Speckle Noise Reduction in SAR Images Using Fuzzy Inference System

Vijayakumar Singanamalla, Santhi Vaithyanathan
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引用次数: 2

Abstract

In recent years, image processing has played a vital role in major research areas. In this article, a new approach using a fuzzy inference system is proposed for speckle reduction in SAR images. In general, SAR images are predominantly used to monitor coastal regions to detect oil spills, ship wake, sea shores and climate changes. In this article, a gamma distribution model is used in a fuzzy inference system to remove speckle noise from SAR images. The performance of the proposed model is tested using fuzzy inference systems, such as mamdani and sugeno. The experimental results proved the efficiency of the proposed system through objective metrics.
基于模糊推理系统的SAR图像散斑降噪
近年来,图像处理在各大研究领域发挥着至关重要的作用。本文提出了一种利用模糊推理系统对SAR图像进行斑点抑制的新方法。一般来说,SAR图像主要用于监测沿海地区,以探测石油泄漏、船舶尾流、海岸和气候变化。本文将伽玛分布模型应用于模糊推理系统中,以去除SAR图像中的散斑噪声。利用模糊推理系统(如mamdani和sugeno)对该模型的性能进行了测试。实验结果通过客观指标证明了系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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