AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Tran, T. T. T.^1¹  Pham, C. T.^2²  Kopylov, A. V.^3³ 

[1] The University of Danang-University of Economics, 71 Ngu Hanh Son, Danang, Viet Nam^1;The University of Danang-University of Science and Technology, 54 Nguyen Luong Bang, Danang, Viet Nam^2;Tula State University, 92 Lenin Ave., Tula, Russia^3

关键词: Adaptive model;    Medical image denoising;    Mixed noise;    Total variation;    Laplacian regularizer;    Split Bregman;   

DOI  :  10.5194/isprs-archives-XLII-2-W12-219-2019

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

Image denoising is one of the important tasks required by medical imaging analysis. In this work, we investigate an adaptive variation model for medical images restoration. In the proposed model, we have used the first-order total variation combined with Laplacian regularizer to eliminate the staircase effect in the first-order TV model while preserve edges of object in the piecewise constant image. We also propose an instance of Split Bregman method to solve the proposed denoising model as an optimization problem. Experimental results from mixed Poisson-Gaussian noise are given to demonstrate that our proposed approach outperforms the related methods.

【 授权许可】

CC BY