Name
Abstract | ||
|---|---|---|
In this paper, a novel remote sensing image enhancement technique based on a non-local means filter in a nonsubsampled contourlet transform (NSCT) domain is proposed. The overall flow of the approach can be divided into the following steps: Firstly, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands with NSCT. Secondly, contrast stretching is adopted to deal with the low-frequency sub-band coefficients, and the non-local means filter is applied to suppress the noise contained in the first high-frequency sub-band coefficients. Thirdly, the processed coefficients are reconstructed with the inverse NSCT transform. Finally, the unsharp filter is used to enhance the details of the image. The simulation results show that the proposed algorithm has better performance in remote sensing image enhancement than the existing approaches. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.3390/a10040116 | ALGORITHMS |
Keywords | Field | DocType |
NSCT,contrast stretching,non-local means filter,unsharp filter | Normalization (image processing),Computer vision,Inverse,Non-local means,Remote sensing,Artificial intelligence,Mathematics,Contourlet | Journal |
Volume | Issue | ISSN |
10 | 4 | 1999-4893 |
Citations | PageRank | References |
1 | 0.35 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liangliang Li | 1 | 1 | 0.69 |
| Yujuan Si | 2 | 13 | 4.64 |
| Zhenhong Jia | 3 | 29 | 15.13 |