AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION

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 stairc...

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Main Authors: T. T. T. Tran, C. T. Pham, A. V. Kopylov, V. N. Nguyen
Format: Article
Language:English
Published: Copernicus Publications 2019-05-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W12/219/2019/isprs-archives-XLII-2-W12-219-2019.pdf
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author T. T. T. Tran
C. T. Pham
A. V. Kopylov
V. N. Nguyen
author_facet T. T. T. Tran
C. T. Pham
A. V. Kopylov
V. N. Nguyen
author_sort T. T. T. Tran
collection DOAJ
description 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.
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spelling doaj.art-e520070b315a4b218e47564e78a3cbe52022-12-22T01:41:28ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-05-01XLII-2-W1221922410.5194/isprs-archives-XLII-2-W12-219-2019AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATIONT. T. T. Tran0C. T. Pham1A. V. Kopylov2V. N. Nguyen3The University of Danang-University of Economics, 71 Ngu Hanh Son, Danang, Viet NamThe University of Danang-University of Science and Technology, 54 Nguyen Luong Bang, Danang, Viet NamTula State University, 92 Lenin Ave., Tula, RussiaThe University of Danang-University of Science and Technology, 54 Nguyen Luong Bang, Danang, Viet NamImage 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.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W12/219/2019/isprs-archives-XLII-2-W12-219-2019.pdf
spellingShingle T. T. T. Tran
C. T. Pham
A. V. Kopylov
V. N. Nguyen
AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
title_full AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
title_fullStr AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
title_full_unstemmed AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
title_short AN ADAPTIVE VARIATIONAL MODEL FOR MEDICAL IMAGES RESTORATION
title_sort adaptive variational model for medical images restoration
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W12/219/2019/isprs-archives-XLII-2-W12-219-2019.pdf
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