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首页> 外文会议>International Conference on Circuits, Systems and Simulation >An Adaptive Denoising Algorithm for Speckle Noise in DoFP Polarization Images
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An Adaptive Denoising Algorithm for Speckle Noise in DoFP Polarization Images

机译：DOFP偏振图像中斑点噪声的自适应去噪算法

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In this paper, an adaptive algorithm for filtering speckle noise in Division-of-Focal-Plane (DoFP) polarization images is presented. The proposed algorithm involves replacing the first round of operation in the Block-matching and 3D Filtering (BM3D) denoising algorithm with an adaptive thresholding technique based on the smoothness of an image patch. This improves the "Semi-Filtered" image that is passed to the final BM3D denoising round. With this adaptive technique, key image details are preserved and speckle noise is significantly suppressed. Experimental results on four DoFP test images indicate the significant performance of the proposed algorithm in suppressing speckle noise. This significant performance is then compared with the performance of other existing denoising algorithms. Comparison is done numerically using Peak-Signal-to-Noise-Ratio (PSNR) and Structural Similarity (SSIM) Index scores. Thereafter, comparison is extended to visual results to ascertain agreement between the two sets of comparisons.
机译：本文介绍了一种用于滤波局部平面（DOFP）偏振图像中的散斑噪声的自适应算法。该算法涉及用基于图像贴片的平滑度的自适应阈值技术替换块匹配和3D滤波（BM3D）去噪算法中的第一轮操作。这改善了传递给最终BM3D的“半过滤”图像。利用这种自适应技术，保留了关键图像细节，并且显着抑制了斑点噪声。四个DOFP测试图像的实验结果表明所提出的算法在抑制散斑噪声时的显着性能。然后将这种显着性能与其他现有去噪算法的性能进行比较。使用峰值信噪比（PSNR）和结构相似度（SSIM）索引分数来数值上进行数值依次进行比较。此后，比较扩展到视觉结果，以确定两套比较之间的协议。

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