Abstract
Lens distortion can introduce deviations in visual measurement and positioning. The distortion can be minimized by optimizing the lens and selecting high-quality optical glass, but it cannot be completely eliminated. Most existing correction methods are based on accurate distortion models and stable image characteristics. However, the distortion is usually a mixture of the radial distortion and the tangential distortion of the lens group, which makes it difficult for the mathematical model to accurately fit the non-uniform distortion. This paper proposes a new model-independent lens complex distortion correction method. Taking the horizontal and vertical stripe pattern as the calibration target, the sub-pixel value distribution visualizes the image distortion, and the correction parameters are directly obtained from the pixel distribution. A quantitative evaluation method suitable for model-independent methods is proposed. The method only calculates the error based on the characteristic points of the corrected picture itself. Experiments show that this method can accurately correct distortion with only 8 pictures, with an error of 0.39 pixels, which provides a simple method for complex lens distortion correction.
Highlights
The optical aberration of the lens will cause the non-linear distortion of the image.Distortion correction is necessary in digital image analysis
We propose a model-independent lens distortion correction method
We propose a model-independent lens distortion correction method based on sub-pixel phase encoding and isophase detection
Summary
The optical aberration of the lens will cause the non-linear distortion of the image.Distortion correction is necessary in digital image analysis. The characteristic of the traditional methods is to use the known structure information of the scene, which is usually used to calibrate the block. It can be used for any camera model with high calibration accuracy. The calibration process is complicated and requires high-precision known structural information. Zhang [9,10] proposed a multiviewpoint correction method that uses the correspondence between points in different images to measure lens distortion parameters. In some special cases, non-radial, tangential nonlinearity, or hybrid distortion may not be well corrected because the distortion is the cumulative effect of complex lens systems, camera geometric errors, and sensor shapes. An overly accurate model is bound to be very complicated, and the coupling of parameters may lead to numerical instability
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