Rolling Shutter Image Correction Using Adaptive IMU Integration
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Solution Overview
Problem
Conventional image stabilization methods fail to effectively correct images acquired with rolling shutter technology under high-frequency vibrations, such as those caused by drone rotors, especially in low-light environments where longer exposure times are required, leading to overcompensation and distortion.
Innovation Solution
The method integrates inertial measurement unit (IMU) sensor data over exposure time to calculate an average camera orientation, using a cumulative buffer and index calculation based on gyroscope sampling frequency and exposure time, which adapts to changing exposure times and prevents further distortion in images subject to high-frequency vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If longer exposure times are used in low-light environments, then image brightness is improved, but image distortion increases due to high-frequency vibrations
Solution Approach 1:
The patent applies dynamics by making the stabilization correction adaptive to changing exposure times. The system dynamically adjusts the correction amount based on the actual exposure time used, rather than applying a fixed correction. This allows the system to optimize for both brightness and distortion reduction under varying lighting conditions.
Solution Approach 2:
The patent changes the parameter of exposure time and uses it to modulate the stabilization correction. By varying the correction amount as a function of exposure time, the system can accommodate longer exposures in low light while preventing excessive correction that would cause distortion. The correction amount is scaled according to the exposure time parameter.
2Manufacturing precision
If conventional image stabilization methods are applied, then motion blur is reduced, but overcompensation and distortion occur under high-frequency vibrations
Solution Approach 1:
The patent implements feedback by using IMU sensor data to continuously monitor camera motion and adjusting the stabilization correction accordingly. The system processes gyroscope samples, integrates them over the exposure time, and uses this feedback to calculate the appropriate correction amount, preventing overcompensation.
Solution Approach 2:
The patent applies partial action by using only the portion of IMU data that is relevant to the actual exposure time. Instead of applying full stabilization correction regardless of exposure duration, the system integrates IMU samples proportionally to the exposure time, applying just enough correction to reduce motion blur without excessive correction that would cause distortion.
3Device complexity
If IMU sensor data is not integrated over exposure time, then processing complexity is reduced, but correction accuracy deteriorates for varying exposure times
Solution Approach 1:
The patent applies preliminary action by pre-calculating the integration of IMU sensor data over the exposure time period. The system accumulates gyroscope samples during the exposure and uses this pre-integrated data to determine the correction amount, ensuring accurate correction without requiring complex real-time processing during the exposure itself.
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
This approach prevents further distortion in images with high-frequency motion blur without overcorrecting, effectively stabilizing images with varying exposure times and frequencies, improving image quality in low-light conditions.
Implementation Method 1
obtain gyroscope samples from an inertial measurement unit (IMU) of the image acquisition device during image acquisition
Implementation Method 2
integrate the gyroscope samples over the exposure time of the image to obtain an integrated signal representing an average camera orientation during image acquisition
Data Source
AI summary
A method of correcting an image obtained by an image acquisition device includes obtaining successive measurements, Gn, of device movement during exposure of each row of an image. An integration range, idx, is selected in proportion to an exposure time, te, for each row of the image. Accumulated measurements, Cn, of device movement for each row of an image are averaged across the integration range to provide successive filtered measurements, G, of device movement during exposure of each row of an image. The image is corrected for device movement using the filtered measurements G.