In image processing, color is generally treated as an autonomous entity that is separate from spatial dimensions. Consequently, color processing and color mapping are predominantly done as point operations, linking one color to another, without considering spatially neighboring colors. It is well known that this point-wise approach does not capture the spatial dependencies of color that we humans experience in everyday life. More precise mathematical models of color vision that take into account spatial dependencies are generally computationally expensive. This leads to a continuing predominance of point-wise color processing. We introduce some simple spatially dependent processing techniques and demonstrate the potential advantages of even such simple schemes. The underlying assumption is that simple spatial operations allow the "hiding" of artifacts and errors in a way that is less objectionable to a human observer.