一种基于小波分析的改进阈值图像去噪方法

An Improved Threshold Image Denoising MethodBased on Wavelet Analysis

  • 摘要: 该文针对图像去噪中的小波阈值图像去噪方法进行了研究,分析了硬阈值去噪和软阈值去噪在实际应用中的优点与不足,结合这两种去噪方法的优点,在硬阈值去噪和软阈值去噪的基础上,提出了一种改进的阈值图像去噪方法。对于大小为256×256的Lena图片,该改进阈值法的峰值信噪比(PSNR)分别比软阈值法和硬阈值法提高了1.63%和1.59%。实验结果表明,当选择合适的控制系数值时,与硬阈值去噪方法和软阈值去噪方法相比较,该改进方法能达到更好的去噪效果。

     

    Abstract: This article mainly studies the wavelet threshold image denoising method in image denoising.The advantages and disadvantages of hard threshold denoising and soft threshold denoising in practical applications are studied.Combined with the advantages of these two methods,an improved threshold image denoising method is proposed based on hard threshold denoising and soft threshold denoising.For the Lena images of 256×256,the obtained peak signal-to-noise ratio(PSNR)of the improved threshold method was 1.63% and 1.59% higher than that of the soft threshold method and the hard threshold method,respectively.The results show that the improved threshold image denoising method can achieve a better denoising effect compared with the hard threshold denoising and the soft threshold denoising method when the appropriate control system values are selected.

     

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