Despite its many strengths, TOF-SIMS imaging presents the analyst with several formidable challenges. One of the most notable of these challenges is differentiating between chemical and topographical effects. The intensity of ion signals depends not only on the surface composition but also upon the surface height and inclination (topography) and the material beneath the surface (matrix). These effects can be particularly dramatic on insulating samples where topography may result in a distortion of the electric field. In many cases, the intensity variations due to the structure of the sample can obscure features associated with surface chemistry. We have been involved in quantifying the effects of topography on TOF-SIMS images and exploring multivariate statistical methods that can be used to deconvolve chemical and topographic effects. Images of surfaces with strong topographic features, including fibers, spherical particles, and trenches will be presented. The influence of these topographic features on the absolute and relative peak intensities has been explored on conducting and insulating surfaces. We have found that when images are generated by rastering the ion beam, topography can cause severe distortions in the image. For example, spikes on the surface can appear as thin stripes in the image. Particles can create field lines that result in repressed ion emission causing a halo surrounding the particles. Multivariate statistics can help reduce some but not all of these effects on the images. Results will be presented using principle components analysis and mixture models to process images with confounding chemical and topographical features.