CRITICAL ASSESSMENT OF CORRECTION METHODS FOR FISHEYE LENS DISTORTION

Abstract. A fisheye lens is widely used to create a wide panoramic or hemispherical image. It is an ultra wide-angle lens that produces strong visual distortion. The distortion modeling and estimation of the fisheye lens are the crucial step for fisheye lens calibration and image rectification in computer vision and close-range photography. There are two kinds of distortion: radial and tangential distortion. Radial distortion is large for fisheye imaging and critical for the subsequent image processing. Although many researchers have developed calibration algorithms of radial distortion of fisheye lens, quantitative evaluation of the correction performance has remained a challenge. This is the first paper that intuitively and objectively evaluates the performance of five different calibration algorithms. Upto- date research on fisheye lens calibration is comprehensively reviewed to identify the research need. To differentiate their performance in terms of precision and ease-using, five methods are then tested using a diverse set of actual images of the checkerboard that are taken at Wuhan University, China under varying lighting conditions, shadows, and shooting angles. The method of rational function model, which was generally used for wide-angle lens correction, outperforms the other methods. However, the one parameter division model is easy for practical use without compromising too much the precision. The reason is that it depends on the linear structure in the image and requires no preceding calibration. It is a tradeoff between correction precision and ease-using. By critically assessing the strengths and limitations of the existing algorithms, the paper provides valuable insight and guideline for future practice and algorithm development that are important for fisheye lens calibration. It is promising for the optimal design of lens correction models that are suitable for the millions of portable imaging devices.