Probability- and curve-based fractal reconstruction on 2D DEM terrain profile

Data compression and reconstruction has been playing important roles in information science and engineering. As part of them, image compression and reconstruction that mainly deal with image data set reduction for storage or transmission and data set restoration with least loss is still a topic deserved a great deal of works to focus on. In this paper we propose a new scheme in comparison with the well-known Improved Douglas–Peucker (IDP) method to extract characteristic or feature points of two-dimensional digital elevation model (2D DEM) terrain profile to compress data set. As for reconstruction in use of fractal interpolation, we propose a probability-based method to speed up the fractal interpolation execution to a rate as high as triple or even ninefold of the regular. In addition, a curve-based method is proposed in the study to determine the vertical scaling factor that much affects the generation of the interpolated data points to significantly improve the reconstruction performance. Finally, an evaluation is made to show the advantage of employing the proposed new method to extract characteristic points associated with our novel fractal interpolation scheme.