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Image Vignetting Correction Using a Deformable Radial Polynomial Model.

Artur Bal^1,2, Henryk Palus¹

¹Department of Data Science and Engineering, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

Sensors (Basel, Switzerland)

|February 11, 2023

Summary

A new Deformable Radial Polynomial (DRP) model corrects image vignetting, a common radiometric error. This model offers improved accuracy over the standard Radial Polynomial (RP) model for lens-camera systems.

Keywords:

approximation function flat-field correction image shading image vignetting low-level vision single-image vignetting correction vignetting correction vignetting modeling

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Area of Science:

Computer Vision
Image Processing
Optical Engineering

Background:

Image vignetting is a significant radiometric error in lens-camera systems.
Vignetting correction is crucial for accurate image analysis and applications.
Existing methods like flat-field correction rely on accurate vignetting models.

Purpose of the Study:

To introduce a novel vignetting model, the Deformable Radial Polynomial (DRP) model.
To address the limitations of the standard Radial Polynomial (RP) model for non-radial vignetting.
To provide a computationally simple yet universal approach to vignetting correction.

Main Methods:

Development of the Deformable Radial Polynomial (DRP) model.
Utilizing distance transformation and minimization techniques.
Matching radial models to non-radial vignetting in lens-camera systems.

Main Results:

The DRP model demonstrates superior performance compared to the RP model.
Experimental results show significant improvements in vignetting correction accuracy (up to 50%).
The DRP model balances simplicity with the universality of complex models.

Conclusions:

The DRP model offers an effective solution for correcting non-radial image vignetting.
This new model enhances the accuracy of radiometric measurements in imaging systems.
The DRP model provides a practical advancement for lens-camera system calibration.