the monitored images according to the second preset time period. Image enhancement processing is only required according to the preset scheme when the difference between the image clarity after enhancement processing and the image clarity before enhancement processing is greater than the preset clarity threshold or when there are specific image feature detection results.

[0072] It should be noted that the second preset time period is less than the preset time period, and when the difference between the image clarity after image enhancement and the image clarity before enhancement is not greater than the preset clarity threshold, the image enhancement process of the monitored image continues in the area according to the original time period. In one possible embodiment, the second preset time period is 0.7 times the preset time period, wherein the preset time period is between 30 seconds and 1 minute, and the specific time period is determined according to the user's settings.

[0073] Specifically, the specific image feature detection result refers to the image features when the submarine cable is damaged. It is determined based on the image features of the submarine cable's outer shell that were detected by the unmanned robot during historical inspections, and can be determined using texture features.

[0074] S3 performs image enhancement processing on the unmanned robot based on the recognition and processing strategy and the image feature detection results. Based on the image enhancement processing data of the unmanned robot, it determines the areas in the later region that will be image enhanced using a preset scheme.

[0075] Furthermore, image enhancement processing is performed on the unmanned robot, specifically including:

[0076] Image enhancement is only required when the difference between the image sharpness after enhancement and the image sharpness before enhancement exceeds a preset sharpness threshold, or when specific image feature detection results are present.

[0077] Furthermore, the method for determining the region in the later stage that undergoes image enhancement processing using a preset scheme is as follows:

[0078] Based on the inspection data that has undergone image enhancement processing using a preset scheme, determine the inspection duration for image enhancement processing using the preset scheme;

[0079] Using inspection data that has undergone image enhancement processing with a preset scheme, determine the composition data of the inspection duration that has undergone image enhancement processing with a preset scheme in different inspection periods;

[0080] Based on the remaining battery power of the unmanned robot, the inspection time using the preset scheme for image enhancement processing, and the composition data of the inspection time using the preset scheme for image enhancement processing in different inspection periods, the areas in the later stage will be determined to use the preset scheme for image enhancement processing.

[0081] Understandably, if the remaining power of the unmanned robot meets the requirements, that is, if the remaining power can meet the power requirements for inspection of 1.5 times the length of the remaining cable, then the preset scheme will be used for image enhancement processing in the later areas.

[0082] If the remaining battery power of the unmanned robot is low, and the inspection time using the preset image enhancement scheme meets the requirements (i.e., the difference between the image clarity after enhancement and the image clarity before enhancement is greater than the preset clarity threshold, meaning the proportion of the inspection time using the preset scheme due to poor image clarity is less than 0.05% of the existing inspection time), then the unmanned robot does not face the risk of camera contamination. Therefore, if the remaining battery power is sufficient for inspections of less than one time the length of the remaining cable, the preset scheme will only be used for image enhancement at the damaged location. If the remaining battery power is sufficient for inspections of one to 1.5 times the length of the remaining cable, then image enhancement will only be performed according to the preset scheme if the difference between the image clarity after enhancement and the image clarity before enhancement is greater than the preset clarity threshold or if specific image feature detection results are present.

[0083] If the inspection time using the preset image enhancement scheme does not meet the requirements, and the proportion of the inspection time using the preset scheme due to poor image clarity is between 0.05 and 0.1% of the total inspection time, there is a risk of contamination. If the proportion of the inspection time using the preset scheme for image enhancement gradually increases in different inspection periods (i.e., the inspection time in each period is longer than the inspection time in the previous period due to poor image clarity), then the preset scheme will be used for image enhancement in all subsequent areas. In other cases, if the remaining power is sufficient for inspections of less than 1 times the length of the remaining cable, the preset scheme will only be used for image enhancement at the damaged location. If the remaining power is sufficient for inspections of 1 to 1.5 times the length of the remaining cable, then image enhancement will only be performed according to the preset scheme if the difference between the image clarity after enhancement and the image clarity before enhancement exceeds the preset clarity threshold or if specific image feature detection results are present.

[0084] If the inspection time using the preset scheme for image enhancement does not meet the requirements, and the proportion of the inspection time using the preset scheme for image enhancement due to poor image clarity is greater than 0.1% of the existing inspection time, then the preset scheme will be used for image enhancement in all subsequent areas. When the power is insufficient, a new unmanned robot will be used to continue the inspection of the submarine cables that have not yet been inspected.

[0085] Specifically, the inspection period is divided into units of time, with 10-minute intervals as the basis for dividing the inspection period.

[0086] Furthermore, the method for determining the region in the later stage that undergoes image enhancement processing using a preset scheme is as follows:

[0087] Using inspection data that has undergone image enhancement processing with a preset scheme, the composition data of the inspection duration of the image enhancement processing with the preset scheme in different inspection periods is determined. The composition data is used to determine the inspection duration of the image enhancement processing with the preset scheme due to poor image clarity in different inspection periods, and the duration of the image enhancement processing due to the image clarity is determined.

[0088] Based on the changes in the duration of the clarity impact between the inspection period and the previous inspection period, the inspection period in which the duration of the clarity impact increases compared to the previous inspection period is determined and is taken as the additional inspection period;

[0089] Based on the remaining battery power of the unmanned robot and the composition data of the increased inspection period, the areas in the later stage will be determined to undergo image enhancement processing using a preset scheme.

