Adaptive neuro-fuzzy inference system for speckle noise reduction in SAR images

An adaptive neuro-fuzzy inference system (ANFIS) based method is proposed for speckle noise reduction in synthetic aperture radar (SAR) images. Before using active RADAR (radio detection and ranging) and SAR imageries, the very first step is to reduce the effect of speckle noise. Reduction of speckl...

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Bibliographic Details
Main Authors: Basturk, A., Emin Yuksel, M.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive optics
Adaptive systems
Image converters
Noise reduction
Optical surface waves
Radar imaging
Radar remote sensing
Remote sensing
Speckle
Synthetic aperture radar
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Summary:An adaptive neuro-fuzzy inference system (ANFIS) based method is proposed for speckle noise reduction in synthetic aperture radar (SAR) images. Before using active RADAR (radio detection and ranging) and SAR imageries, the very first step is to reduce the effect of speckle noise. Reduction of speckle noise is one of the most important processes to increase the quality of radar coherent images. Filtering is the common method which is used to reduce the speckle noise. For this purpose, two ANFISs are trained and outputs of these systems are converted to one output through a mean calculator in this work. Performance of the proposed method is compared with performances of state-of-the-art methods in the literature for speckle noise reduction. Results are presented by filtered images and a table.
DOI:10.1109/ISSPA.2007.4555350