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 41 articles )

Showing results 1 to 20 of 41.
Sorted by year (citations)

1 2 3 next

  1. Jiang, Dandan: A multi-parameter regularization model for deblurring images corrupted by impulsive noise (2017)
  2. Jia, Zhi-Gang; Wei, Musheng: A new TV-Stokes model for image deblurring and denoising with fast algorithms (2017)
  3. Jung, Yoon Mo; Jeong, Taeuk; Yun, Sangwoon: Non-convex TV denoising corrupted by impulse noise (2017)
  4. Ma, Liyan; Zeng, Tieyong; Li, Gongyan: Hybrid variational model for texture image restoration (2017)
  5. Zhang, Xiongjun; Bai, Minru; Ng, Michael K.: Nonconvex-TV based image restoration with impulse noise removal (2017)
  6. König, Claudia; Werner, Frank; Hohage, Thorsten: Convergence rates for exponentially ill-posed inverse problems with impulsive noise (2016)
  7. Ma, Liyan; Zeng, Tieyong: Image deblurring via total variation based structured sparse model selection (2016)
  8. Qian, Qinchun; Gunturk, Bahadir K.: Blind super-resolution restoration with frame-by-frame nonparametric blur estimation (2016)
  9. Shen, Yuan; Wang, Hongyong: New augmented Lagrangian-based proximal point algorithm for convex optimization with equality constraints (2016)
  10. Li, Qia; Shen, Lixin; Xu, Yuesheng; Zhang, Na: Multi-step fixed-point proximity algorithms for solving a class of optimization problems arising from image processing (2015)
  11. Sciacchitano, Federica; Dong, Yiqiu; Zeng, Tieyong: Variational approach for restoring blurred images with Cauchy noise (2015)
  12. Aybat, Necdet Serhat; Goldfarb, Donald; Ma, Shiqian: Efficient algorithms for robust and stable principal component pursuit problems (2014)
  13. Chen, Feishe; Shen, Lixin; Xu, Yuesheng; Zeng, Xueying: The Moreau envelope approach for the L1/TV image denoising model (2014)
  14. Shen, Yuan; Zhang, Wenxing; He, Bingsheng: Relaxed augmented Lagrangian-based proximal point algorithms for convex optimization with linear constraints (2014)
  15. Shen, Y.; Wen, Z.; Zhang, Y.: Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization (2014)
  16. Whyte, Oliver; Sivic, Josef; Zisserman, Andrew: Deblurring shaken and partially saturated images (2014) ioport
  17. Chan, Raymond H.; Tao, Min; Yuan, Xiaoming: Constrained total variation deblurring models and fast algorithms based on alternating direction method of multipliers (2013)
  18. Chan, R.H.; Lanza, A.; Morigi, S.; Sgallari, F.: An adaptive strategy for the restoration of textured images using fractional order regularization (2013)
  19. Micchelli, Charles A.; Shen, Lixin; Xu, Yuesheng; Zeng, Xueying: Proximity algorithms for the L1/TV image denoising model (2013)
  20. Mu, Xuewen; Zhang, Yaling: An alternating direction method for second-order conic programming (2013)

1 2 3 next