Wide Dynamic Range Image Sensor Signal Mixing
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Solution Overview
Problem
Conventional image sensors with only high-gain cells suffer from white washout and black washout issues, leading to loss of gray level precision in dynamic scenes due to limited dynamic range, which cannot be effectively addressed by adjusting shutter speed or gain parameters.
Innovation Solution
A wide dynamic range image sensor method that combines the responses of high-gain and low-gain sensing cells by finding the highest slope linear fit within their response curves, allowing for seamless mixing to achieve a wider dynamic range, using a selected representative method of least squares (SR-MLS) to accurately calculate the relationship between the two cell types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only high-gain cells are used in the image sensor, then the sensor structure is simple, but white washout and black washout occur leading to loss of gray level precision
Solution Approach 1:
The image sensor is segmented into multiple sensing cell types with different gain factors (high-gain cells and low-gain cells), each optimized for specific dynamic ranges. This segmentation allows different regions of the dynamic range to be captured with appropriate precision, eliminating washout effects while maintaining manageable structural complexity through modular cell design.
Solution Approach 2:
Multiple sensing cell types with different gain characteristics are merged into a single pixel array structure. The high-gain and low-gain cells work together to cover an extended dynamic range, combining their advantages to achieve both high precision in shadow and highlight regions without requiring separate sensor arrays.
2Adaptability or versatility
If shutter speed or gain parameters are adjusted to address washout issues, then dynamic range is limited, but image quality degrades due to loss of gray level precision
Solution Approach 1:
Instead of adjusting shutter speed or electronic gain parameters, the invention changes the fundamental parameter of the sensor by incorporating multiple cell types with different fixed gain factors. This allows the sensor to maintain appropriate gain for each dynamic range region inherently, preserving gray level precision across the extended dynamic range without quality degradation.
3Adaptability or versatility
If high-gain and low-gain sensing cells are combined, then dynamic range is extended, but signal mixing non-linearity occurs
Solution Approach 1:
A feedback mechanism is implemented where the processor analyzes the response curves of high-gain and low-gain cells and automatically determines optimal mixing parameters. This feedback loop compensates for non-linearity by adjusting mixing weights and offset values based on actual cell responses, ensuring linear mixed signals across the extended dynamic range.
Solution Approach 2:
The invention dynamically changes mixing parameters (weights, offsets) based on the signal levels and cell responses. By adjusting these parameters adaptively, the system maintains signal linearity across different dynamic ranges while extending the overall sensor dynamic range through the combination of high-gain and low-gain cells.
Data Source
AI summary
A wide dynamic range image sensor method combines the response of high-gain sensing cells and low-gain sensing cells with better linearity than the prior art. A search is made in successive central regions within the response curve of the high-gain and low-gain cells to find a highest slope linear fit. This highest slope and the corresponding offset are used in mixing the high-gain and low-gain responses to achieve a wide dynamic range.