Image Sensor Gain Calculation Using Exclusion Regions
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Solution Overview
Problem
Image sensors often face challenges in capturing scenes with varying dynamic ranges, leading to unsatisfactory representation of both bright and dark regions due to insufficient dynamic range, particularly when a compromise is needed for mixed lighting conditions.
Innovation Solution
A method is introduced where a gain setting for a primary image sensor is calculated using a subset of pixels from a test image sensor, excluding specific exclusion regions identified, such as areas of high brightness, depth, or temperature, to improve exposure settings and enhance image quality in regions of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a gain setting is calculated using all pixels from the image sensor, then the exposure setting reflects the overall scene brightness, but regions with extreme brightness (bright regions or dark regions) cannot be properly represented due to insufficient dynamic range
Solution Approach 1:
The patent extracts and removes pixels corresponding to exclusion regions (bright regions, dark regions, or regions with insufficient depth/temperature data) from the histogram calculation. By taking out these problematic pixels, the gain setting calculation focuses only on reliable pixel data, preventing extreme values from skewing the exposure setting and ensuring accurate representation of regions of interest.
Solution Approach 2:
The patent applies different processing quality to different regions. Instead of treating all pixels equally, it identifies exclusion regions based on local characteristics (brightness thresholds, depth information, temperature data) and applies selective exclusion. This allows high-quality exposure calculation for regions with sufficient data while excluding regions that would compromise overall accuracy.
2Reliability
If the dynamic range of the sensor is insufficient to capture the worst case dynamic range, then some regions of the image will not appear as desired, but increasing the dynamic range requires additional hardware resources
Solution Approach 1:
The patent performs preliminary identification of exclusion regions using test matrix data (depth or temperature information) before calculating the final gain setting. By preliminarily determining which regions should be excluded based on depth or temperature thresholds, the system prepares a filtered pixel set that ensures accurate exposure calculation without requiring the sensor to capture the full dynamic range of all regions simultaneously.
Solution Approach 2:
The patent introduces intermediary data (test matrix from depth or temperature sensors) as a mediator to guide the exposure calculation. This intermediary information identifies which regions should be excluded from the histogram, allowing the system to achieve reliable image representation by selecting appropriate pixels for exposure calculation rather than relying solely on the sensor's raw dynamic range capability.
3Adaptability or versatility
If a compromise gain setting is used to balance bright and dark regions, then both regions cannot appear as desired simultaneously, but using different gain settings for different regions requires complex processing
Solution Approach 1:
The patent segments the image pixels into inclusion regions and exclusion regions based on characteristics such as brightness thresholds, depth information, or temperature data. This segmentation allows the system to calculate a single gain setting based on reliable pixels (inclusion regions) while excluding pixels that would compromise the exposure calculation (exclusion regions), achieving adaptability without requiring complex regional processing.
Data Source
AI summary
Calculating a gain setting for a primary image sensor includes receiving a test-matrix of pixels from a test image sensor, and receiving a first-frame matrix of pixels from a primary image sensor. A gain setting is calculated for the primary image sensor using the first-frame matrix of pixels except those pixels imaging one or more exclusion regions identified from the test matrix of pixels.