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Volume 12, Issue 2
A coupling segmentation method based on CV model for highnoise image

Kai Cai

J. Info. Comput. Sci. , 12 (2017), pp. 130-140.

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  • Abstract
For image segmentation methods, a clear image is often the object. High-quality segmentation is possible in many experiments. However, in the actual image, noise is inevitable. Many segmentation methods for high-noise images are not satisfactory. This paper puts forward a method of image coupling denoising and segmentation for high-noise image. A new variational model is adopted, then the denoised image is segmented using the improved CV model. The numerical calculation uses multiple directions difference to approximate the partial derivative, obtaining a rapid and stable effect. The experimental results show that the proposed coupling denoising and segmentation method could demonstrate validity. Where the image’s, high noise is concerned, segmentation is obviously superior to the Li’s[15] model.
  • Keywords

image segmentation high noise denoising coupling model CV model.

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COPYRIGHT: © Global Science Press

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@Article{JICS-12-130, author = {Kai Cai}, title = {A coupling segmentation method based on CV model for highnoise image}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {12}, number = {2}, pages = {130--140}, abstract = {For image segmentation methods, a clear image is often the object. High-quality segmentation is possible in many experiments. However, in the actual image, noise is inevitable. Many segmentation methods for high-noise images are not satisfactory. This paper puts forward a method of image coupling denoising and segmentation for high-noise image. A new variational model is adopted, then the denoised image is segmented using the improved CV model. The numerical calculation uses multiple directions difference to approximate the partial derivative, obtaining a rapid and stable effect. The experimental results show that the proposed coupling denoising and segmentation method could demonstrate validity. Where the image’s, high noise is concerned, segmentation is obviously superior to the Li’s[15] model. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22489.html} }
TY - JOUR T1 - A coupling segmentation method based on CV model for highnoise image AU - Kai Cai JO - Journal of Information and Computing Science VL - 2 SP - 130 EP - 140 PY - 2024 DA - 2024/01 SN - 12 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22489.html KW - image segmentation KW - high noise KW - denoising KW - coupling model KW - CV model. AB - For image segmentation methods, a clear image is often the object. High-quality segmentation is possible in many experiments. However, in the actual image, noise is inevitable. Many segmentation methods for high-noise images are not satisfactory. This paper puts forward a method of image coupling denoising and segmentation for high-noise image. A new variational model is adopted, then the denoised image is segmented using the improved CV model. The numerical calculation uses multiple directions difference to approximate the partial derivative, obtaining a rapid and stable effect. The experimental results show that the proposed coupling denoising and segmentation method could demonstrate validity. Where the image’s, high noise is concerned, segmentation is obviously superior to the Li’s[15] model.
Kai Cai. (2024). A coupling segmentation method based on CV model for highnoise image. Journal of Information and Computing Science. 12 (2). 130-140. doi:
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