Infrared-Visible Image Fusion for UAV Target Tracking
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) equipped with infrared cameras face difficulties in tracking objects due to similar temperatures between objects and their surroundings, making it challenging to distinguish targets effectively using only infrared information.
Innovation Solution
A computer-implemented method and system that combines infrared and visible images to generate a combined image, allowing for the extraction and matching of features, which are then used to identify and track targets by generating control signals for the UAV's imaging device and carrier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only infrared imaging is used for target tracking, then the system structure remains simple, but target detection accuracy deteriorates when object temperature is similar to surrounding environment
Solution Approach 1:
The patent combines infrared imaging and visible light imaging into a unified tracking system. The infrared image processing unit processes infrared images to extract target features, while the visible light image processing unit processes visible light images to extract target features. Both processing results are integrated to generate comprehensive control signals for tracking, thereby improving target detection accuracy in environments where temperature contrast is insufficient while maintaining reasonable system complexity through modular architecture.
2Measurement precision
If infrared and visible images are combined for tracking, then target identification accuracy improves, but image processing complexity increases
Solution Approach 1:
The patent divides the image processing system into separate infrared image processing unit and visible light image processing unit. Each unit independently extracts target features from its respective image type. The infrared processing extracts thermal characteristics while visible light processing extracts optical characteristics. These segmented processing streams are then integrated to form comprehensive target identification, reducing overall processing complexity through modular division of labor.
Solution Approach 2:
The patent introduces a control signal generation unit that acts as an intermediary to integrate the processing results from both infrared and visible light image processing units. This intermediary unit synthesizes the feature extraction results from both imaging modalities and generates unified control signals for the imaging device and carrier, simplifying the integration process and reducing overall system complexity.
3Reliability
If multi-modal image fusion is implemented, then tracking reliability improves in challenging environments, but system resource consumption increases
Solution Approach 1:
The patent implements selective feature extraction and processing for infrared and visible light images. Rather than processing all image data in full detail, the system extracts key target features from each modality and integrates these essential features for tracking. This partial processing approach maintains tracking reliability in challenging environments while reducing overall computational resource consumption and energy usage.
Data Source
AI summary
A method for tracking includes obtaining an infrared image and a visible image from an imaging device supported by a carrier of an unmanned aerial vehicle (UAV), combining the infrared image and the visible image to obtain a combined image, identifying a target in the combined image, and controlling at least one of the UAV, the carrier, or the imaging device to track the identified target. Combing the infrared image and the visible image includes matching the infrared image and the visible image based on matching results of different matching methods.