Single infrared image super-resolution algorithm based on improved total generalized variation

Abstract

Keywords:
• infrared image super-resolution,
• total generalized variation(TGV),
• graduate sharpening operator,
• regularization

References

1. [1]

   FERSTL D,REINBACHER C,RANFTL R,et al.Image guided depth upsampling using anisotropic total generalized variation[C]//IEEE International Conference on Computer Vision.Piscataway:IEEE,2013:993.

2. [2]

   WERLBERGER M,TROBIN W,PORK T,et al.Anisotropic huber-L1 optical flow[C]//Proceedings of the British Machine Vision Conference.[S.l.:s.n.],2009:1.

3. [3]

   苏冰山,吴炜,杨晓敏,等.一种基于多传感器的红外图像正则化超分辨率算法[J].光电子激光,2015,26(2):368.
   

4. [4]

   KOVESI P.Phase congruency detects corners and edges[C]//Proceedings of Digital Image Computing:Techniques and Applications.Sydney:[s.n.],2003:309.

5. [5]

   苏冰山,陈继光,陈雨.基于改进总广义变分的红外图像超分辨率算法[J].电脑知识与技术,2019,15(22):193.
   

6. [6]

   戚曹,朱桂斌,唐鉴波,等.基于稀疏表示的红外视频图像超分辨率算法[J].计算机工程,2016,42(3):278.
   

7. [7]

   王新华,欧阳继红,庞武斌.压缩编码孔径红外成像超分辨重建[J].吉林大学学报(工学版),2016,46(4):1239.
   

8. [8]

   翟海天,李辉,李彬.基于区域划分的红外超分辨率重建[J].光学精密工程,2015,23(10):2989.
   

9. [9]

   PANAGIOTOPOULOU A,ANASTASSOPOULOS V.Super-resolution reconstruction of thermal infrared images[C]//Proceedings of the 4th WSEAS International Conference on REMOTE SENSING.[S.l.:s.n.],2011:40.

10. [10]

    WANG J,RALPH J F,GOULERMAS J Y.An analysis of a robust super resolution algorithm for infrared imaging[C]//Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis.Piscataway:IEEE,2009:158.

11. [11]

    KONGSKOV D R,DONG Y Q,KNUDSEN K.Directional total generalized variation regularization[J].BIT Numerical Mathematics,2019,59(4):903.

12. [12]

    ESSER E,ZHANG X Q,CHAN T F.A general framework for a class of first order primal-dual algorithms for convex optimization in imaging science[J].SIAM Journal on Imaging Sciences,2010,3(4):1015.

13. [13]

    CHAMBOLLE A,PORK T.A first-order primal-dual algorithm for convex problems with applications to imaging[J].Journal of Mathematical Imaging and Vision,2011,40:120.

Proportional views