Interchangeable Lens Distortion Correction by Feature Matching
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Solution Overview
Problem
Cameras equipped with interchangeable lenses face challenges in correcting lens distortions when they lack access to the necessary distortion correction algorithms for the installed lens, and may incorrectly apply algorithms meant for different lenses, leading to image blurring and distortion.
Innovation Solution
A method and device that determine lens distortion correction by matching features between images captured with different lenses, using a known distortion correction for one lens to calculate the correction for another without requiring known patterns, allowing real-time adaptation to lens changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the camera applies a lens distortion correction algorithm for a default lens, then the camera can correct distortions for the default lens, but the camera cannot correct distortions for interchangeable lenses without access to their specific correction algorithms
Solution Approach 1:
The system performs self-calibration by automatically detecting features in the captured image, matching them between corrected and uncorrected views, and computing the distortion correction parameters for the interchangeable lens without requiring external calibration patterns or manual intervention
Solution Approach 2:
The system changes the operational parameters by switching between a default lens with known distortion characteristics and an interchangeable lens with unknown distortion characteristics, then uses feature matching to transform the parameter set from the known lens to the unknown lens
2Measurement precision
If the camera uses known patterns such as chessboards for distortion correction, then the distortion correction can be calculated accurately, but the method requires special arrangements and prior knowledge of the scene
Solution Approach 1:
The system eliminates the need for external calibration patterns by using the scene itself as the calibration target, automatically detecting and matching features that are naturally present in the captured image
Solution Approach 2:
The feature matching approach works with any scene containing detectable features, making the distortion correction method universally applicable without requiring specific calibration patterns or controlled environmental conditions
3Stability of the object's composition
If the camera does not detect lens changes, then the camera can maintain its current correction algorithm, but the camera may apply incorrect correction algorithms when lenses are exchanged
Solution Approach 1:
The system implements feedback by continuously monitoring image quality metrics and feature matching results, and automatically adjusting the distortion correction algorithm when changes in lens characteristics are detected
Solution Approach 2:
The system transitions from a static correction approach (fixed algorithm for default lens) to a dynamic approach that automatically adapts the correction algorithm based on the currently installed lens, enabling the system to respond to lens exchanges in real-time
Data Source
AI summary
A method for determining a lens distortion correction comprising:obtaining an indication of a first feature and a first corrected position of the first feature in a first corrected image frame, the first corrected position is based on a first lens distortion correction of a first uncorrected position of the first feature in a first uncorrected image frame captured by the camera when equipped with a first interchangeable lens;detecting a change of lenses on the camera;obtaining an indication of a second feature and a second uncorrected position of the second feature in a second uncorrected image frame captured by the camera when equipped with a second lens;matching the first feature with the second feature; anddetermining a second lens distortion correction for the second lens based on a mapping between the first corrected position and the second uncorrected position.