SAR Image Pixel Association via Phase Correlation and Shape Similarity
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Solution Overview
Problem
Current synthetic aperture radar (SAR) image analysis systems face challenges in accurately associating pixels with geospatial information due to distortion issues and the need for manual data acquisition, particularly when using existing ortho-correction methods, which can leave errors and make it difficult to integrate SAR images with geographical data.
Innovation Solution
A system that determines phase correlation and shape similarity between SAR image pixels and geospatial objects, enabling automatic association of pixels with objects using phase correlation determination, shape determination, and association processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If ortho-correction is performed using known elevation data (DEM), then the distortion of geographical space in the SAR image is roughly corrected, but distortion due to DEM errors remains and large distortion relating to buildings not normally recorded in DEM will remain
Solution Approach 1:
The patent changes the parameter basis for correction from DEM elevation data to actual SAR image phase information. By using the phase difference between multiple SAR images and comparing it with the phase difference expected from geospatial information, the system directly measures and corrects distortion based on actual observed data rather than modeled data, thereby eliminating DEM-related errors and building distortion issues
Solution Approach 2:
The patent replaces the mechanical DEM-based correction system with a phase-correlation-based correction system. Instead of relying on physical elevation models, the system uses electromagnetic wave phase information from SAR images to detect and correct distortion, substituting a more accurate measurement-based approach for the less accurate model-based approach
2Manufacturing precision
If ortho-correction apparatus is used, then the distortion of geographical space is corrected, but information regarding the reflection of electromagnetic waves of each object recorded in geospatial information must be manually acquired from the SAR image
Solution Approach 1:
The system performs self-service by automatically extracting object information from SAR image phases during the distortion correction process itself. The phase correlation analysis that corrects distortion also automatically identifies objects and their electromagnetic wave reflection characteristics, eliminating the need for separate manual acquisition operations
Solution Approach 2:
The patent merges the distortion correction process with the object information extraction process. By combining phase correlation determination, shape determination, and association operations into a single integrated workflow, the system simultaneously achieves geographical space correction and automatic object information acquisition, eliminating manual operations
3Ease of operation
If SAR image pixels are associated with geospatial information by simply superimposing, then the process is simple, but the association is difficult due to remaining distortion
Solution Approach 1:
The patent introduces phase correlation strength and shape similarity degree as intermediary parameters between SAR image pixels and geospatial objects. These intermediaries provide quantitative criteria for association, bridging the gap between distorted SAR image space and accurate geospatial information space, enabling precise automatic association without simple superimposition
4Measurement precision
If manual acquisition of electromagnetic wave reflection information is performed, then accurate object information can be obtained, but the operation is complicated
Solution Approach 1:
The system performs self-service by automatically extracting object information during the phase correlation analysis. The same computational processes that determine phase correlation strength and shape similarity also automatically identify objects and their electromagnetic wave reflection characteristics, eliminating manual acquisition operations while maintaining accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient and accurate association of SAR image pixels with geospatial information, reducing manual effort and minimizing distortion errors, thereby improving the integration of SAR images with geographical data.
Implementation Method 1
synthetic aperture radar is a technology that obliquely irradiates electromagnetic waves from the sky to the ground by satellites and airplanes, and observes the state of the ground surface by imaging reflected waves from the ground surface against the electromagnetic waves
Implementation Method 2
a phase correlation determination means which determines a strength of the phase correlation between a plurality of pixels in an image selected from among a plurality of images on the basis of the plurality of images that have been photographed by a synthetic aperture radar
Data Source
AI summary
A synthetic aperture radar image analysis system 20 includes: a phase correlation determination means 21 which determines a strength of the phase correlation between a plurality of pixels in an image selected from among a plurality of images on the basis of the plurality of images that have been photographed by a synthetic aperture radar and show the same point; a shape determination means 22 which determines a degree of similarity between the shape of the distribution of the plurality of pixels and an object shape indicated by geospatial information; and an association means 23 which associates the plurality of pixels with the object on the basis of the determined strength of the phase correlation and the determined degree of similarity.