Polycrystalline Microstructure Reconstruction Using Markov Random Fields and Histogram Matching

A new numerical method is presented for reconstructing three-dimensional (3D) microstructures from two-dimensional (2D) sections, imaged on orthogonal planes, by exploiting the complete red–green–blue (RGB) color space. The algorithm reconstructs 3D models through sampling voxel neighborhoods to representative 2D micrographs, based upon a Markovian assumption. The sampling is followed by an optimization procedure, ensuring smoothness across the orthogonal sections of the synthesized voxels. Previous 3D Markov random field (MRF) microstructure reconstruction techniques were restricted to traditional grayscale images only. This method now enables the use of the entire RGB spectrum, employing a histogram matching step. This paper examines the algorithm’s accurate representation of orientations and morphologies, encompassing a variety of micrographs from electron backscatter diffraction (EBSD) and polarized light microscopy.