Variable Aperture CCD Pixel Readout for Motion Blur Deconvolution
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Solution Overview
Problem
Modern cameras face challenges in mitigating motion blur due to indeterminate and unpredictable motion during exposure, making it difficult to extract motion information from images, especially with constant apertures that do not provide directional or velocity data.
Innovation Solution
The solution involves changing the aperture shape or size during exposure to transform blur into a predictable shape, allowing for the detection of bokeh artifacts, which are then analyzed to determine motion direction, velocity, and acceleration, enabling deblurring and improving image clarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a constant aperture is used during exposure, then the image capture process is simple and straightforward, but motion blur becomes indeterminate and motion information cannot be extracted
Solution Approach 1:
The aperture is changed dynamically during the exposure period rather than remaining constant. The controller modifies the aperture size or shape at different time points, causing moving objects to produce distinctive bokeh artifacts that encode motion information. This dynamic adjustment allows the system to capture motion characteristics while maintaining a relatively simple hardware architecture.
Solution Approach 2:
The aperture parameters (size or shape) are changed during exposure to transform the blur characteristics. By varying the aperture state at different exposure intervals, the system creates distinguishable bokeh patterns that reveal motion direction and velocity, converting previously lost motion information into analyzable visual data.
2Measurement precision
If the aperture is changed during exposure to capture motion information, then motion details can be determined, but the device complexity and control difficulty increase
Solution Approach 1:
The exposure period is divided into multiple intervals, with the aperture held at different states during each interval. This segmentation allows the controller to systematically capture image data at discrete aperture configurations, simplifying the control logic while enabling precise motion detection through comparison of bokeh artifacts across segments.
Solution Approach 2:
The system captures image data at different aperture states and uses the resulting bokeh artifacts as feedback to determine motion characteristics. The controller adjusts aperture settings based on the need to capture specific motion information, creating a feedback loop where image analysis informs aperture control decisions for optimal motion detection.
3Loss of information
If multiple aperture states are used during exposure, then bokeh artifacts provide motion information, but the image processing complexity increases
Solution Approach 1:
The system converts the previously harmful effect of motion blur into a beneficial source of motion information. By capturing images at different aperture states, moving objects produce distinctive bokeh artifacts that encode motion direction and velocity. The image processor analyzes these artifacts, transforming what was once indeterminate blur into quantifiable motion data that enhances rather than degrades image quality.
Data Source
AI summary
A system and method for obtaining, by an electronic device, a first set of image data recorded during an image capture event and a second set of image data recorded during an image capture event. During the image capture event, a characteristic of an image capture device is changed from a first state to a second state. The first and second sets of image data are recorded by an image capture device having one or more image recording components with one or more image sensor arrays. An image is generated based at least in part on the first and second sets of image data.