In this work we introduce a new image filtering scheme, based on the spectrum of a global filter computed from image affinities. The global filter derived from a fully connected graph representing the image, can be approximated using the Nystrom extension. Using this, we drive an approximation to the spectral (principal) components of the global filter which can be implemented efficiently by sampling a fairly small percentage of the pixels in the image. Experiments illustrate that the mapping of the eigenvalues by an appropriate polynomial function endows the filter with a number of important capabilities, such as edge-aware sharpening, denoising, tone manipulation and abstraction.