首页> 外文会议>2016 International Conference on Intelligent Systems Engineering >Poisson noise reduction in scintigraphic images using Gradient Adaptive Trimmed Mean filter
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Poisson noise reduction in scintigraphic images using Gradient Adaptive Trimmed Mean filter

机译:使用梯度自适应修正均值滤波器减少闪烁图像的泊松噪声

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We propose a new hybrid technique for reduction of poisson noise in scintigraphic images. Our proposed method is a combination of Gradient calculation and Adaptive Trimmed Mean filter (ATMF). In a predefined window, gradient of the center pixel is averaged out. ATMF remove the lowest and highest variations in the pixel values of Gradient denoised image and average out remaining neighborhood pixel values. The proposed technique is applied on scintigraphic images. Results are compared with conventional filters i.e. Median, Wiener filter and latest denoising filter i.e. Non Local Mean (NLM) filter. The proposed scheme shows good visual results with improving Correlation, Mean Squared Error (MSE), Structural Similarity Index Metric (SSIM) and Peak to Signal Noise Ratio (PSNR) of the image.
机译:我们提出了一种新的混合技​​术,以减少闪烁图像中的泊松噪声。我们提出的方法是将梯度计算和自适应修整均值滤波器(ATMF)结合在一起的。在预定义的窗口中,将中心像素的梯度平均化。 ATMF消除了梯度降噪图像的像素值的最低和最高变化,并对剩余的邻域像素值求平均。所提出的技术被应用于闪烁图像。将结果与常规滤波器(即中值,维纳滤波器)和最新降噪滤波器(即非局部均值(NLM)滤波器)进行比较。所提出的方案显示了良好的视觉效果,并改善了图像的相关性,均方误差(MSE),结构相似性指标(SSIM)和峰信噪比(PSNR)。

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