Imaging Sensor Gain and Exposure Balancing via Motion
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Solution Overview
Problem
Electronic devices face challenges in capturing high-quality imagery for applications like SLAM, AR, and VR due to varying capture conditions, such as device motion and scene distance, which affect the optimal settings for gain and exposure.
Innovation Solution
The electronic device balances gain and exposure settings using a combination of non-visual sensor data, such as gyroscopes, and analysis of feature tracks from captured imagery to enhance image quality, adjusting settings based on identified capture conditions like rotational velocity and scene distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If gain and exposure settings are adjusted to capture high-quality imagery, then image quality improves, but the complexity of identifying and implementing correct settings increases
Solution Approach 1:
The electronic device automatically determines motion characteristics using its own motion sensor and adjusts gain and exposure settings autonomously without requiring external input or complex manual configuration. The device serves itself by using its motion sensor data to dynamically optimize imaging parameters.
Solution Approach 2:
The system dynamically changes imaging parameters (gain and exposure) based on detected motion characteristics. When motion exceeds a threshold, the system adjusts these parameters to compensate for motion blur, transforming the imaging quality parameters in response to real-time conditions.
2Manufacturing precision
If motion compensation techniques are applied to maintain image quality during device motion, then image quality improves, but the complexity of the capture system increases
Solution Approach 1:
The system combines motion sensor data with imaging parameter control in a unified automated process. By merging these functions and implementing them through integrated software logic, the system reduces overall complexity compared to having separate manual adjustment mechanisms or multiple independent subsystems.
Solution Approach 2:
The system uses feedback from the motion sensor to continuously monitor device motion and automatically adjusts gain and exposure settings in response. This closed-loop feedback mechanism simplifies the capture system by eliminating the need for manual intervention or complex predictive algorithms.
3Adaptability or versatility
If automated settings adjustment is implemented to adapt to varying capture conditions, then adaptability improves, but the processing requirements and system complexity increase
Solution Approach 1:
The device automatically adapts to varying capture conditions by using its own motion sensor data to determine motion characteristics and adjust imaging parameters accordingly. This self-service approach eliminates the need for external control systems or complex user interfaces.
Solution Approach 2:
The system adapts to different capture conditions by dynamically changing gain and exposure parameters based on motion threshold detection. This parameter adjustment strategy provides versatility across various motion scenarios without requiring multiple dedicated systems for each condition.
Data Source
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AI summary
An electronic device [100] balances gain and exposure at an imaging sensor [104] of the device based on detected image capture conditions, such as motion of the electronic device [704], distance of a scene from the electronic device [710], and predicted illumination conditions for the electronic device [706]. By balancing the gain and exposure, the quality of images captured by the imaging sensor is enhanced, which in turn provides for improved support of location-based functionality.