Robust Line-Based Radial Distortion Estimation From a Single Image

Abstract

The pinhole model utilized in most computer vision algorithms becomes unfeasible because of lens distortion. Thus it is a must to compensate lens distortion to make the pinhole model available. In this paper, we propose a new robust line-based distortion estimation method to correct radial distortion. Our method works from a single image and is able to estimate the distortion center rather than assuming it is at the image center. Distortion parameters are estimated from parameters of circulars arcs, on the basis that straight lines are imaged as circular arcs under one-parameter division model. A new feature selection scheme by refining circular arcs is introduced to make the process of distortion estimation fully automatic and more robust. Moreover, a linear optimization algorithm is applied to calculating parameters in each selection run, making our feature selection scheme more efficient. Experiments on synthetic images and real images show that our method performs well in radial distortion estimation even with severely distorted images.

Keywords

• Distortion estimation
• radial distortion
• division model
• feature selection
• plumb-line