The scale information in images is important for guiding image-filtering configuration. The authors propose a scale-aware spatially guided mapping (SaSGM) model, which formulates and combines multiple spatial influences of simple edge responses under different levels of detail. The SaSGM model is thus more sensitive to image patterns at a large scale. The authors further incorporate the SaSGM into several image processing models, such as detail enhancement and image stylization models. Experiments show that by inheriting the characteristics of the SaSGM, the extended models are able to differentiate image contents in terms of their scales and thus generate more natural or diversified visual effects. This article is part of a special issue on quality modeling.