[0090] It is understandable that when the number of additional inspection periods does not meet the requirements, the preset scheme will be used for image enhancement processing in all subsequent areas. In one possible embodiment, when the number of additional inspection periods is more than four, it is determined that the number of additional inspection periods does not meet the requirements.

[0091] If the number of inspection periods meets the requirements, and if the remaining power of the unmanned robot meets the requirements (i.e., the remaining power can meet the power requirements for inspection of 1.5 times the length of the remaining cable), then the preset scheme will be used for image enhancement processing in all subsequent areas.

[0092] It should be noted that the power required for inspecting the remaining cable length, i.e. the power required for the length of the submarine cable that has not yet been inspected, is specifically determined by multiplying the average power consumption of the unmanned robot inspecting 1m of submarine cable by the length of the uninspected submarine cable.

[0093] If the remaining power is sufficient to cover the inspection needs of less than 1 times the length of the remaining cable, then image enhancement processing will only be performed at the damaged location using the preset scheme. If the remaining power is sufficient to cover the inspection needs of 1 to 1.5 times the length of the remaining cable, then image enhancement processing will only be performed according to the preset scheme if the difference between the image clarity after enhancement and the image clarity before enhancement exceeds the preset clarity threshold or if there are specific image feature detection results.

[0094] Example 2

[0095] Secondly, such as Figure 4 As shown, the present invention provides a computer system, including: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described image enhancement processing method for submarine cable inspection when running the computer program.

[0096] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0097] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0098] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. An image enhancement processing method for submarine cable inspection, characterized in that, Specifically, it includes: Based on the load operation data of the submarine cable, when it is determined that the partial discharge risk of the submarine cable meets the requirements, the distribution of the damaged locations of the submarine cable is determined based on the inspection data. When it is determined that the unmanned robot cannot use the preset scheme for image enhancement processing throughout the entire process based on the distribution of the damaged locations, proceed to the next step. The submarine cable is divided into multiple regions based on the location of the damage. Based on the damage location data of the submarine cable during subsequent inspections of the regions, an image enhancement processing strategy is determined for each region. Based on the aforementioned recognition and processing strategy and image feature detection results, image enhancement processing is performed on the unmanned robot. Based on the image enhancement processing data of the unmanned robot, the regions in the subsequent areas to be image enhanced using a preset scheme are determined. Image enhancement processing is performed using a preset scheme. Specifically, the images collected by the unmanned robot are transmitted to a remote platform for image enhancement and cable damage identification. The remote platform uses a convolutional neural network (CNN) to construct an end-to-end learning mapping function for image enhancement. That is, the monitoring images acquired by the unmanned robot are used as input to the convolutional neural network, and the enhanced image is determined based on the output results.

2. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, The load operation data includes the power transmitted by the submarine cable and the line loss data.

3. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, Determining that the partial discharge risk of the submarine cable meets the requirements specifically includes: The power transmission capacity of the submarine cable is determined based on the load operation data of the submarine cable. Based on line loss data under different transmitted power levels, it is determined whether the partial discharge risk of the submarine cable meets the requirements.

4. The image enhancement processing method for submarine cable inspection as described in claim 3, characterized in that, When the partial discharge risk of the submarine cable does not meet the requirements, the image enhancement processing is performed using a preset scheme throughout the entire length of the submarine cable.

5. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, The location of the damaged submarine cable is determined based on the historical inspection data of the unmanned robot, specifically based on the image recognition results of the unmanned robot during the historical inspection process.

6. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, The submarine cable is divided into multiple zones, specifically including: Submarine cables between adjacent damaged locations are classified as the same area.

7. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, The method for determining the recognition processing strategy for image enhancement processing of the region using a preset scheme is as follows: Based on the data on the location of damage to submarine cables during subsequent inspections in the area, the number of locations of damage to submarine cables during subsequent inspections in the area is determined. Based on the number of damaged locations of submarine cables identified during subsequent inspections in the area, a recognition processing strategy for image enhancement processing of the area using a preset scheme is determined.

8. The image enhancement processing method for submarine cable inspection as described in claim 7, characterized in that, The number of damaged locations of submarine cables to be inspected in the later stages of the inspection in the area is determined based on the number of damaged locations of submarine cables to be inspected in the later stages of the inspection in the area.

9. The image enhancement processing method for submarine cable inspection as described in claim 1, characterized in that, The method for determining the region in the later stage that undergoes image enhancement processing using a preset scheme is as follows: Based on the inspection data that has undergone image enhancement processing using a preset scheme, determine the inspection duration for image enhancement processing using the preset scheme; Using inspection data that has undergone image enhancement processing with a preset scheme, determine the composition data of the inspection duration that has undergone image enhancement processing with a preset scheme in different inspection periods; Based on the remaining battery power of the unmanned robot, the inspection time using the preset scheme for image enhancement processing, and the composition data of the inspection time using the preset scheme for image enhancement processing in different inspection periods, the areas in the later stage will be determined to use the preset scheme for image enhancement processing.

10. A computer system, comprising: A memory and processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that, when the processor runs the computer program, it executes an image enhancement processing method for submarine cable inspection as described in any one of claims 1-9.

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