Kullback–Leibler Divergence-Based Fuzzy C-Means Clustering

We propose a Kullback–Leibler Divergence-Based Fuzzy C-Means Clustering algorithm for image segmentation, published in IEEE TCYB, 2022.

We elaborate on a Kullback-Leibler divergence-based Fuzzy C-Means (FCM) algorithm by incorporating a tight wavelet frame transform and morphological reconstruction. To make membership degrees of each image pixel closer to those of its neighbors, a Kullback-Leibler divergence term on partition matrix is introduced as a part of FCM, thus resulting in Kullback-Leibler divergence-based FCM.