Speckle Removal from SAR Images in the Lapped Transform Domain Using Adaptive Threshold Based on Despeckling Evaluation Indexes
Speckle Removal from SAR Images in the Lapped Transform Domain Using Adaptive Threshold Based on Despeckling Evaluation Indexes
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DOI：
10.1016/j.procs.2016.05.141
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发表时间：
2016
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影响因子：
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通讯作者：
D. Hazarika;V. K. Nath;M. Bhuyan
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文献类型：
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作者：
D. Hazarika;V. K. Nath;M. Bhuyan
我们在本文中提出了一种基于重叠变换（LT）的有效自适应阈值估计方法，用于抑制合成孔径雷达（SAR）图像中的散斑。重叠正交变换 (LOT) 对过度平滑具有鲁棒性，可以更好地保留纹理分量，并且比正交离散小波变换 (DWT) 具有更低的计算复杂度。由于LOT是块变换，因此首先进行变换系数的二元重映射，然后对子带系数进行阈值化。我们使用两个去斑性能指标（即等效外观数（ENL）和边缘节省指数（ESI））来估计“最佳”阈值。然后在软阈值函数中使用阈值来缩小噪声 LOT 系数。由于在阈值估计中使用了去散斑性能指标，在真实SAR图像上的测试表明，该方法对散斑的抑制效果显着，且边缘保持良好，取得了比其他相关方法更好的性能。
We propose in this paper an efficient and adaptive threshold estimation method for suppressing speckle in synthetic aperture radar (SAR) images, based on Lapped transform (LT). Lapped orthogonal transform (LOT) is robust to oversmoothing, can preserve texture components better and has less computational complexity than orthogonal discrete wavelet transform (DWT). Since LOT is block transform, the dyadic remapping of transform coefficients are carried out first and then the subband coefficients are thresholded. We estimate the ‘optimal’ threshold value using two despeckling performance indexes namely equivalent number of looks (ENL) and edge saving index (ESI). The threshold value is then used in soft thresholding function to shrink the noisy LOT coefficients. Due to the use of despeckling performance indexes in threshold estimation, the test on real SAR images show that the proposed method notably suppresses speckle with good edge preservation and achieves better performance than other related methods.