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Electro-Optical Imagery Reference Architecture - Electro-Optical Imagery Reference Architecture
Electro-Optical Imagery Reference ArchitectureElectro-Optical Imagery Reference Architecture (Classified Processing)Further readingDiagram history

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

Reference architecture diagram showing how you can use AWS services to process elctro-optical imagery on AWS.

  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)

Reference architecture diagram showing how to process classified electro-optical imagery on AWS

  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

Further reading

For additional information, refer to

Diagram history

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Initial publication

Reference architecture diagram first published.

May 12, 2021

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