Research On Fish-eye Image Correctionalgorithm

As fish-eye lens have the advantages of short focal length (f=6~16mm) and large field (about even ), Thus it have been very widely used in many areas, such as video conferencing, video surveillance, intelligent transportation, panoramic view etc. But the fish-eye images that are taken with the camera has a very serious distortion, if we want to use the information of projection image with serious distortion, these deformed images need to be corrected to comply with the visual habits of the perspective projection image. Therefore, Correcting the images that is captured by fish-eye lens is worthy of the subject of research. 180 02700The effective area need to be extracted before the fish-eye image correction. It is critical in the entire correction process. In this paper, an improved algorithm is given for the deficiencies of several commonly used extraction methods. The experimental results show that the method improves efficiency under ensuring the premise of accuracy. The fish-eye image correction is divided into 2D and 3D correction. 2D fish-eye image correction directly map the pixel of the fish-eye image to the corrected image, 3D fish-eye image correction is that the pixel in the image is projected into three dimension space and then it is mapped to the corrected image by corrected model.The main works of the paper are as follows:(1) The relevant literatures about the fish-eye is analyzed and summarized, that describes the development of fish-eye image technique and the significance of the fish-eye image correction. Discussion of the relevant theoretical knowledge of image correction, such as: all kinds of coordinates, the pinhole image, perspective projection, all kinds of distortion and image preprocessing. The image model is given by the feature of fish-eye image.(2) Fish-eye image extraction circular effective area is very important throughout the whole correction. This paper gives some usually used the extraction algorithms of the effective circular area for fish-eye image and experimental results are given. The paper points out the shortcomings from the adaptability, complexity, computation.(3) As the shortcoming of area statistics, sweeping line by line and region growing, this paper gives the improvement algorithm of the effective circular area for fish-eye image and the corresponding verification. In addition, it compares several algorithms.(4) According to the characteristic of fish-eye image, fish-eye image are corrected respectively from the perspective of 2D and 3D space, such as: longitude coordinate correction, equidistance projection and spherical constraint model. Finally, verifying the algorithms.