| Autor: |
Min, Lihua, Lian, Xiaoyu, Jin, Zhengmeng, Zheng, Minling |
| Zdroj: |
Journal of Mathematical Imaging & Vision; Jun2023, Vol. 65 Issue 3, p437-452, 16p |
| Abstrakt: |
It is often challenging to selectively segment the images with intensity inhomogeneity for the existing region-based variational models. This article proposes a Retinex-based selective segmentation model for inhomogeneous images. The main idea is to employ the Retinex theory to decouple the input inhomogeneous image into illumination bias and reflective parts and then introduce the regularizer of these two parts in the proposed model for selective segmentation. Also, a convex formulation of the model is presented and the relationship between the solutions of the proposed model and its convex relaxation is given. Furthermore, we design an effective algorithm for numerically solving the model by incorporating the alternating minimization method. Experimental results on synthetic binary images and real medical images validate the performance of the proposed method. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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