The electron-backscatter diffraction (EBSD) is a scanning electron microscopy (SEM) based technique used to obtain the grain orientation data. EBSD data often come with many misoriented pixels, which have the appearance of noise, and may have regions of missing data. We have developed partial differential equation-based denoising and inpainting algorithms, which produce high-quality reconstructions of the EBSD data. Our algorithms build on weighted total variation flow and minimal surface equation. In this poster, we compare the results obtained using our algorithms with various other denoising and data reconstruction algorithms commonly used for EBSD images. To this effect, we produce synthetic EBSD data with misorientation noise and missing data. We compare our PDE-based approach with other reconstruction algorithms such as mean filter, median filter, spline filter, Kuwahara filter, half-quadratic filter, and infimal convolution.