Electro-Optical Imagery Reference Architecture

Publication date: May 12, 2021 (Diagram history)

This architecture enables you to process electro-optical imagery on AWS.

Electro-Optical Imagery Reference Architecture

1. Demodulate and Decode: Extract baseband waveform from modulated carrier; remove forward error correction.

2. Convert into raw sensor data: Decommutate signal frames; decrypt data .

3. Process Raw Images: Process Raw Images and Perform QA Review

   • QA Review: Confirm Images are sufficient for processing

   • AWS Batch: Run multiple jobs in parallel

   • AWS Fargate and AWS Lambda:

     • Sensor Correction: Apply corrections for optical distortions

     • Orthorectify: Sensor perspective

     • Georeference: Apply image to spatial grid and assign known coordinate system

     • Generate Thumbnails: Create post-processed thumbnails for customer purchase

4. Store metadata: Store information on latitude/longitude collection, region collection, time and date of retrieval .

5. Storage: Store preprocessed images in a variety of Amazon S3 services by balancing cost savings and time of retrieval.

6. Post Processing and Analysis: Complete imagery processing.

   • Feature Extraction: Identify features in images (such as ships)

   • Naming/Tagging of Features: Tag features by name/identification system

   • Time Series Creation: Tag images to sort

7. Storage and Dissemination: Final storage of images and analytics for end customer.

8. Customer Delivery: Deliver final images to end customers

Electro-Optical Imagery Reference Architecture (Classified Processing)

1. Demodulate and Decode: Extract baseband waveform from modulated carrier; remove forward error correction.

2. Convert into raw sensor data: Decommutate signal frames; decrypt data .

3. Immutable transaction log: Cryptographically establish provenance and fidelity .

4. Optional Classified Processing: Throughout the image processing, move data to the appropriate regions for classified processing.

5. Process Raw Images: Process Raw Images and Perform QA Review

   • QA Review: Confirm Images are sufficient for processing

   • AWS Batch: Run multiple jobs in parallel

   • AWS Fargate and AWS Lambda:

     • Sensor Correction: Apply corrections for optical distortions

     • Orthorectify: Sensor perspective

     • Georeference: Apply image to spatial grid and assign known coordinate system

     • Generate Thumbnails: Create post-processed thumbnails for customer purchase

6. Store metadata: Store information on latitude/longitude collection, region collection, time and date of retrieval .

7. Storage: Store preprocessed images in a variety of Amazon S3 services by balancing cost savings and time of retrieval.

8. Post Processing and Analysis: Complete imagery processing.

   • Feature Extraction: Identify features in images (such as ships)

   • Naming/Tagging of Features: Tag features by name/identification system

   • Time Series Creation: Tag images to sort

9. Storage and Dissemination: Final storage of images and analytics for end customer.

10. Customer Delivery: Deliver final images to end customers

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Diagram history

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Change	Description	Date
Initial publication	Reference architecture diagram first published.	May 12, 2021

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