Image Superresolution Reconstruction via Granular Computing Clustering

Algorithm 3

GrC clustering process.

Input: Data set , the user-defined threshold of granularity

Output: Granule set

S1. initialize the granule set

S2.

S3. for the th sample in S, form the corresponding atomic granule

S4.

S5. compute the fuzzy inclusion measure between the atomic granule and the th granule in

S6.

S7. find the maximal fuzzy inclusion measure

S8. if the granularity of the join of and is less than or equal to , the granule is replace by the join ,

otherwise is the new member of GS

S9. remove until is empty.