基于小波变换和维纳滤波的SAR图像去噪

Priyanka S. Tondewad, M. Dale
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引用次数: 0

摘要

噪声是图像中不需要的信号。散斑噪声通常存在于合成孔径雷达(SAR)、超声波或任何有源雷达传感器图像中。这种噪音限制了信息的解释。该方法首先应用频域方法去除高频噪声,然后应用空间域滤波器实现。我们已经演示了各种基于转换的方法。频域方法便于使用单独的频带进行处理。结果表明,基于平稳小波变换的方法更有效。与传统的散斑去噪滤波器相比,视觉质量得到了提高,并改进了峰值信噪比(PSNR)、等效外观数(ENL)、相似指数测度(SSIM)、散斑抑制指数(SSI)和结构等定性参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Denoising of SAR Images using Wavelet Transforms and Wiener Filter
Noise is unwanted signal present in the image. Speckle noise is usually present in Synthetic Aperture Radar (SAR), ultrasound or any active radar sensor images. This noise limits the information interpretation. The proposed novel method is realized by first applying frequency domain methods for high frequency noise removal and then applying spatial domain filters. We have demonstrated various transform-based methods. Frequency domain methods gives ease to use separate bands for processing. Stationary Wavelet transform based method proves to be more efficient. Visual quality is improved as compared to the traditional speckle noise removal filters also the qualitative parameters like Peak Signal-to-Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Similarity Index Measure (SSIM) and Speckle Suppression Index (SSI) and Structural are improved.
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