Dual-Sensor Camera Imaging for Wide Dynamic Range Detection
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Solution Overview
Problem
Cameras struggle to capture images with a wide dynamic range, especially in autonomous vehicle applications, due to motion blur and exposure limitations, leading to distorted colors and impaired image quality when dealing with varying luminance levels from very bright to very dark objects.
Innovation Solution
A camera system utilizing multiple image sensors with different exposure settings, including one with a fixed exposure and another with a variable exposure, captures images through a neutral-density filter, allowing for a broader dynamic range and improved object identification by a processor executing instructions to analyze these images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If a single image sensor is used with fixed exposure settings, then the camera structure remains simple, but the dynamic range is limited and cannot capture both very bright and very dark objects simultaneously
Solution Approach 1:
The patent divides the image capture function into multiple independent image sensors, each optimized for specific luminance ranges. The first image sensor captures images in a first luminance range while the second image sensor captures images in a second luminance range, allowing the system to segment the dynamic range coverage across multiple specialized sensors rather than relying on a single general-purpose sensor.
Solution Approach 2:
The patent extends the dynamic range capability by adding another dimension to the camera system through multiple image sensors with different exposure settings. Instead of trying to expand the range of a single sensor, the system uses multiple sensors operating in parallel, each contributing to different portions of the overall luminance spectrum, effectively adding a dimensional aspect to dynamic range coverage.
2Reliability
If the exposure duration is kept short to prevent motion blur in moving vehicles, then motion clarity is improved, but the maximum exposure duration is limited and cannot capture sufficient light from dark objects
Solution Approach 1:
The patent segments the exposure duration requirements by assigning different exposure durations to different image sensors. The first image sensor uses a first exposure duration optimized for capturing dark objects, while the second image sensor uses a second exposure duration optimized for preventing motion blur in bright conditions. This segmentation allows each sensor to operate at its optimal exposure setting without compromise.
Solution Approach 2:
The patent applies local quality by optimizing different parts of the imaging system for different functions. Each image sensor is configured with specific exposure settings tailored to its intended purpose - one sensor is locally optimized for low-light conditions with longer exposure, while the other is locally optimized for high-light conditions with shorter exposure to prevent motion blur.
3Measurement precision
If a single image sensor captures images across all luminance levels, then the device complexity remains low, but object identification accuracy decreases for objects at extreme luminance levels
Solution Approach 1:
The patent segments the object identification task across multiple image sensors, each specialized for specific luminance ranges. The processor identifies first objects in the first luminance range using images from the first image sensor, and identifies second objects in the second luminance range using images from the second image sensor. This segmentation improves identification accuracy by matching objects with the sensor best suited for their luminance characteristics.
Solution Approach 2:
The patent changes the exposure settings parameter for different image sensors to optimize object identification. The first image sensor operates with exposure settings optimized for detecting objects in lower luminance ranges, while the second image sensor operates with exposure settings optimized for detecting objects in higher luminance ranges, thereby improving overall identification accuracy across the full dynamic range.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the ability to identify objects across a wide range of luminance levels, improving object detection and avoidance in autonomous vehicles by capturing images that span a wider dynamic range than a single sensor can achieve, reducing computation time and increasing the number of identifiable objects.
Implementation Method 1
The second image sensor receives light from the scene via a neutral-density filter
Data Source
AI summary
Example embodiments relate to multiple operating modes to expand dynamic range. An example embodiment includes a camera system. The camera system may include a first image sensor having a first dynamic range corresponding to a first range of luminance levels in a scene. The system may also include a second image sensor having a second dynamic range corresponding to a second range of luminance levels in the scene. The camera system may further include a processor coupled to the first image sensor and the second image sensor. The processor may be configured to execute instructions to identify objects of a first type in a first image of the scene captured by the first image sensor and identify objects of a second object type in a second image of the scene captured by the second image sensor.