تقرير
Neural shrinkage for wavelet-based SAR despeckling
| العنوان: | Neural shrinkage for wavelet-based SAR despeckling |
|---|---|
| المؤلفون: | Mastriani, Mario, Giraldez, Alberto E. |
| سنة النشر: | 2016 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | The wavelet shrinkage denoising approach is able to maintain local regularity of a signal while suppressing noise. However, the conventional wavelet shrinkage based methods are not time-scale adaptive to track the local time-scale variation. In this paper, a new type of Neural Shrinkage (NS) is presented with a new class of shrinkage architecture for speckle reduction in Synthetic Aperture Radar (SAR) images. The numerical results indicate that the new method outperforms the standard filters, the standard wavelet shrinkage despeckling method, and previous NS. Comment: 12 pages, 7 figures, 2 tables. arXiv admin note: text overlap with arXiv:1607.03105, arXiv:1608.00273, arXiv:1608.00270, arXiv:1608.00277 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1608.00279 |
| رقم الأكسشن: | edsarx.1608.00279 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |