李莲, 熊倩飞. 基于自适应阈值的图像去噪新算法[J]. 微电子学与计算机, 2013, 30(4): 83-86.
引用本文: 李莲, 熊倩飞. 基于自适应阈值的图像去噪新算法[J]. 微电子学与计算机, 2013, 30(4): 83-86.
LI Lian, XIONG Qian-fei. New Image Denoising Method Based on Adaptive Threshold[J]. Microelectronics & Computer, 2013, 30(4): 83-86.
Citation: LI Lian, XIONG Qian-fei. New Image Denoising Method Based on Adaptive Threshold[J]. Microelectronics & Computer, 2013, 30(4): 83-86.

基于自适应阈值的图像去噪新算法

New Image Denoising Method Based on Adaptive Threshold

  • 摘要: 提出了一种具有自适应阈值的图像去噪算法.首先,阈值函数具有连续性,高阶可导性,充分体现了小波分解后系数的能量分布,且函数表达式简单易于计算,适合各种数学处理.其次,阈值的选取考虑了分解过程中小波系数的相关性和过程性等因素,减小了对噪声的误判率,具有更强的实用性.仿真实验结果表明,新算法不仅比传统算法运算量小,而且取得了更高的峰值信噪比(PSNR)和更小的均方误差(MSE),更加有效地去除了图像的噪声.

     

    Abstract: A new denoising algorithm based on adaptive threshold is proposed.First,the threshold function is continuous and has infinite rank continuous derivative,fully reflects the energy distribution of wavelet coefficients. What's more,the function expression is simple and easy to calculate,so it is suitable for various mathematical processing.Secondly,the correlation and procedural of wavelet coefficients in decomposition process is considered to the threshold's selection,which will reduce the false positive probability of noises and will be more practical. Simulation results show that the new algorithm not only has smaller computational cost than traditional algorithms, and achieves a higher PSNR and smaller MSE.It can remove the noise more effectively.

     

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