Vehicle HDR Camera Pipeline for Real-Time Hazard Detection
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating unpredictable environments due to limitations such as visibility, traction, and lighting conditions, which can lead to accidents even with the use of LIDAR and RADAR in combination with cameras.
Innovation Solution
The implementation of a real-time high-dynamic range (HDR) camera system that processes pixel values from multiple image sensors to provide a continuous view of a vehicle's environment, merging images taken at different light levels to extend the dynamic range and detect features in both very low-light and intensely lit areas, allowing for improved hazard detection and response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cameras with limited dynamic range are used, then the system is simpler and faster, but it cannot detect features in scenes with extreme lighting conditions (bright lights or dark areas)
Solution Approach 1:
The camera system is divided into multiple image sensors, each optimized for different light levels (bright, intermediate, dark). Each sensor segment captures data for its optimal range, and the system merges these segmented views to create a complete HDR image that covers the full dynamic range, solving the limitation of single-sensor cameras in extreme lighting conditions
Solution Approach 2:
The system combines multiple images captured at different light levels by merging corresponding pixels from each sensor. This merging process integrates the strengths of each sensor (capturing bright, intermediate, and dark areas) to produce a single composite image with extended dynamic range, enabling detection in both very bright and very dark scene regions
2Productivity
If the system waits to collect entire image frames before processing, then it ensures complete image data, but it increases processing time and reduces real-time response capability
Solution Approach 1:
The system processes pixel values continuously as they are generated by the image sensors, rather than waiting for complete frames. This continuous processing approach maintains an uninterrupted data flow through the pipeline, allowing the system to generate HDR output in real-time without the delays associated with traditional frame-based processing
Solution Approach 2:
The system performs preliminary processing operations on pixel values as they stream in, preparing and merging data before complete frames are available. This preliminary action on individual pixels enables real-time HDR generation while maintaining the integrity and completeness of the final image data
Data Source
AI summary
The invention provides an autonomous vehicle with a video camera that merges images taken a different light levels by replacing saturated parts of an image with corresponding parts of a lower-light image to stream a video with a dynamic range that extends to include very low-light and very intensely lit parts of a scene. The high dynamic range (HDR) camera streams the HDR video to a HDR system in real time—as the vehicle operates. As pixel values are provided by the camera's image sensors, those values are streamed directly through a pipeline processing operation and on to the HDR system without any requirement to wait and collect entire images, or frames, before using the video information.