Total Variation (TV) l1 Norm Minimization Based Limited Data X-ray CT Image Reconstruction
Source abstract
Abstract
Limited data CT Image reconstruction is a real-life problem. A Total Variation (TV) l1 norm minimization technique has been examined and validated here to reconstruct CT images from limited data incorporating a limited number of views along with limited angular span, a situation typical in engineering applications. The Lagrangian technique has been used to solve TV equations. The reconstructed CT image has been compared with the images reconstructed by SIRT, Higher Order TV (HOTV) technique, l2 norm minimization based technique and some other techniques with the help of various image quality index (IQI) parameters. The comparison shows that the proposed scheme is an attractive solution for limited data CT Image reconstruction from industrial and engineering perspective. The application of Sobolev space error analysis has also been given to ensure good global reconstruction.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Medical Imaging Techniques and Applications · Advanced X-ray and CT Imaging · Image and Signal Denoising Methods
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Nuclear Engineering & Technology Programme, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India
References (44)
Show source-provided references
1. 10.1080/09349847.2010.53483610.1080/09349847.2010.534836 ↗
2. 10.1109/42.12691110.1109/42.126911 ↗
3. 10.1080/0934984990940964210.1080/09349849909409642 ↗
4. 10.1063/1.500092810.1063/1.5000928 ↗
5. 10.18576/amis/10060210.18576/amis/100602 ↗
6. 10.1016/j.patcog.2013.02.00810.1016/j.patcog.2013.02.008 ↗
7. 10.1007/s11694-008-9059-810.1007/s11694-008-9059-8 ↗
8. Sarkar S. · 2015
9. 10.1063/1.496202310.1063/1.4962023 ↗
10. 10.1016/j.combustflame.2014.08.02010.1016/j.combustflame.2014.08.020 ↗
11. 10.1016/S0196-8858(03)00099-X10.1016/S0196-8858(03)00099-X ↗
12. 10.1109/83.19992010.1109/83.199920 ↗
13. 10.1364/JOSAA.1.00061210.1364/JOSAA.1.000612 ↗
14. 10.1016/j.ndteint.2014.09.01210.1016/j.ndteint.2014.09.012 ↗
15. 10.1259/0007-1285-46-552-101610.1259/0007-1285-46-552-1016 ↗
16. 10.1016/0022-5193(70)90109-810.1016/0022-5193(70)90109-8 ↗
17. 10.1080/10407799927585710.1080/104077999275857 ↗
18. 10.1080/09349847.2013.79563510.1080/09349847.2013.795635 ↗
19. 10.1029/JB095iB08p1255310.1029/JB095iB08p12553 ↗
20. 10.1109/42.2036010.1109/42.20360 ↗
21. 10.1088/0031-9155/53/17/02110.1088/0031-9155/53/17/021 ↗
22. 10.1088/0266-5611/24/4/04501110.1088/0266-5611/24/4/045011 ↗
23. 10.1109/TMI.2011.217523310.1109/TMI.2011.2175233 ↗
24. 10.1007/BF0214976110.1007/BF02149761 ↗
25. 10.1080/09349847.2015.106065910.1080/09349847.2015.1060659 ↗
26. 10.1016/j.ultramic.2016.12.02010.1016/j.ultramic.2016.12.020 ↗
27. 10.1007/s10589-013-9576-110.1007/s10589-013-9576-1 ↗
28. 10.1137/04061507910.1137/040615079 ↗
29. 10.1016/j.apm.2011.07.05510.1016/j.apm.2011.07.055 ↗
30. Li X. · IEEE Trans. Syst. Man Cybern. B · 2009 · 40 · 1170
31. 10.5201/ipol.2012.g-tvd10.5201/ipol.2012.g-tvd ↗
32. 10.1088/0266-5611/7/3/00710.1088/0266-5611/7/3/007 ↗
33. 10.1016/0963-8695(92)90160-I10.1016/0963-8695(92)90160-I ↗
34. 10.1016/0963-8695(93)90353-V10.1016/0963-8695(93)90353-V ↗
35. Munshi P. · Mater. Eval. Feb. · 1997 · 55 · 188
36. Munshi P. · Eur. J. NDT · 1994 · 3 · 104
37. 10.1080/09349847.2014.94472510.1080/09349847.2014.944725 ↗
38. 10.1098/rsta.2014.039410.1098/rsta.2014.0394 ↗
39. 10.1109/TIP.2011.210973010.1109/TIP.2011.2109730 ↗
40. Reisenhofer R. · Signal Process. · 2018 · 61 · 33
41. 10.1109/TIP.2013.229342310.1109/TIP.2013.2293423 ↗
42. 10.1088/0031-9155/57/10/306510.1088/0031-9155/57/10/3065 ↗
43. 10.1088/0031-9155/58/7/211910.1088/0031-9155/58/7/2119 ↗
44. 10.1016/j.ndteint.2018.11.00910.1016/j.ndteint.2018.11.009 ↗