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International Journal of Computer Mathematics Volume 90, 2013 - Issue 1: VARIATIONAL IMAGE PROCESSING MODELS AND APPLICATIONS
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Original Articles

A fast minimization method for blur and multiplicative noise removal

Fan Wang Department of Mathematics, Centre for Mathematical Imaging and Vision, Hong Kong Baptist University, Kowloon Tong, Hong Kong
&
Michael K. Ng Department of Mathematics, Centre for Mathematical Imaging and Vision, Hong Kong Baptist University, Kowloon Tong, Hong Kong; School of Mathematics and Statistics, Lanzhou University, Gausu, ChinaCorrespondence[email protected]
Pages 48-61 | Received 16 Nov 2011, Accepted 03 Apr 2012, Published online: 29 May 2012

Citations (17)

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Read on this site (5)

Chunyan Li & Qibin Fan. (2018) Multiplicative noise removal via combining total variation and wavelet frame. International Journal of Computer Mathematics 95:10, pages 2036-2055.
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Hamid Esmaeili, Majid Rostami & Morteza Kimiaei. (2018) Combining line search and trust-region methods for -minimization. International Journal of Computer Mathematics 95:10, pages 1950-1972.
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Hong Deng, Wangmeng Zuo, Hongzhi Zhang & David Zhang. (2014) An additive convolution model for fast restoration of nonuniform blurred images. International Journal of Computer Mathematics 91:11, pages 2446-2466.
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Yu Han, Chen Xu, George Baciu & Xiangchu Feng. (2014) Multiplicative noise removal combining a total variation regularizer and a nonconvex regularizer. International Journal of Computer Mathematics 91:10, pages 2243-2259.
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Ke Chen. (2013) Introduction to variational image-processing models and applications. International Journal of Computer Mathematics 90:1, pages 1-8.
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Articles from other publishers (12)

Suman Kumar Maji & Ramesh Kumar Thakur. (2022) A Successive Variational Model for Multiplicative Noise and Blur Removal. A Successive Variational Model for Multiplicative Noise and Blur Removal.
Chunyan Li, Baoguang Sun & Liming Tang. (2022) A nonconvex hybrid regularization model for restoring blurred images with mixed noises. Digital Signal Processing 130, pages 103734.
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Wei Wang, Mingjia Yao & Michael K. Ng. (2021) Color image multiplicative noise and blur removal by saturation-value total variation. Applied Mathematical Modelling 90, pages 240-264.
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Chunyan Li, Zemin Ren & Liming Tang. (2020) Multiplicative noise removal via using nonconvex regularizers based on total variation and wavelet frame. Journal of Computational and Applied Mathematics 370, pages 112684.
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Ramesh Kumar Thakur & Suman Kumar Maji. (2020) A Variational Approach to Image Despeckling under Varied Blur. A Variational Approach to Image Despeckling under Varied Blur.
Kshitij Susheel Jauhri, Ramesh Kumar Thakur & Suman Kumar Maji. (2020) A Blind Metric Based Variational Approach for Ultrasound Image Denoising. A Blind Metric Based Variational Approach for Ultrasound Image Denoising.
Tingting Wu, Wei Li, Lihua Li & Tieyong Zeng. (2020) A Convex Variational Approach for Image Deblurring With Multiplicative Structured Noise. IEEE Access 8, pages 37790-37807.
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Chunyan Li & Qibin Fan. (2017) A Modified Variational Model for Restoring Blurred Images with Additive Noise and Multiplicative Noise. Circuits, Systems, and Signal Processing 37:6, pages 2511-2534.
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Asmat Ullah, Wen Chen, Mushtaq Ahmad Khan & HongGuang Sun. (2017) A New Variational Approach for Multiplicative Noise and Blur Removal. PLOS ONE 12:1, pages e0161787.
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Fan Wang, Xi-Le Zhao & Michael K. Ng. (2016) Multiplicative Noise and Blur Removal by Framelet Decomposition and <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math> </inline-formula>-Based L-Curve Method. IEEE Transactions on Image Processing 25:9, pages 4222-4232.
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De-Yong Lu. (2016) A hybrid optimization method for multiplicative noise and blur removal. Journal of Computational and Applied Mathematics 302, pages 224-233.
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Xi-Le Zhao, Fan Wang & Michael K. Ng. (2014) A New Convex Optimization Model for Multiplicative Noise and Blur Removal. SIAM Journal on Imaging Sciences 7:1, pages 456-475.
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