Feature-Preserving Mesh Decimation for Normal Integration

High-resolution normal maps, e.g. from photometric stereo, capture astonishing surface details. Since normals are estimated pixel-by-pixel, the subsequent normal integration is typically performed on the regular pixel grid. Consequently, resolving structures half the size requires doubling both image height and width.To avoid this quadratic growth with increasing image size, recent work has suggested approximating the pixel grid with lower-resolution 2D triangle meshes and integrating the triangle mesh afterwards. In our work, we analyse the local shape structure to increase the compression ratio and precision of 2D meshes. Previous work generated only isotropic meshes with equilateral triangles. Instead, our mesh decimation method leverages anisotropy by placing edges and vertices along ridges and furrows, thereby achieving a more accurate approximation. Our main contribution is the derivation of the renowned quadric error measure from mesh decimation for screen space applications and its combination with optimal Delaunay triangulations.