芦碧波, 李阳, 王永茂. 结合松弛中值滤波的高阶彩色图像迭代去噪算法[J]. 应用光学, 2016, 37(3): 365-371. DOI: 10.5768/JAO201637.0302001
引用本文: 芦碧波, 李阳, 王永茂. 结合松弛中值滤波的高阶彩色图像迭代去噪算法[J]. 应用光学, 2016, 37(3): 365-371. DOI: 10.5768/JAO201637.0302001
Lu Bibo, Li Yang, Wang Yongmao. Color image denoising using high order iterating model by combining relaxed median filter[J]. Journal of Applied Optics, 2016, 37(3): 365-371. DOI: 10.5768/JAO201637.0302001
Citation: Lu Bibo, Li Yang, Wang Yongmao. Color image denoising using high order iterating model by combining relaxed median filter[J]. Journal of Applied Optics, 2016, 37(3): 365-371. DOI: 10.5768/JAO201637.0302001

结合松弛中值滤波的高阶彩色图像迭代去噪算法

Color image denoising using high order iterating model by combining relaxed median filter

  • 摘要: 为去除基于局部平均曲率的彩色图像去噪模型中作为几何特征而保留下来的斑点,提出了一种改进的迭代算法。采用局部平均曲率作为正则项耦合各个颜色通道,在迭代过程中根据局部统计量检测斑点,并引入松弛中值滤波进行斑点抑制。使用不同特征的图像进行仿真实验,并对峰值信噪比的演化进行分析。实验结果表明,改进的算法在有效消除斑点的同时较好地保护了图像结构,并且提高了计算效率。峰值信噪比提高了2.47%,迭代次数减少了93.66%。

     

    Abstract: An improved iterating algorithm was proposed to eliminate the speckles preserved by the local curvaturebased model as geometrical characteristic. It utilized the local curvature coupling 3 channels as the regularizing term,then detected speckles by using local statistics values. The relaxed median filter was introduced to suppress these speckles. Numerical experiments using images of different features were carried out and the evolution of the values of the peak signal to noise ratio(PSNR) was analyzed. The results show that this algorithm can accelerate the progress of evolution and eliminate the speckles while protecting the image structure information. The value of the PSNR increases by 2.47%, and the iterations decrease by 93.66%.

     

/

返回文章
返回