The sensitive detection of protein interactions in living cells is an important first step toward understanding each of the multitude of cellular processes that are regulated by such interactions. Spatial image cross-correlation spectroscopy (ICCS) is one method used to measure protein-protein interactions from the analysis of two-channel fluorescence microscopy images. In spatial ICCS, cross-correlation of fluctuations in fluorescence intensity recorded as images from two independent wavelength detection channels in a fluorescence microscope is used to determine the average number of interacting particles in the imaged region. Even in situations where the particle number density is relatively high, ICCS provides an accurate measure of molecular interactions. However, it was shown previously that the method suffers from relatively high detection limits of interacting particles (approximately 20%) and can be perturbed by heterogeneous spatial distributions of the fluorescent particles within the images. Here, we demonstrate new approaches to circumvent some of the limitations of ICCS. Spatial scrambling of pixel blocks within fluorescence images was investigated as a way of extending the detection of spatial ICCS to measure lower interaction fractions as well as colocalization within cells. We also show that 'mean-intensity-padding' of regions of interest within fluorescence images is a feasible method of applying ICCS to arbitrarily selected areas of the cell with boundaries or edge morphologies that would be impossible to analyze with conventional ICCS. Using these newly developed strategies we were able to measure the fraction of actin that interacts with alpha-actinin in the leading edge of a migrating cell.