Accelerated Split Bregman Method for Image Compressive Sensing Recovery under Sparse Representation

AbstractIn this paper, we propose a new projection method for solving a general minimization problems with twoL1-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rateO(k−2). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.

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L p Regularization for Bioluminescence Tomography Based on the Split Bregman Method

Molecular Imaging and Biology ◽

10.1007/s11307-016-0970-9 ◽

2016 ◽

Vol 18 (6) ◽

pp. 830-837 ◽

Cited By ~ 7

Author(s):

Yifang Hu ◽

Jie Liu ◽

Chengcai Leng ◽

Yu An ◽

Shuang Zhang ◽

...

Keyword(s):

Split Bregman Method ◽

Split Bregman ◽

Bioluminescence Tomography

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A variational model based on split Bregman method for multiplicative noise removal

AEU - International Journal of Electronics and Communications ◽

10.1016/j.aeue.2015.05.009 ◽

2015 ◽

Vol 69 (9) ◽

pp. 1291-1296 ◽

Cited By ~ 15

Author(s):

Yan Hao ◽

Jianlou Xu ◽

Shuaijie Li ◽

Xuande Zhang

Keyword(s):

Multiplicative Noise ◽

Noise Removal ◽

Variational Model ◽

Split Bregman Method ◽

Split Bregman ◽

Model Based ◽

Multiplicative Noise Removal

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Holographic Microwave Imaging for Breast Cancer Detection Based on Compressive Sensing

Volume 3: Biomedical and Biotechnology Engineering ◽

10.1115/imece2017-70063 ◽

2017 ◽

Author(s):

Lulu Wang ◽

Hu Peng

Keyword(s):

Breast Cancer ◽

Compressive Sensing ◽

Cancer Detection ◽

Imaging System ◽

Measurement Data ◽

Operation Time ◽

Microwave Imaging ◽

Breast Cancer Detection ◽

Split Bregman ◽

Small Breast

Microwave imaging (MI) has been considered as an alternative way to X-ray mammography for breast cancer detection. This paper presents a compressive sensing based holographic microwave imaging (CS-HMI) approach for diagnosing of breast cancer. A numerical imaging system is developed to validate the proposed CS-HMI approach, which includes a realistic human breast phantom and measurement model. Small breast tumour can be detected in the reconstructed CS-HMI image via Split Bregman (SB) with using 10% measurement data. Simulation and experimental results show that CS-HMI has the ability to produce high quality image by using significantly less measurement data and operation time.

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