Hits:

Indexed by:期刊论文

First Author:Wang, Xiaoguang

Correspondence Author:Wang, XG (reprint author), Dalian Univ Technol, Sch Math Sci, Dalian 116024, Liaoning, Peoples R China.

Co-author:Lu, Dawei,Song, Lixin

Date of Publication:2018-01-01

Journal:COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

Included Journals:SCIE、Scopus

Volume:47

Issue:17

Page Number:4215-4228

ISSN No.:0361-0926

Key Words:Bayesian information criterion; image segmentation; model selection consistency; noisy image; robust estimation

Abstract:Image segmentation plays an important role in image processing before image recognition or compression. Many segmentation solutions follow the information theoretic criteria and often have excellent results; however, they are not robust to reduce the noise effect in contaminated image data. To guarantee the optimal segmentation with possible noise, a robust Bayesian information criterion is proposed to segment a grayscale image and it is less sensitive to noise. The asymptotic properties are also studied. Monte Carlo numerical experiments along with a brain magnetic resonance image are conducted to evaluate the performance of the new method.