Rational polynomial image magnification based on edge and distance constraints

Abstract

Surface fitting is one of the most effective methods in image magnification. The key is to construct the surface fitting the image.Image details and edges play a key role in the visual effect of the image. Therefore, one of the keys to constructing the fitting surface is to preserve the image details and edges.The surface fitting methods based on spline and polynomial cannot effectively preserve the edge information of the image, so that the magnified image has obvious jagged edges. In this paper, a new image magnification algorithm based on edge and distance constraints is proposed. The algorithm constructs a quadratic polynomial surface patch on the adjacent region of each pixel, which fits the pixels in the neighborhood, and a quadratic polynomial median surface patch is constructed on each quadrilateral mesh. The rational polynomial patch is generated from the weighted average of five patches on each quadrilateral mesh. The patch has the accuracy of the quadratic polynomial approximation, and the resulting image has a better visual effect. The accuracy and visual effects of the magnified image are improved by constructing error patches. The new algorithm calculates the constant term, the first term and the second term of the quadratic polynomial by different methods, which provides a new technique for constructing the polynomial function with constraints. The experimental results show that compared with other algorithms, the proposed algorithm not only has higher approximation accuracy but also has better visual effect of the magnified image.