Abstract
In recent years, SAR image processing plays a major role in coastal region monitoring through object identification for the betterment of the livelihood of sea shore people. In order to carry out the above said task, SAR images need to be analysed for extracting features which could be accomplished only after the removal of speckle noise. In this work, a new approach using Neuro-Fuzzy method is proposed for the removal of speckle noise. It is developed on fuzzy logic rule-based system. It is designed based on 3-input 1-output first order Sugeno type fuzzy inference system (FIS). The experimental analysis shows an effective performance of the proposed approach. The obtained results of the proposed approach are compared with results of the traditional approaches and it is proved that the NeuroFuzzy approach is giving better results compared with traditional methods.
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Singanamalla, V., Vaithyanathan, S. (2017). Neuro-Fuzzy Approach for Speckle Noise Reduction in SAR Images. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_23
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DOI: https://doi.org/10.1007/978-981-10-4859-3_23
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