Recent improvements in experimental and computational techniques have led to a vast amount of data on the microstructure and deformation of polycrystals. These show that, in a number of phenomena, including phase transformation, localized bands of deformation percolate in a complex way across various grains. Often, this information is given as point-wise values arrayed in pixels, voxels and grids. The massive extent of data in this form renders identifying key features difficult and the cost of digital storage expensive. This work explores the efficiency of wavelets in storing, representing and analyzing such data on shape-memory polycrystals as a specific example. It is demonstrated how a compact wavelet representation captures the essential physics contained in experimental and simulated strains in superelastic media.