Multi-Camera Exposure Control Using Map-Prioritized Regions
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Solution Overview
Problem
Image processing systems face challenges with overexposure and underexposure issues, particularly when the point of focus or light conditions change, leading to an inability to view critical areas due to uniform exposure adjustments across the entire image.
Innovation Solution
A computer-implemented method for adjusting exposure settings based on a region of interest, using localization parameters to determine the geographic position and light conditions of an autonomous vehicle, allowing for dynamic exposure adjustments specific to critical regions such as road surfaces, pedestrians, or traffic signs, thereby prioritizing the visibility of these areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If uniform exposure adjustment is applied across the entire image, then the overall brightness balance is maintained, but the region of interest becomes overexposed or underexposed and critical areas become unviewable
Solution Approach 1:
The image is divided into multiple regions including a region of interest (ROI) and non-ROI areas. Different exposure settings are applied to different regions, allowing the ROI to be properly exposed while maintaining acceptable exposure in other areas. This segmentation enables selective exposure control that preserves critical information.
Solution Approach 2:
Different exposure qualities are applied to different parts of the image. The ROI receives a customized exposure setting optimized for capturing critical details, while non-ROI areas use different exposure parameters. This local differentiation ensures that the most important areas are properly exposed without compromising the entire image.
2Speed
If the point of focus changes or light conditions change suddenly, then the camera must rapidly adjust exposure, but conventional algorithms affect the entire viewing screen causing over/underexposure
Solution Approach 1:
The image processing system segments the frame into ROI and non-ROI portions, applying different exposure adjustments to each. This allows rapid exposure changes in response to lighting conditions or focus changes while maintaining image quality consistency in critical areas through region-specific control.
Solution Approach 2:
The exposure settings are dynamically adjusted for different regions based on real-time conditions. The system can rapidly change exposure parameters for the ROI independently from non-ROI areas, enabling fast response to environmental changes while maintaining overall image quality through adaptive regional control.
3Ease of operation
If users manually identify the point of focus and determine exposure compensation areas, then exposure can be adjusted, but this requires user intervention and does not consider the present environment
Solution Approach 1:
The system automatically identifies the region of interest and determines appropriate exposure settings without requiring user intervention. The autonomous vehicle's processing system analyzes the image data, identifies critical areas, and applies exposure adjustments autonomously, eliminating the need for manual user input while adapting to environmental conditions.
Solution Approach 2:
The system uses feedback from image analysis and environmental sensing to automatically adjust exposure settings. By continuously monitoring the scene and analyzing image data, the system adapts to changing environmental conditions and automatically optimizes exposure for critical regions without user intervention.
Data Source
AI summary
The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.