Contrast enhancement is an important preprocessing technique for improving the performance of downstream tasks in image processing and computer vision. Our multidimensional photoemission spectroscopy results in densely sampled data of higher than three dimensions. The initial understanding of these complex multidimensional datasets often requires human intervention through visual examination, which may be hampered by the varying levels of contrast permeating through the dimensions. In collaboration with collaborators from the MPI for Intelligent Systems, a multidimensional extension of contrast-limited adaptive histogram equalization (MCLAHE) has been developed.

The algorithm is publicly available, a preprint of its description is available here: arXiv:1906.11355.