Poisson noise reduction in scintigraphic images using Gradient Adaptive Trimmed Mean filter

Khan Bahadar Khan, Amir A. Khaliq, Muhammad Shahid, Hayyat Ullah
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引用次数: 9

Abstract

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.
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基于梯度自适应裁剪均值滤波的科学图像泊松降噪
我们提出了一种新的混合技术来降低科学图像中的泊松噪声。我们提出的方法是梯度计算和自适应平均滤波(ATMF)的结合。在预定义的窗口中,平均中心像素的梯度。ATMF去除梯度去噪图像中像素值的最小和最大变化,并对剩余的邻域像素值进行平均。将该方法应用于闪烁图像。结果与传统滤波器即中值滤波器、维纳滤波器和最新的去噪滤波器即非局部均值(NLM)滤波器进行了比较。该方案提高了图像的相关性、均方误差(MSE)、结构相似度指标(SSIM)和峰信噪比(PSNR),具有良好的视觉效果。
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