The haptic rendering of surface mesostructure (fine relief features) in dense triangle meshes requires special structures, equipment, and high sampling rates for detailed perception of rugged models. Some approaches simulate haptic texture at a lower processing cost, but at the expense of fidelity of perception. We propose a better method for rendering fine surface detail by using image-based Hybrid Rugosity Mesostructures (HRMs), composed of paired maps of piece-wise heightfield displacements and corresponding normals, which are layered on top of a less complex mesh, adding greater surface detail than the one actually present in the geometry. The core of the algorithm renders surface features by modulating the haptic probe's force response using a blended HRM coat. The proposed method solves typical problems arising at edge crossings, concave foldings and smoothing texture stitching transitions across edges. By establishing a common set of specially devised meshes, HRM mesostructures, and a battery of performance tests, we build a usability testing framework that allows a fair and balanced experimental procedure for comparing haptic rendering approaches. The trial results and user testing evaluations show the goodness of the proposed HRM technique in the accurate rendering of high 3D surface detail at low processing costs, deriving useful modeling and perception thresholds for this technique.