期刊
DIGITAL SIGNAL PROCESSING
卷 60, 期 -, 页码 186-199出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.dsp.2016.08.003
关键词
Image segmentation; 3D Otsu thresholding; Multi-scale image representation; Local Laplacian filtering
资金
- National Science & Technology Pillar Program, China [2012BAH48F02]
- National Science Foundation of China [61272209]
- Technology Development Plan of Jilin Province [201105017]
- Agreement of Science & Technology Development Project, Jilin Province [20150101014JC]
Thresholding technique is one of the most imperative practices to accomplish image segmentation. In this paper, a novel thresholding algorithm based on 3D Otsu and multi-scale image representation is proposed for medical image segmentation. Considering the high time complexity of 3D Otsu algorithm, an acceleration variant is invented using dimension decomposition rule. In order to reduce the effects of noises and weak edges, multi-scale image representation is brought into the segmentation algorithm. The whole segmentation algorithm is designed as an iteration procedure. In each iteration, the image is segmented by the efficient 3D Otsu, and then it is filtered by a fast local Laplacian filtering to get a smoothed image which will be input into the next iteration. Finally, the segmentation results are pooled to get a final segmentation using majority voting rules. The attractive features of the algorithm are that its segmentation results are stable, it is robust to noises and it holds for both bi-level and multi-level thresholding cases. Experiments on medical MR brain images are conducted to demonstrate the effectiveness of the proposed method. The experimental results indicate that the proposed algorithm is superior to the other multilevel thresholding algorithms consistently. (C) 2016 Elsevier Inc. All rights reserved.
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