US-20260127707-A1 - SERVER AND METHOD FOR SUPER-RESOLUTION AND SYSTEM INCLUDING THE SAME

Abstract

The present invention relates to a server and method for super-resolution that may vary a super-resolution method for video data (e.g., satellite image, aerial video, drone video, etc.) according to a user's request, and a system including the same. The super-resolution server may include a data collection module that receives video data and requirement information related to the user's needs for the video data, a super-resolution module that super-resolves the video data according to the requirement information to generate a high-resolution satellite image, and an output module that outputs the high-resolution satellite image and reliability information on the high-resolution satellite image.

Inventors

• HYUN SUN PARK
• Young Ju Lee
• Yeo Wool LEE
• Yong Hyub Sakong
• Dong Chul Kim
• Ah Rom Goo
• Myung Hoon Kang

Assignees

• MEISSA INC.

Dates

Publication Date

20260507

Application Date

20250312

Priority Date

20241104

Claims (20)

1. 1 . A super-resolution server, comprising: a data collection module that receives video data and requirement information related to a user's needs for the video data; a super-resolution module that super-resolves the video data according to the requirement information to generate a high-resolution satellite image; and an output module that outputs the high-resolution satellite image and reliability information on the high-resolution satellite image.
2. 2 . The super-resolution server of claim 1 , wherein the data collection module receives the video data from an external database that stores and manages the video data and receives the requirement information from a user terminal for the user.
3. 3 . The super-resolution server of claim 1 , wherein the requirement information includes coordinate information related to a coordinate area that a user wants to analyze and purpose information related to a purpose that the user wants to achieve through the high-resolution satellite image.
4. 4 . The super-resolution server of claim 3 , wherein the purpose information includes simple super-resolution that means only super-resolution of the video data and a selection of the user of one of special analyses that refers to specific data analysis through the video data.
5. 5 . The super-resolution server of claim 4 , wherein the super-resolution module includes: an object segmentation unit that segments an object included in the video data to generate a segmentation result for the corresponding video data; a method determination unit that determines a super-resolution method which is a method of performing the super-resolution based on the segmentation result and the requirement information; and a generation unit that super-resolves the video data according to the determined super-resolution method to generate the high-resolution satellite image.
6. 6 . The super-resolution server of claim 5 , wherein the object segmentation unit segments the object using a segmentation model trained in advance based on a neural network to generate the segmentation result.
7. 7 . The super-resolution server of claim 6 , wherein the segmentation model includes a semantic segmentation model.
8. 8 . The super-resolution server of claim 5 , wherein the method determination unit determines one of a first method based on up-scaling and a second method based on a high-resolution model using a neural network to be the super-resolution method, and the high-resolution model includes a generative artificial intelligence model.
9. 9 . The super-resolution server of claim 8 , wherein the method determination unit determines the super-resolution method based on the purpose information included in the requirement information.
10. 10 . The super-resolution server of claim 9 , wherein when the purpose information constitutes the simple super-resolution, the method determination unit determines the second method to be the super-resolution method.
11. 11 . The super-resolution server of claim 9 , wherein, when the purpose information constitutes object analysis among the special analyses, the method determination unit determines the second method to be the super-resolution method.
12. 12 . The super-resolution server of claim 9 , wherein when the purpose information constitutes area analysis or band analysis for a specific target from among the special analyses, the method determination unit determines a result of combining the first method and the second method to be the super-resolution method.
13. 13 . The super-resolution server of claim 12 , wherein the method determination unit determines the first method to be the super-resolution method for some of a plurality of regions included in the segmentation result, and determines the second method to be the super-resolution method for some regions other than the some of the plurality of regions.
14. 14 . The super-resolution server of claim 13 , wherein the method determination unit determines a region of interest from among the plurality of regions included in the segmentation result based on the specific target, determines the first method to be the super-resolution method for the determined region of interest, and determines the second method to be the super-resolution method for other regions excluding the region of interest.
15. 15 . The super-resolution server of claim 14 , wherein when the specific object is a road and a type of the special analysis is area analysis for the road, the method determination unit determines a region including the road to be the region of interest, determines the first method to be the super-resolution method for the region of interest including the road, and determines the second method to be the super-resolution method for other regions excluding the road.
16. 16 . The super-resolution server of claim 14 , wherein when the specific target is vegetation and a type of the special analysis is band analysis for the vegetation, the method determination unit determines a region including the vegetation to be the region of interest, determines the first method to be the super-resolution method for the region of interest including the vegetation, and determines the second method to be the super-resolution method for other regions excluding the vegetation.
17. 17 . The super-resolution server of claim 1 , wherein the output module generates the reliability information based on a difference between the video data and the high-resolution satellite image.
18. 18 . The super-resolution server of claim 17 , wherein the output module compares the video data with the high-resolution satellite image to generate as the reliability information a probability of correspondence between an object included in the video data and the object included in the high-resolution satellite image.
19. 19 . A super-resolution server, comprising: a memory that stores at least one instruction; and at least one processor that executes the at least one instruction, wherein the processor receives video data and requirement information related to a user's need for the video data, super-resolves the video data according to the requirement information to generate a high-resolution satellite image, and outputs the high-resolution satellite image and reliability information on the high-resolution satellite image.
20. 20 . A super-resolution system, comprising: an external database that stores video data; a super-resolution server that communicates with the external database to receive the video data; a user terminal that transmits requirement information related to a user's needs for the video data to the super-resolution server; and a communication network that performs communication between the external database, a user terminal, and the super-resolution server, wherein the super-resolution server includes: a memory storing at least one instruction, and at least one processor that executes the at least one instruction, and the processor receives the video data and the requirement information, super-resolves the video data according to the requirement information to generate a high-resolution satellite image, and outputs the high-resolution satellite image and reliability information on the high-resolution satellite image.

