Extended Range Image Processing via Motion Vector Registration

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Solution Overview

Problem

Existing electro-optical (EO) systems face challenges in processing images of moving targets and scenes with high noise and limited resolution, especially at long ranges, due to issues with motion tracking and integration of image frames.

Innovation Solution

The proposed solution involves generating motion vectors by computing correlation functions between reference and current frames at registration points, registering the current frame based on these vectors, and integrating frames over time to produce stabilized and noise-reduced images, enhancing both scene and target tracking capabilities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If motion vectors are generated by computing correlation functions at multiple registration points to improve tracking accuracy, then target detection precision is improved, but computational complexity increases

Engineering Contradiction:
Improvetarget detection precisionVSAvoidcomputational complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent divides the image frame into multiple registration points (N registration points) and computes correlation functions independently at each point. This segmentation allows parallel processing of different regions, improving target detection precision through comprehensive coverage while managing computational complexity through distributed calculation across multiple points rather than processing the entire frame as a single unit.

Inventive Principle:
Principle #1Segmentation

2Reliability

If multiple image frames are integrated over time to reduce noise and improve resolution, then signal-to-noise ratio is improved, but processing time increases

Engineering Contradiction:
Improvesignal-to-noise ratioVSAvoidprocessing time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent implements continuous frame integration where multiple image frames are processed and combined over time to produce stabilized output. By maintaining continuous processing of incoming frames and integrating them systematically, the system reduces noise and improves signal-to-noise ratio while managing processing time through ongoing rather than batch processing, allowing real-time or near-real-time output generation.

Inventive Principle:
Principle #20Continuity of useful action

3Speed

If image frames are registered and integrated in real-time for continuous imaging, then imaging speed is improved, but noise reduction capability deteriorates

Engineering Contradiction:
Improveimaging speedVSAvoidnoise reduction capability
Core Design Contradiction:
SpeedVSReliability

Solution Approach 1:

The patent applies partial integration by selecting and integrating a subset of frames rather than all available frames, or by integrating frames with different weighting factors. This partial action approach maintains real-time imaging speed by not waiting for complete frame sequences while still achieving sufficient noise reduction through selective integration of the most relevant frames, balancing speed and noise reduction capability.

Inventive Principle:
Principle #16Partial or excessive action

Data Source

PatentUS7991196B2Continuous extended range image processing
Publication Date: 2011.08.02 LOCKHEED MARTIN CORP
  • US7991196B2 patent drawing
  • US7991196B2 patent drawing
  • US7991196B2 patent drawing

AI summary

Methods and systems for image processing are provided. A method for processing images of a scene includes receiving image data of a reference and a current frame; generating N motion vectors that describe motion of the image data within the scene by computing a correlation function on the reference and current frames at each of N registration points; registering the current frame based on the N motion vectors to produce a registered current frame; and updating the image data of the scene based on the registered current frame. Optionally, registered frames may be oversampled. Techniques for generating the N motion vectors according to roll, zoom, shift and optical flow calculations, updating image data of the scene according to switched and intermediate integration approaches, re-introducing smoothed motion into image data of the scene, re-initializing the process, and processing images of a scene and moving target within the scene are provided.