Drone Camera Wobble Correction via Gyro Signal Filtering
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Solution Overview
Problem
Digital images captured by drones suffer from 'wobble' artifacts due to high-frequency vibrations, leading to image distortion and quality degradation, especially when used as mobile video cameras for capturing sequences intended for storage and later reproduction.
Innovation Solution
A digital filtering technique is applied to the gyrometric signal from the inertial unit of the drone, using a complementary filter with an inverse transfer function to correct for the irregular response of the gyrometric sensors, thereby eliminating overcorrections and widening the bandwidth for effective image stabilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a rolling shutter mechanism is used to capture video sequences, then the camera can capture images continuously, but the high-frequency vibrations cause wobble artifacts and image distortion
Solution Approach 1:
The patent implements a feedback mechanism where gyrometric sensors continuously measure the actual vibrations and movements of the drone, and this measurement is used to dynamically adjust the image capture and processing parameters. The system compares the expected image with the actual captured image, detects deviations caused by vibrations, and applies real-time corrections to compensate for the wobble effect, thereby maintaining image quality during continuous video capture.
Solution Approach 2:
The patent replaces mechanical vibration damping solutions with a digital/image processing-based solution. Instead of using complex mechanical stabilization systems or physical dampers, the invention uses software algorithms that process the captured images to remove vibration artifacts. This substitution of mechanical systems with digital processing reduces complexity while achieving effective vibration compensation.
2Manufacturing precision
If gyrometric correction is applied to compensate for vibrations, then image stabilization is improved, but overcorrection occurs causing new artifacts and ripples
Solution Approach 1:
The patent applies partial correction rather than full correction of the detected vibrations. The system intentionally applies less correction than the maximum possible amount, avoiding overcorrection. By using a correction factor that is less than unity, the system stabilizes images without introducing the ripples and artifacts that result from excessive correction, thus finding an optimal balance between stabilization and artifact prevention.
Solution Approach 2:
The patent implements dynamic adjustment of correction parameters based on real-time vibration characteristics. Rather than applying a fixed correction amount, the system continuously adapts the correction strength and parameters according to the measured vibration intensity and frequency. This dynamic approach allows the system to apply appropriate correction levels for different vibration conditions, preventing overcorrection while maintaining stabilization effectiveness.
3Device complexity
If standard gyrometric sensors are used for vibration measurement, then the system is simple, but the irregular frequency response causes inaccurate correction at certain frequencies
Solution Approach 1:
The patent changes the parameters of the gyrometric sensors, specifically selecting sensors with optimized characteristics for the expected vibration frequency range. By carefully choosing sensors with appropriate sensitivity, frequency response, and noise characteristics, the system achieves accurate vibration measurement without requiring complex sensor arrays or additional measurement devices, thus maintaining simplicity while improving precision.
Solution Approach 2:
The patent introduces an intermediary processing stage that compensates for the irregular frequency response of standard gyrometric sensors. A calibration or correction algorithm acts as an intermediary between the raw sensor output and the final correction application, adjusting the sensor readings to account for frequency-dependent inaccuracies. This intermediary processing layer corrects measurement errors without requiring replacement of the simple sensor hardware.
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 significantly reduces image distortions caused by drone vibrations, enhancing the visual quality of captured video sequences by accurately compensating for the wobble effect and improving image stabilization across a broader frequency range.
Implementation Method 1
an inertial unit, comprising a gyrometric sensor capable of measuring variations in the attitude of the drone and of outputting a gyrometric signal representative of the rotations of the drone at a given instant
Implementation Method 2
A digital filtering technique is applied to the gyrometric signal from the inertial unit of the drone, using a complementary filter with an inverse transfer function to correct for the irregular response of the gyrometric sensors
Implementation Method 3
an image processing module, comprising an anti-wobble module which receives the video data and the gyrometric signal as inputs, and outputs video data processed and corrected for artifacts introduced by vibrations produced by the drone
Data Source
AI summary
The drone comprises a camera (14) having a rolling shutter digital sensor which sends video data (l) line by line. An inertial unit (26) sends a gyrometric signal representative of the variations in attitude (φ, θ, ψ) of the camera at a given instant. An image processing module (30) comprising an anti-wobble module receives the video data (l) and the gyrometric signal as inputs, and outputs video data processed and corrected for artifacts introduced by the vibrations of the motors of the drone. A complementary filtering module (36) applies a predetermined compensating transfer function to the gyrometric signal at the input of the anti-wobble module, which transfer function is an inverse transfer function of the frequency response of the gyrometric sensor of the inertial unit.