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首页> 外文期刊>Applied Acoustics >Center affine filter based adaptive image despeckling method with preserving details
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Center affine filter based adaptive image despeckling method with preserving details

机译:基于仿射滤波器的保留细节的自适应图像检测方法

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Speckle noises inherently exist in radar, sonar, ultrasound and optical coherent tomography images. Such noises greatly degrade image quality, and thus make the tasks such as object detection and image registration difficult. With the Center Affine Filter (CAF), this paper proposes a new adaptive method for suppressing speckle noises. The proposed method adopts both local arithmetic mean and local geometric mean around an image pixel to compute the dispersion parameter of the CAF. The metrics of arithmetic and geometric mean not only intimately relate to the probability density function of speckle noise, but also reflect the image homogeneity; therefore, the designed CAF is capable of adaptively suppressing the speckle noises while maintaining the useful details in an image. Then, to speed up the proposed method, the technique of the integral image is used to get the local arithmetic and local geometric mean. The proposed method is experimentally tested on both synthetic and real images, which shows a prospective performance over Lee filter, SRAD filter, and the state-of-the-art BNLM filter. (C) 2019 Elsevier Ltd. All rights reserved.
机译:散斑噪声固有地存在于雷达,声纳,超声波和光学相干断层扫描图像中。这种噪声大大降低了图像质量,从而使得诸如物体检测和图像配准的任务困难。凭借中心仿射过滤器(CAF),本文提出了一种抑制斑点噪声的新型自适应方法。所提出的方法采用局部算术平均值和局部几何平均值,以计算CAF的色散参数。算术和几何指标意味着不仅与散斑噪声的概率密度函数密切相关,而且反映了图像均匀性;因此,设计的CAF能够自适应地抑制斑点噪声,同时保持图像中的有用细节。然后,为了加速所提出的方法,积分图像的技术用于获得本地算术和局部几何平均值。所提出的方法在综合性和实际图像上进行了实验测试,其示出了李滤波器,SRAD滤波器和最先进的BNLM滤波器的前瞻性性能。 (c)2019 Elsevier Ltd.保留所有权利。

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