@inbook{dfb9372907cb4ba8bd4a7d63fa172a0f,
title = "Hierarchical Data Clustering Based on Iterative Bilateral Filter",
abstract = "We propose a method for hierarchical data clustering based on iterative bilateral filter, which is an iterative version of bilateral filter, a nonlinear edge-preserving smoothing filter. Experimental results with a 2D point data demonstrate that the proposed method captures the hierarchical cluster structure in the dataset. We also present a memory-efficient method for implementing the proposed method, and experimentally show that the memory-efficient method converges faster than the original method. The convergence of given dataset to a single point is visually confirmed by applying the proposed method to the task of image segmentation, where any image converges to a uniform image.",
keywords = "bilateral filter, cluster analysis, dendrogram, hierarchical clustering, image segmentation, iterative method",
author = "Chenhao Guo and Yunjia Huang and Kohei Inoue and Naoki Ono and Kenji Hara",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.",
year = "2025",
doi = "10.1007/978-3-031-71013-1\_9",
language = "English",
series = "Lecture Notes on Data Engineering and Communications Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "88--97",
booktitle = "Lecture Notes on Data Engineering and Communications Technologies",
address = "Germany",
}