CMOS Imager Adaptive Exposure for Highlight Detail
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Solution Overview
Problem
Conventional imaging systems struggle with scenes having high dynamic range, leading to pixel saturation and loss of detail in highlights or specular reflections, as they cannot capture the full range of light variations in a scene.
Innovation Solution
An electronic image capture system with a CMOS imager that allows independent control of pixel integration time, using an adaptive exposure algorithm to decrease integration time in saturated pixels, enabling the capture of a wider dynamic range by adjusting exposure based on scene data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional imaging systems use a single integration time for all pixels, then the exposure can be set to capture the main scene, but pixels in highlighted portions become saturated and lose detail
Solution Approach 1:
The image sensor divides pixels into multiple regions with different integration times. The sensor captures first image data with a first integration time for normal scene exposure, and second image data with a second integration time for highlighted portions. This segmentation allows different parts of the scene to be captured with optimal exposure settings, preventing saturation in highlights while maintaining detail in normal areas.
Solution Approach 2:
The imaging system dynamically adjusts integration time based on scene requirements. By capturing multiple images with different integration times and selecting or combining them based on pixel saturation levels, the system adapts to varying light conditions within the scene, capturing both dim and bright portions effectively.
2Measurement precision
If the exposure level is set to capture the main scene correctly, then the couple is properly exposed, but the sun causes pixel saturation in the image
Solution Approach 1:
The system performs preliminary capture of the scene at the maximum integration time to identify which pixels will be saturated. Based on this preliminary data, it determines the coordinates of saturated pixels and then captures additional images with reduced integration time specifically for those pixel regions. This preliminary action allows the system to plan the multi-integration-time capture strategy in advance.
Solution Approach 2:
Different regions of the image sensor are assigned different integration times based on local scene brightness. Normal scene areas use the maximum integration time for optimal detail capture, while highlighted areas use reduced integration times to prevent saturation. This local quality approach ensures each region is captured with the most appropriate exposure settings.
3Loss of information
If multiple images are captured with different integration times, then the dynamic range is extended, but the processing complexity and number of captures increase
Solution Approach 1:
The system captures multiple images with different integration times, but only processes the portions of images that are necessary. Specifically, it identifies saturated pixels in the first image and only uses the second image data for those specific pixel coordinates, while using the first image data for non-saturated regions. This partial action approach extends dynamic range coverage while minimizing unnecessary processing.
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
The system achieves a greater scene exposure latitude, allowing for the capture of more dynamic range without pixel saturation, resulting in improved image quality with reduced noise and increased accuracy.
Implementation Method 1
CMOS imagers
Data Source
AI summary
A method for decreasing integration time of saturated paxels within an imager; wherein the method includes decreasing the integration time of the saturated paxels within an imager according to scene data from a captured image.