Adaptive image interpolation based on rough set

A new adaptive interpolation algorithm for still image is presented. The algorithm is based on the concept of indiscernibility relation in rough set theory and incorporates a novel rotating mask. The sample points that are indiscernible to the loss point are first identified by applying the concept of upper and lower approximation based on the continuity of images. Then the lost point is further identified using the information of the sample points. Simulation results demonstrate that the new algorithm improves substantially the subjective and objective quality of the interpolated images over conventional interpolations. The algorithm represents an attempt to incorporate rough sets in image processing.