We report results from a new methodology for investigating the visually perceived properties of surface textures. Densely sampled two-dimensional 1/f(beta) noise processes are used to model natural looking surfaces, which are rendered using combined point-source and ambient lighting. Surfaces are shown in motion to provide rich cues to their relief. They are generated in real time to enable observers to dynamically manipulate surface parameters. A method of adjustment is employed to investigate the effects that the two surface parameters, magnitude roll-off factor and RMS height, have on perceived roughness. The results are used to develop an estimation method for perceived roughness.