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An Image Denoising Algorithm based on Kuwahara Filter

机译:基于Kuwahara滤波器的图像去噪算法。

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In order to improve the readability of digital image, the image denoising algorithm is studied. The algorithm is performed using a combination of Kuwahara filter and non-subsampling Shearlets transform (NSST). Firstly, the image with noise is decomposed in multiple scales and in multiple directions by NSST, that is, the low frequency coefficients and high frequency coefficients are obtained, and then the threshold is processed to remove most of the noise effectively. Then, the filtered coefficient is transformed into NSST inverse transformation, and the denoising image 1 is obtained. Finally, the de-noising image 1 is filtered by the Kuwahara filter, and the final de-noising image is obtained. While de-noising, the Kuwahara filter can well retain the edge, contour and other details of the image. Through experimental simulation, this algorithm has the advantage of image denoising and can get high quality image denoising. By comparing objective evaluation indexes, this method is effective for image denoising.
机译:为了提高数字图像的可读性,研究了图像去噪算法。该算法是结合使用Kuwahara滤波器和非二次采样Shearlets变换(NSST)来执行的。首先,利用NSST将具有噪声的图像在多个尺度和多个方向上分解,即得到低频系数和高频系数,然后对阈值进行处理以有效去除大部分噪声。然后,将滤波后的系数变换为NSST逆变换,从而获得去噪图像1。最后,通过Kuwahara滤波器对降噪图像1进行滤波,从而获得最终的降噪图像。去噪时,Kuwahara滤镜可以很好地保留图像的边缘,轮廓和其他细节。通过实验仿真,该算法具有图像去噪的优点,可以得到高质量的图像去噪。通过比较客观评价指标,该方法对图像去噪是有效的。

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