UAV Image Exposure Method for Target Tracking in Light Shadow Changes
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in maintaining target tracking during aerial photography due to changes in light and shadow, leading to potential loss of the target object, especially when it enters shaded areas with low illuminance and high background illuminance.
Innovation Solution
An image exposure method for UAVs that involves acquiring original image information, obtaining weighted image information, calculating the compensation amount for automatic exposure, and adjusting the exposure strategy based on brightness specific gravity to maintain optimal exposure settings, including adjusting exposure time, analog gain, and digital gain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic exposure strategy is used for image capture, then the imaging process is simplified and operation is easier, but the target is easily lost when light and shadow conditions change
Solution Approach 1:
The patent applies local quality by performing exposure calculation separately for target areas and non-target areas. The exposure strategy is differentiated based on spatial location, with target areas receiving specialized exposure handling to maintain tracking reliability while non-target areas use standard automatic exposure, thus resolving the contradiction between ease of operation and target tracking reliability
Solution Approach 2:
The patent segments the image into target areas and non-target areas, and processes exposure parameters separately for each segment. This segmentation allows the system to maintain simple automatic exposure operation overall while applying specialized exposure control specifically to target regions, preventing target loss during lighting changes
2Measurement precision
If exposure time, analog gain, and digital gain are increased to improve target visibility in low illuminance, then target detection capability is improved, but image overexposure and noise increase
Solution Approach 1:
The patent applies different exposure parameter adjustments to different spatial regions. Target areas receive increased exposure parameters (time, analog gain, digital gain) to improve detection precision, while non-target areas maintain normal exposure settings to avoid overexposure and noise, thus resolving the contradiction between target detection precision and image quality
Solution Approach 2:
The patent dynamically changes exposure parameters (exposure time, analog gain, digital gain) based on local illuminance conditions. By adjusting these parameters specifically for target areas with low illuminance while maintaining normal parameters elsewhere, the system improves target detection without causing image overexposure or excessive noise
3Measurement precision
If weighted image information is calculated to improve exposure accuracy, then exposure precision is improved, but computational complexity increases
Solution Approach 1:
The patent applies weighted image information calculation only to target areas rather than the entire image. This localized approach improves exposure calculation precision for target regions while minimizing computational complexity by avoiding unnecessary calculations in non-target areas, thus resolving the contradiction between exposure precision and computational complexity
Data Source
AI summary
Embodiments of the present invention are an image exposure method and device for an unmanned aerial vehicle, and an unmanned aerial vehicle. The method comprises: firstly, acquiring the original image information about a target object, then obtaining the weighted image information according to the original image information, further obtaining the compensation amount of an automatic exposure according to the weighted image information, and finally adjusting an automatic exposure strategy according to the compensation amount of the automatic exposure. The method prevents an unmanned aerial vehicle from easily losing a target during the process of the unmanned aerial vehicle automatically following a moving object, even when encountering a change in light and shadow.