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Fractional Order Variational Approach for Image Denoising and CT Reconstruction

Authors:
Suhua Wei
Linghai Kong

Keywords: image denoising; total variation; fractional order; CT; image reconstruction

Abstract:
Image denoising is a fundamental problem in the area of image processing. The widely applications make it very important to research. Variational method is an efficient way to restore images corrupted by noises. In this paper, we propose a variational model to deal with Gaussian noise and mixed noise. In the proposed model, we use the combination of Total Variation (TV) and Fractional order Total Variation (FTV) as the regularization term. Numerical results show that the proposed model has advantages on recovering image edges and textures. We also generalize our approach to CT image reconstruction by fan beam X-rays from a single radiograph. By a single radiograph, we can reconstruct an axially symmetric object image. The variational model and the algorithm to solve it will be given, and the efficiency of the proposed method will be illustrated by numerical tests.

Pages: 4 to 5

Copyright: Copyright (c) IARIA, 2024

Publication date: March 10, 2024

Published in: conference

ISSN: 2519-8432

ISBN: 978-1-68558-142-8

Location: Athens, Greece

Dates: from March 10, 2024 to March 14, 2024