CatSIM: A Categorical Image Similarity Metric

• Activity Number: 155 - Section on Statistics in Imaging Student Paper Award Winners
• Type: Topic-Contributed
• Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
• Sponsor: Section on Statistics in Imaging
• Author(s): Geoffrey Thompson* and Ranjan Maitra
• Companies: Indiana University and Iowa State University
• Keywords: image analysis; image segmentation; distortion; structural similarity

Abstract

We introduce CatSIM, a new similarity metric for binary and multinary two- and three-dimensional images and volumes. CatSIM uses a structural similarity image quality paradigm and is robust to small perturbations in location so that structures in similar, but not entirely overlapping, regions of two images are rated higher than using simple matching. The metric can also compare arbitrary regions inside images. CatSIM is evaluated on artificial data sets, image quality assessment surveys and two imaging applications.