王凌志, 周先春, 陈铭. 改进型PM与递归滤波器相结合的图像去噪方法[J]. 信息与控制, 2019, 48(5): 559-566. DOI: 10.13976/j.cnki.xk.2019.8543
引用本文: 王凌志, 周先春, 陈铭. 改进型PM与递归滤波器相结合的图像去噪方法[J]. 信息与控制, 2019, 48(5): 559-566. DOI: 10.13976/j.cnki.xk.2019.8543
WANG Lingzhi, ZHOU Xianchun, CHEN Ming. Image Denoizing Algorithm Based on Improved PM and Recursive Filter[J]. INFORMATION AND CONTROL, 2019, 48(5): 559-566. DOI: 10.13976/j.cnki.xk.2019.8543
Citation: WANG Lingzhi, ZHOU Xianchun, CHEN Ming. Image Denoizing Algorithm Based on Improved PM and Recursive Filter[J]. INFORMATION AND CONTROL, 2019, 48(5): 559-566. DOI: 10.13976/j.cnki.xk.2019.8543

改进型PM与递归滤波器相结合的图像去噪方法

Image Denoizing Algorithm Based on Improved PM and Recursive Filter

  • 摘要: 由于各向异性扩散算法在运用于图像去噪的过程中,容易产生图像边缘信息丢失,纹理细节模糊等现象.针对这一情况,提出了一种改进型PM与递归滤波器相结合的图像去噪算法,该算法首先通过控制梯度方向和垂直于梯度方向的扩散系数来保留图像的边缘信息,再通过递归滤波算法减少迭代次数来保护图像的细节纹理特征.实验结果表明,新方法在图像去噪和保护图像的边缘细节信息等方面都有着优越的效果,且大幅降低了均方差,对于图像的峰值信噪比也有显著的提高.

     

    Abstract: In the image denoizing process, the anisotropic diffusion algorithm is prone to image edge information loss and texture detail blur. Considering this, an image denoizing algorithm combining improved PM and recursive filter is proposed. This algorithm first preserves the edge information of the image by controlling the coefficients of the diffusion in the gradient direction and that perpendicular to the gradient direction, and then the recursive filtering algorithm is used to reduce the number of iterations to protect the detailed texture features of the image. The experimental results show that the new method has superior effects in image denoizing and edge detail information protection, and greatly reduces the mean square error. The peak signal-to-noise ratio of the image is also significantly improved.

     

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