The NSCT-NLmeans Based CS Reconstruction for Noisy Image
Sparsity was prior condition in compressed sensing which had been widely concerned in signal reconstruction. Meanwhile nonsubsampled contourlet proposed as a development to contourlet, not only provided flexible multi-scale, multi-direction sparse image decomposition but also featured with shift-inv...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2014-09-01.
|
| Subjects: | |
| Online Access: | Get fulltext |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Sparsity was prior condition in compressed sensing which had been widely concerned in signal reconstruction. Meanwhile nonsubsampled contourlet proposed as a development to contourlet, not only provided flexible multi-scale, multi-direction sparse image decomposition but also featured with shift-invariance property which was beneficial to image denoising. This paper combined threshold operator in nonsubsampled contourlet domain with non local means filter for image denoising in the compressed sensing framework. Therefore, NSCT-NLmeans based compressed sensing reconstruction was proposed for noisy image. The experiment results showed that NSCT- NLmeans based algorithm outperformed the other multi-resolution and multi-directional transforms in recovering and denoising image simultaneously. |
|---|---|
| Item Description: | https://ijeecs.iaescore.com/index.php/IJEECS/article/view/3817 |