Chemical imaging methods, including imaging mass spectrometry, are increasingly used for the analysis of samples ranging from biological tissues to electronic devices. A barrier to wider adoption of imaging mass spectrometry is the presence of matrix effects which complicate quantitative analysis. Interactions between an analyte molecule and its surroundings (the “matrix”) can substantially alter both the yield and type of ions observed. Furthermore, such “intrinsic” effects can be confused with nonlinear response due to detector saturation and other instrument-related complications. As a result, quantitative analyses of time-of-flight secondary ion mass spectrometry (TOF SIMS) data that attempt to account for matrix effects are rare. The authors discuss analysis of such data using maximum a posteriori reconstruction based on physically motivated models, and present progress toward the quantitative extraction of chemical concentration profiles and component spectra in the presence of matrix effects, using mixed self-assembled alkanethiolate monolayers as a test system. The authors demonstrate that the incorporation of matrix effects to lowest order using a series-expansion approach is an effective strategy and that doing so provides improved quantitative performance in measuring surface compositions and can also yield information about interactions between species during the SIMS process.