NDLI: NSST and vector-valued C–V model based image segmentation algorithm

Content Provider	IET Digital Library
Author	Wang, Xianghai Zhao, Xiaoyang Zhu, Yihuan Su, Xin
Abstract	Image segmentation is a process of partitioning an image into non-overlapping regions. Existing unsupervised image segmentation methods include level set, automatic thresholding and region-based CV mode and so on. However, image segmentation as a key technology in the field of image processing has not been solved indeed, especially for images with complex texture. For this reason, the authors proposed a novel image segmentation algorithm based on NSST and the vector-valued Chan–Vese (C–V) model. First, they obtained a multi-scale representation by exploiting the non-subsampled shearlet transform (NSST) to extract multi-dimensional data in the image. Afterwards, they gave the vector-valued C–V model, and applied it to all subbands of NSST, which are treated as a vector-valued image. By comparing with other class methods, the experimental results show that the proposed method has better visual effects and lower error rates. But at the same time, it is a little time consuming. The proposed method is reasonable and effective, by taking full advantages of each subband's directional information during its diffusion process, compared with traditional C–V model.
Starting Page	1614
Ending Page	1620
Page Count	7
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 8, Jun (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5027
Journal	IET Image Processing
Publisher Date	2020-03-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Thresholding Computer Vision And Image Processing Technique Diffusion Process Image Fusion Image Processing Image Segmentation Image Segmentation Algorithm Integral Transforms Nonoverlapping Region Nonsubsampled Shearlet Transform NSST Optical, Image And Video Signal Processing Transform Unsupervised Image Segmentation Method Vector-valued C-V Model Vector-valued Chan-Vese Model Vector-valued Image Visual Effect
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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