Satellite Image Splicing With Metadata Lineage Retention
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Solution Overview
Problem
Conventional image retrieval tools for satellite imagery fail to guarantee the usability and retention of metadata, leading to inefficient manual intervention and loss of metadata in correcting flawed images, which are often unusable due to issues like missing pixels or cloud cover.
Innovation Solution
An automated system that splices together satellite images to generate coherent, up-to-date images while retaining metadata by identifying flaws, retrieving complementary images, and stitching them together, using geodatabases to maintain metadata lineage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to review and correct satellite images, then image quality and suitability can be improved, but time consumption and resource efficiency deteriorate
Solution Approach 1:
The system performs preliminary automated quality assessment of satellite images before manual review, identifying flawed images in advance. This preliminary filtering action reduces the number of images requiring manual intervention, thereby decreasing time consumption while maintaining reliability by ensuring only necessary manual reviews are performed.
Solution Approach 2:
The system enables self-service by implementing automated image quality assessment and metadata retention capabilities. The automated tools evaluate image quality metrics, identify flaws, and preserve metadata throughout processing, reducing dependence on manual intervention while maintaining image suitability and reducing time consumption.
2Reliability
If manual correction processes are applied to flawed satellite images, then image usability can be improved, but metadata retention deteriorates
Solution Approach 1:
The system introduces an intermediary automated processing layer between the original satellite image and the final corrected image. This intermediary layer preserves metadata throughout the correction process by automatically tracking and retaining metadata from source images, thereby improving image usability while preventing metadata loss that would otherwise occur during manual correction.
Solution Approach 2:
The system creates and maintains copies of metadata alongside image processing operations. By automatically copying and preserving metadata through each processing step, the system ensures metadata retention is maintained even as images undergo correction and enhancement, allowing usability improvement without information loss.
3Reliability
If multiple satellite images are downloaded and manually assembled, then complete coverage can be improved, but productivity and resource efficiency deteriorate
Solution Approach 1:
The system applies segmentation by automatically dividing the task of creating complete coverage into individual image assessment and assembly steps. It segments the evaluation of multiple satellite images, automatically identifying which images contribute to complete coverage and assembling them systematically, thereby improving coverage completeness while enhancing productivity by eliminating manual assembly operations.
Solution Approach 2:
The system implements feedback mechanisms that automatically evaluate image quality metrics and provide information about coverage status. This feedback loop enables the system to intelligently select and assemble images to achieve complete coverage, improving both coverage completeness and productivity by automating the decision-making process that previously required manual intervention.
Data Source
AI summary
Automatic image splicing with metadata retention is disclosed. An image is retrieved from an image repository and checked for missing or invalid pixels. Additional images are retrieved from the image repository based on the missing or invalid pixels. Valid pixels from the additional images are used to replace the missing or invalid pixels in the original image. The resulting spliced image is complete. Metadata from all images represented in the spliced image are included in a metadata lineage associated with the spliced image.