Shape restoration of nonlinear distorted images

Image shape restoration based on mathematical transformation is a successful approach to nonlinear distortions in computer vision, robot vision and pattern recognition. The key of this process is to find the distortion function and its inverse function. Usually, the distortion function is unknown or unclear. Even in the case of when the function is known, it remains difficult to compute or estimate the parameters necessary for the restoration. To overcome this problem, in this paper, boundary functions have been used to approximate the exact distortion function. In this manner, the boundary functions are calculated using B-spline curve interpolation which coincides with the necessary condition of major elements that constitute a Coons transformation. The performance of the proposed method with nonlinear distorted images has been demonstrated in experiments with interesting results