The Laplace operator introduced in the BSCB model during the transmission process uses four adjacent points around a certain pixel, limiting the pixel representation and then resulting in blurred edges after restoration. In this study, an improved BSCB (Bertalmio, Sapiro, Caselles, Ballester) algorithm is proposed based on rough data deduction to optimize this problem. The improved BSCB algorithm uses the rough data deduction space to formulate rules related to a certain pixel for mining the approximation, derivation, and expansion relations between pixels and adopting points that exhibit the greatest correlation with a certain pixel, avoiding the locality of pixel representation. The experimental results denote that the points adopted during the transmission process of the improved BSCB algorithm can better reflect the image structure, and the proposed algorithm can obtain a better visual effect when compared with the classical BSCB algorithm. The peak signal-to-noise ratio also confirms the improvement of the restoration effect based on the data level.