Adaptive image interpolation algorithm based on the fuzzy logic

Conventional image interpolation algorithm always introduces the the blur and jagged edges. To solve this problem, an improved adaptive image interpolation algorithm with using membership function is proposed in this paper. Fuzzy logic is used to obtain the membership function with the local characteristics of the gradient and phase angle. The first step is to correct the special distance of interpolated pixels along one dimension in the basis of local asymmetry features and the membership function, and then to convert the corrected distance of one dimension into two dimensions, applying the corrected distance to conventional image interpolation algorithm. Experimental results demonstrate that the improved algorithm can produce better results in regard to the signal-to-nosie ratio and succeed in preserving interpolation image edges in various directions.