FTVd

FTVd: A Fast Algorithm for Total Variation based Deconvolution. FTVd refers to Fast Total Variation (TV) deconvolution, and is a TV based deconvolution / denoising package. The latest package includes fast solvers for the TV/L2 and TV/L1 models, which are compatible with both grayscale and color images. FTVd can be easily modified to work with three and higher dimensional image/data.


References in zbMATH (referenced in 59 articles )

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  1. Liu, Xiaoman; Liu, Jijun: Image restoration from noisy incomplete frequency data by alternative iteration scheme (2020)
  2. Shen, Yuan; Liu, Xin: An alternating minimization method for matrix completion problems (2020)
  3. Kang, Myeongmin; Kang, Myungjoo; Jung, Miyoun: Sparse representation based image deblurring model under random-valued impulse noise (2019)
  4. Lee, Chang-Ock; Nam, Changmin; Park, Jongho: Domain decomposition methods using dual conversion for the total variation minimization with (L^1) fidelity term (2019)
  5. Lu, Jian; Qiao, Ke; Li, Xiaorui; Lu, Zhaosong; Zou, Yuru: (\ell_0)-minimization methods for image restoration problems based on wavelet frames (2019)
  6. Lu, Jian; Tian, Jiapeng; Shen, Lixin; Jiang, Qingtang; Zeng, Xueying; Zou, Yuru: Rician noise removal via a learned dictionary (2019)
  7. Shen, Yuan; Ji, Lei: Partial convolution for total variation deblurring and denoising by new linearized alternating direction method of multipliers with extension step (2019)
  8. Zhang, Xiongjun; Ng, Michael K.: A fast algorithm for solving linear inverse problems with uniform noise removal (2019)
  9. Cui, Zhuo-Xu; Fan, Qibin: A “Nonconvex(+)nonconvex” approach for image restoration with impulse noise removal (2018)
  10. Gao, Yiming; Liu, Fang; Yang, Xiaoping: Total generalized variation restoration with non-quadratic fidelity (2018)
  11. Lu, Jian; Yang, Zeping; Shen, Lixin; Lu, Zhaosong; Yang, Hanmei; Xu, Chen: A framelet algorithm for de-blurring images corrupted by multiplicative noise (2018)
  12. Zhang, Xiongjun; Ng, Michael K.; Bai, Minru: A fast algorithm for deconvolution and Poisson noise removal (2018)
  13. Jiang, Dandan: A multi-parameter regularization model for deblurring images corrupted by impulsive noise (2017)
  14. Jia, Zhi-Gang; Wei, Musheng: A new TV-Stokes model for image deblurring and denoising with fast algorithms (2017)
  15. Jung, Yoon Mo; Jeong, Taeuk; Yun, Sangwoon: Non-convex TV denoising corrupted by impulse noise (2017)
  16. Ma, Liyan; Zeng, Tieyong; Li, Gongyan: Hybrid variational model for texture image restoration (2017)
  17. Yang, Jiao; Dai, Yi-Qing; Peng, Zheng; Zhuang, Jie-Peng; Zhu, Wen-Xing: A homotopy alternating direction method of multipliers for linearly constrained separable convex optimization (2017)
  18. Yang, Xiaojuan; Wang, Li: Fast half-quadratic algorithm for image restoration and reconstruction (2017)
  19. Zhang, Xiongjun; Bai, Minru; Ng, Michael K.: Nonconvex-TV based image restoration with impulse noise removal (2017)
  20. Chen, Chong; Xu, Guoliang: A new linearized split Bregman iterative algorithm for image reconstruction in sparse-view X-ray computed tomography (2016)

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