In this paper, we approach the novel problem of classifying images of underwater textures as observed from outside the water. Our main contribution is to combine a geometric distortion removal algorithm with a texture classification method to solve the problem of classifying images of submerged textures when the water is disturbed by waves. We show that by modeling the separate types of distortion, we can extract enough texture information to correctly classify textures using spatial statistical measurements on the texton representations. We evaluate our algorithm on both natural and artificial textures acquired in our laboratory. Results are promising and show the feasibility of our algorithm.