In this paper, an integrated resolution up-conversion and compression artifacts removal algorithm is proposed. Local image patterns are classified into object details or coding artifacts using the combination of structure information and activity measure. For each pattern class, the weighting coefficients for up-scaling and artifact reduction are optimized by a Least Mean Square (LMS) training technique, which trains on the combination of the original images and the compressed down-sampled versions of the original images. The proposed combined algorithm is proven to be more effective than previous classification based techniques in concatenation.