To effectively extract the minimal relative reduction from incomplete decision table,the paper proposes an attribute reduction algorithm based on granular computing.First,changing trends of relative granularity in the process of the attribute reduction is analyzed and studied.Secondly,by increasing the attribute into the nuclear attributes set,method of extracting minimal reduction from incomplete decision table is discussed.Last,a detailed example is given to prove the validity of the algorithm.