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koosha--mohaddeseh
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Fine logarithmic adaptive soft morphological algorithm for synthetic aperture radar image segmentation
, Article IET Image Processing ; Volume 8, Issue 2 , 2014 , Pages 90-102 ; ISSN: 17519659 ; Hajsadeghi, K ; Koosha, M ; Sharif University of Technology
2014
Abstract
Synthetic aperture radar (SAR) appropriate image processing in conjunction with noise reduction is crucial in proper image segmentation. The authors present a new algorithm, logarithmic adaptive soft morphological (LASM) filter, utilising collectivity and flexibility of order-statistic soft morphological filters. This method not only reduces the speckle noise of the single-look SAR imagery considerably, but it significantly enhances the segmentation results. To verify the performance, a simulated SAR image is first created by applying an imagery method to an original noiseless image. The resulting image has characteristics identical to a real SAR image. The LASM method, as well as several...
Speckle Noise Reduction Using Adaptive Filters with Application to SAR Images
, M.Sc. Thesis Sharif University of Technology ; Hajsadeghi, Khosrow (Supervisor)
Abstract
SAR image noise is a significant problem for SAR image analysis.The inherent noise of SAR images, known as speckle, seriously affects the SAR image interpretation. It also has adverse effects on the classification and segmentation of SAR images. Due to its great significance, the SAR image processing has received considerable attention in recent years and many researchers have developed techniques to reduce the inherent noise accompanying the SAR images. A survey of the literature shows that the wavelet analysis is one of the most common methods used for speckle reduction. While the power of the morphological analysis method has mostly not been recognized, we have utilized this efficient...