Year: 2022
Advances in Applied Mathematics and Mechanics, Vol. 14 (2022), Iss. 4 : pp. 960–988
Abstract
Image segmentation is a significant problem in image processing. In this paper, we propose a new two-stage scheme for segmentation based on the Fischer-Burmeister total variation (FBTV). The first stage of our method is to calculate a smooth solution from the FBTV Mumford-Shah model. Furthermore, we design a new difference of convex algorithm (DCA) with the semi-proximal alternating direction method of multipliers (sPADMM) iteration. In the second stage, we make use of the smooth solution and the K-means method to obtain the segmentation result. To simulate images more accurately, a useful operator is introduced, which enables the proposed model to segment not only the noisy or blurry images but the images with missing pixels well. Experiments demonstrate the proposed method produces more preferable results comparing with some state-of-the-art methods, especially on the images with missing pixels.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/aamm.OA-2021-0126
Advances in Applied Mathematics and Mechanics, Vol. 14 (2022), Iss. 4 : pp. 960–988
Published online: 2022-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 29
Keywords: Image segmentation Fischer-Burmeister total variation difference of convex algorithm sPADMM K-means method.
-
Difference of anisotropic and isotropic TV for segmentation under blur and Poisson noise
Bui, Kevin | Lou, Yifei | Park, Fredrick | Xin, JackFrontiers in Computer Science, Vol. 5 (2023), Iss.
https://doi.org/10.3389/fcomp.2023.1131317 [Citations: 2] -
A new difference of anisotropic and isotropic total variation regularization method for image restoration
Zhang, Benxin | Wang, Xiaolong | Li, Yi | Zhu, ZhibinMathematical Biosciences and Engineering, Vol. 20 (2023), Iss. 8 P.14777
https://doi.org/10.3934/mbe.2023661 [Citations: 1] -
An Efficient Smoothing and Thresholding Image Segmentation Framework with Weighted Anisotropic-Isotropic Total Variation
Bui, Kevin | Lou, Yifei | Park, Fredrick | Xin, JackCommunications on Applied Mathematics and Computation, Vol. 6 (2024), Iss. 2 P.1369
https://doi.org/10.1007/s42967-023-00339-w [Citations: 0]