Image De-Speckling Based on the Coefficient of Variation, Improved Guided Filter, and Fast Bilateral Filter

Hadi Salehi
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引用次数: 1

Abstract

Images are widely used in engineering. Unfortunately, medical ultrasound images and synthetic aperture radar (SAR) images are mainly degraded by an intrinsic noise called speckle. Therefore, de-speckling is a main pre-processing stage for degraded images. In this paper, first, an optimized adaptive Wiener filter (OAWF) is proposed. OAWF can be applied to the input image without the need for logarithmic transform. In addition its performance is improved. Next, the coefficient of variation (CV) is computed from the input image. With the help of CV, the guided filter converts to an improved guided filter (IGF). Next, the improved guided filter is applied on the image. Subsequently, the fast bilateral filter is applied on the image. The proposed filter has a better image detail preservation compared to some other standard methods. The experimental outcomes show that the proposed denoising algorithm is able to preserve image details and edges compared with other de-speckling methods.
基于变异系数、改进制导滤波器和快速双边滤波器的图像去斑
图像在工程中有着广泛的应用。不幸的是,医学超声图像和合成孔径雷达(SAR)图像主要被一种称为散斑的固有噪声所降低。因此,去斑点化是退化图像预处理的主要步骤。本文首先提出了一种优化的自适应维纳滤波器(OAWF)。OAWF可以应用于输入图像,而不需要进行对数变换。此外,它的性能也得到了改善。接下来,从输入图像计算变异系数(CV)。在CV的帮助下,导频滤波器转化为改进的导频滤波器(IGF)。接下来,将改进的引导滤波器应用于图像上。随后,对图像进行快速双边滤波。与其他一些标准方法相比,该滤波器具有更好的图像细节保留效果。实验结果表明,与其他去斑方法相比,该去斑算法能够保留图像的细节和边缘。
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