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JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE)  2018, Vol. 52 Issue (9): 1804-1810    DOI: 10.3785/j.issn.1008-973X.2018.09.022
Electronic Communication Technology     
Piecewise noise variance estimation of images based on wavelet transform
ZHANG Cheng-zhi, FENG Hua-jun, XU Zhi-hai, LI Qi, CHEN Yue-ting
State Key Laboratory of Optical Instrumentation, Zhejiang University, Hangzhou 310027, China
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Abstract  

A new image noise estimation method was proposed to improve the accuracy of the small noise estimation. The method was based on the statistical properties of the detail factors of the image wavelet, which was analyzed and processed by the piecewise function. The original image was transformed by wavelet transform, and the initial estimation of noise standard deviation was obtained according to the traditional Donoho method. Finally, the initial estimation was processed according to the proposed formula which obtained the final results by segmenting and calculating the initial value. The experimental results show that the proposed method is more accurate than the traditional wavelet noise estimation method, especially for the images with less noise and more details. The noise variance estimated by the proposed method and the traditional method were substituted into the wavelet threshold de-noising method. The image de-noising effect using the noise variance estimated by the proposed method is better; the details can be kept better; the peak signal to noise ratio (PSNR) is at least 0.6 dB higher compared with the traditional method when the noise standard deviation is 10.



Received: 21 June 2017      Published: 20 September 2018
CLC:  TP391  
Cite this article:

ZHANG Cheng-zhi, FENG Hua-jun, XU Zhi-hai, LI Qi, CHEN Yue-ting. Piecewise noise variance estimation of images based on wavelet transform. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2018, 52(9): 1804-1810.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2018.09.022     OR     http://www.zjujournals.com/eng/Y2018/V52/I9/1804


图像噪声方差分段估计法

为了提高对较小噪声估计的准确性,提出一种图像噪声估计的新方法.该方法基于图像小波细节系数的统计特性,用分段函数进行分析处理.将原始图像进行小波变换,根据传统的Donoho方法得出噪声标准方差的初始估计值,将初始估计值根据提出的公式进行处理.实验结果表明,所提方法比传统的小波噪声估计方法更准确,特别是对于图像噪声较小(标准差小于20)和细节较多的图像.将所提方法和传统方法估计出的噪声方差分别代入小波阈值去噪方法中,所提方法去噪效果更好,能更好地保持图像细节,当噪声标准差等于10时,峰值信噪比(PSNR)至少比传统方法高0.6 dB.

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