Spatial frequency-domain imaging (SFDI) utilizes multiple-frequency structured illumination and model-based computation to generate two-dimensional maps of tissue absorption and scattering properties. SFDI absorption data are measured at multiple wavelengths and used to fit for the tissue concentration of intrinsic chromophores in each pixel. This is done with a priori knowledge of the basis spectra of common tissue chromophores, such as oxyhemoglobin (ctO(2)Hb), deoxyhemoglobin (ctHHb), water (ctH(2)O), and bulk lipid. The quality of in vivo SFDI fits for the hemoglobin parameters ctO(2)Hb and ctHHb is dependent on wavelength selection, fitting parameters, and acquisition rate. The latter is critical because SFDI acquisition time is up to six times longer than planar two-wavelength multispectral imaging due to projection of multiple-frequency spatial patterns. Thus, motion artifact during in vivo measurements compromises the quality of the reconstruction. Optimal wavelength selection is examined through matrix decomposition of basis spectra, simulation of data, and dynamic in vivo measurements of a human forearm during cuff occlusion. Fitting parameters that minimize cross-talk from additional tissue chromophores, such as water and lipid, are determined. On the basis of this work, a wavelength pair of 670 nm∕850 nm is determined to be the optimal two-wavelength combination for in vivo hemodynamic tissue measurements provided that assumptions for water and lipid fractions are made in the fitting process. In our SFDI case study, wavelength optimization reduces acquisition time over 30-fold to 1.5s compared to 50s for a full 34-wavelength acquisition. The wavelength optimization enables dynamic imaging of arterial occlusions with improved spatial resolution due to reduction of motion artifacts.