Description

CROSS-REFERENCE TO RELATED APPLICATION This application claims priority to and the benefit of Korean Patent Application No. 10-2024-0153964, filed on Nov. 4, 2024, the disclosure of which is incorporated herein by reference in its entirety. BACKGROUND 1. Field of the Invention The present invention relates to a server and method for super-resolution and a system including the same. More particularly, the present invention relates to a server and method for super-resolution that may vary a super-resolution method for video data (e.g., a satellite image, aerial video, drone video, etc.) according to a user's request and a system including the same. 2. Discussion of Background Art The contents described in this Background Art merely provide background information with respect to the present embodiment and do not constitute the related art. Recently, video data, such as satellite images, aerial images, and drone images, are being utilized to acquire information on buildings, roads, nature, etc. Such video data is being utilized in various ways, such as detecting the possibility of forest fires and determining a vegetation index. In this case, since a satellite image is captured from a high altitude above the ground, there may be cases where data analysis is not made easy due to low resolution when performing the data analysis using the satellite image. In this case, super-resolution, which involves a task of increasing the resolution of the satellite image, is performed. However, in general, when super-resolution of the satellite image is performed, only the post-processing of the known method is performed in a batch, and no technological development is being made for performing super-resolution in a manner that matches the user's needs. Accordingly, there is a sufficient need for super-resolution-related technology that reflects user requirements. SUMMARY OF THE INVENTION The present invention is directed to providing a server and method for super-resolution that can vary the super-resolution method according to a user's request, and a system including the same. More specifically, the present invention is directed to providing a server and method for super-resolution that can vary the super-resolution method depending on whether user requirements are simple super-resolution, object analysis, area analysis, or band analysis to ensure both reliability of the super-resolution results and visibility of the super-resolution effects, and a system including the same. In addition, the present invention is directed to providing a server and method for super-resolution capable of additionally displaying object reliability according to super-resolution to enable users to secure reliability in super-resolution results, and a system including the same. Objects of the present disclosure are not limited to the above-described objects, and other objects and advantages of the present disclosure that are not described may be understood by the following description and will be more clearly appreciated by exemplary embodiments of the present disclosure. In addition, it may be easily appreciated that aspects and advantages of the present disclosure may be realized by means mentioned in the claims and a combination thereof. According to an aspect of the present invention, there is provided a super-resolution server, including a data collection module that receives video data and requirement information related to user's needs for the video data, a super-resolution module that super-resolves the video data according to the requirement information to generate a high-resolution satellite image and an output module that outputs a high-resolution satellite image and reliability information related to the high-resolution satellite image. The data collection module may receive the video data from an external database that stores and manages the video data and receive the requirement information from a user terminal for the user. The requirement information may include coordinate information related to a coordinate area that a user wants to analyze and purpose information related to a purpose that the user wants to achieve through the high-resolution satellite image. The purpose information may include simple super-resolution that refers to only super-resolution of the video data and a selection of the user of one of the special analyses that refers to specific data analysis through the video data. The super-resolution module may include an object segmentation unit that segments an object included in the video data to generate a segmentation result for the corresponding video data, a method determination unit that determines a super-resolution method which is a method of performing the super-resolution based on the segmentation result and the requirement information, and a generation unit that super-resolves the video data according to the determined super-resolution method to generate the high-resolution satellite image. The object segmen