تقرير
Kalman's shrinkage for wavelet-based despeckling of SAR images
| العنوان: | Kalman's shrinkage for wavelet-based despeckling of SAR images |
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| المؤلفون: | Mastriani, Mario, Giraldez, Alberto E. |
| سنة النشر: | 2016 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman's filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman's filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images. Comment: 7 pages, 1 figure, 1 table. arXiv admin note: substantial text overlap with arXiv:1607.03105, arXiv:1608.00270, arXiv:1608.00279, arXiv:1608.00277, arXiv:1608.00274 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1608.00273 |
| رقم الأكسشن: | edsarx.1608.00273 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |