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A New Image Denoising Method by Combining WT with ICA

机译：WT与ICA相结合的图像去噪新方法

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摘要

In order to improve the image denoising ability, the wavelet transform (WT) and independent component analysis (ICA) are both introduced into image denoising in this paper. Although these two algorithms have their own advantages in image denoising, they are unable to reduce noises completely, which makes it difficult to achieve ideal effect. Therefore, a new image denoising method is proposed based on the combination of WT with ICA (WT-ICA). For verifying the WT-ICA denoising method, we adopt four image denoising methods for comparison: median filtering (MF), wavelet soft thresholding (WST), ICA, and WT-ICA. From the experimental results, it is shown that WT-ICA can significantly reduce noises and get lower-noise image. Moreover, the average of WT-ICA denoising image's peak signal to noise ratio (PSNR) is improved by 20.54% compared with noisy image and 11.68% compared with the classical WST denoising image, which demonstrates its advantage. From the performance of texture and edge detection, denoising image by WT-ICA is closer to the original image. Therefore, the new method has its unique advantage in image denoising, which lays a solid foundation for the realization of further image processing task.
机译：为了提高图像去噪能力，本文将小波变换（WT）和独立分量分析（ICA）都引入了图像去噪中。尽管这两种算法在图像去噪方面都有各自的优势，但是它们无法完全降低噪声，因此很难达到理想的效果。因此，提出了一种新的基于WT与ICA相结合的图像去噪方法（WT-ICA）。为了验证WT-ICA去噪方法，我们采用四种图像去噪方法进行比较：中值滤波（MF），小波软阈值（WST），ICA和WT-ICA。从实验结果表明，WT-ICA可以显着降低噪声并获得较低噪声的图像。此外，WT-ICA去噪图像的峰值信噪比（PSNR）的平均值与噪声图像相比提高了20.54％，与经典WST去噪图像相比提高了11.68％，这证明了它的优势。从纹理和边缘检测的性能来看，WT-ICA的去噪图像更接近原始图像。因此，该新方法在图像去噪方面具有独特的优势，为进一步的图像处理任务的实现奠定了坚实的基础。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第19期|582640.1-582640.10|共10页
  • 作者

    Ruan Chengzhi; Zhao Dean; Jia Weikuan; Chen Chen; Chen Yu; Liu Xiaoyang;

  • 作者单位

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China|Wuyi Univ, Sch Mech & Elect Engn, Wuyishan 354300, Peoples R China;

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China;

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China;

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China;

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China;

    Jiangsu Univ, Sch Elect & Informat Engn, Zhenjiang 212013, Peoples R China;

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