4 papers
G-image Segmentation: Similarity-preserving Fuzzy C-Means with Spatial Information Constraint in Wavelet Space
Cong Wang, Witold Pedrycz, ZhiWu Li +2
G-images refer to image data defined on irregular graph domains. This work elaborates a similarity-preserving Fuzzy C-Means (FCM) algorithm for G-image segmentation and aims to dev…
Residual-driven Fuzzy C-Means Clustering for Image Segmentation
Cong Wang, Witold Pedrycz, ZhiWu Li +1
Due to its inferior characteristics, an observed (noisy) image's direct use gives rise to poor segmentation results. Intuitively, using its noise-free image can favorably impact im…
Residual-Sparse Fuzzy -Means Clustering Incorporating Morphological Reconstruction and Wavelet frames
Cong Wang, Witold Pedrycz, ZhiWu Li +2
Instead of directly utilizing an observed image including some outliers, noise or intensity inhomogeneity, the use of its ideal value (e.g. noise-free image) has a favorable impact…
Kullback-Leibler Divergence-Based Fuzzy -Means Clustering Incorporating Morphological Reconstruction and Wavelet Frames for Image Segmentation
Cong Wang, Witold Pedrycz, ZhiWu Li +1
Although spatial information of images usually enhance the robustness of the Fuzzy C-Means (FCM) algorithm, it greatly increases the computational costs for image segmentation. To…