Rolling Shutter Correction Using Iterative Orientation Data
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Solution Overview
Problem
Images captured with CMOS sensors and other rolling shutter sensors often suffer from deformities due to temporal shifts during image capture, especially when the device is in motion, and existing correction methods may not adequately account for high-frequency motion or require dedicated hardware.
Innovation Solution
An iterative image correction process that accounts for changes in imaging sensor orientation at different acquisition times, using an orientation component with sensors like gyroscopes and accelerometers to correct pixel positions and values across the image array, and performing fixed-point iterations to determine corrected pixel locations and values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rolling shutter capture is used to enable continuous image capture, then image capture speed is improved, but image deformation occurs due to temporal shifts between row exposures
Solution Approach 1:
The system performs preliminary actions by capturing orientation data from gyroscopes and accelerometers during the image capture process, and pre-calculates correction parameters based on device motion. This allows the correction to be applied during image processing, resolving the deformation issue while maintaining the high-speed rolling shutter capture capability.
2Manufacturing precision
If existing correction methods are used to fix rolling shutter deformities, then image correction is achieved, but high-frequency motion correction is inadequate
Solution Approach 1:
The system implements feedback by continuously monitoring device orientation through gyroscopes and accelerometers during capture, using this real-time motion data to dynamically adjust and refine correction parameters. This feedback loop enables accurate correction of high-frequency motion that previous static correction methods could not handle.
3Measurement precision
If dedicated hardware is used to achieve accurate rolling shutter correction, then correction precision is improved, but device complexity increases
Solution Approach 1:
The system achieves multi-functionality by utilizing existing motion sensing components (gyroscopes and accelerometers) that are already present in modern devices for other purposes like screen orientation and step counting. These existing sensors are repurposed for rolling shutter correction, eliminating the need for dedicated correction hardware while maintaining high precision.
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
Effectively corrects image deformities caused by rolling shutter effects, ensuring accurate representation of objects by aligning pixel acquisition times with sensor orientations, thereby reducing skewing and distortion in images.
Implementation Method 1
using an orientation component with sensors like gyroscopes and accelerometers to correct pixel positions and values
Implementation Method 2
using an orientation component with sensors like gyroscopes and accelerometers to correct pixel positions and values
Data Source
AI summary
Image captured with an image capture device with a rolling shutter may be deformed due to changes in imaging sensor orientation during image capture. Image deformities may occur due to rolling shutter that exposes rows of pixels to light at slightly different times during image capture. Deformities such as wobble, for example, and/or other deformities may be corrected by constructing an output image. The output image may be constructed by determining corresponding pixels within the input image. The location of the input pixel may be determined by performing one or more fixed point iterations to identify one or more input pixels within the input image. A value of the output pixel within the output image may be determined based on a value of a corresponding pixel within the input image.