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Speckle Noise Reduction Using Adaptive Filters with Application to SAR Images

Koosha, Mohaddeseh | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 43711 (55)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Hajsadeghi, Khosrow
  7. Abstract:
  8. 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 method and have designed our filter in such a way which has improved the segmentation results of the SAR images decisively. The proposed filter can be equally well applied to both main classes of SAR images, namely the amplitude and intensity images, whereas, most of the conventional filters focus only on one of the classes. Finally, the results are compared with the best-known filters commonly used for speckle noise reduction. To better evaluate the results, a SAR imagery method has also been presented. Presenting a precise evaluation is one of our main concerns, so a number of general and non-general criteria are applied to the results. The non-general criteria, which are proposed in this thesis, are claimed to be as effective as the other common criteria used in the field of speckle assessment. The evaluations illustrate that mathematical morphology can provide robust optimization for SAR despeckling
  9. Keywords:
  10. Speckle Noise ; Image Segmentation ; Synthetic Aperture Radar (SAR) ; Adaptive Filters

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