Speckle interferometry provides a basis for analyzing the dynamic motions of materials through differencing of the field scattered from objects at two different times. Phase differences in the signals measured at different times, inferred from fringe patterns, indicate the degree of deformation present. Automatic analysis of differences images requires significant preprocessing to enhance the contrast of fringe regions. Often fringes that are evident to the human eye cannot be perceived automatically because the fringes usually consist of widely separated high intensity spikes. Median or averaging filters are ineffective at enhancing these patterns. Adaptive filtering similar to that used in SAR image analysis is capable of enhancing the fringe area contrast. A two step process is detailed. In a first phase a filter based on window mean and variance suppresses noise and generates a greater cohesion of high intensity points in the fringe areas. In a second phase the image is average filtered to smooth the intensities in the fringes. An auxiliary routine used to count fringes is discussed. Comparisons with median filtered results show the greater ability to automatically count fringes using this two step method.