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计算机工程

• 图形图像处理 • 上一篇    下一篇

多层阈值函数下的小波图像去噪

秦冬冬,陈志军,闫学勤   

  1. (新疆大学 电气工程学院,乌鲁木齐 830047)
  • 收稿日期:2016-05-09 出版日期:2017-06-15 发布日期:2017-06-15
  • 作者简介:秦冬冬(1990—),男,硕士研究生,主研方向为图像识别、嵌入式系统;陈志军,教授、博士;闫学勤,讲师、硕士。
  • 基金资助:
    新疆维吾尔自治区自然科学基金面上项目(2015211C272)。

Wavelet Image Denoising with Multilevel Thresholding Function

QIN Dongdong,CHEN Zhijun,YAN Xueqin   

  1. (College of Electric Engineering,Xinjiang University,Urumqi 830047,China)
  • Received:2016-05-09 Online:2017-06-15 Published:2017-06-15

摘要: 传统的硬软阈值函数在阈值处不连续,容易产生振荡,且估计小波系数与实际小波系数有恒定偏差,存在过扼杀现象。为此,提出一种多层改进型的阈值函数,该函数不仅在阈值处连续,而且估计的小波系数能够渐进实际小波系数。通过加入阈值调节因子,根据采样点长度的不同调节阈值因子,解决固定阈值偏大的问题。实验结果表明,改进后的阈值函数无论在视觉效果上,还是在峰值信噪比和均方误差性能上均优于传统阈值函数。

关键词: 阈值函数, 小波变换, 图像去噪, 均方误差, 峰值信噪比

Abstract: The traditional hard and soft threshold function is not continuous at the threshold,which is easy to generate oscillation,and the estimated wavelet coefficients and the actual wavelet coefficient constant deviation,there are over kill phenomenon.In view of the above shortcomings,a new threshold function is proposed,which can not only be continuous at the threshold,but also estimate the wavelet coefficients.Through adding threshold adjustment factors,according to different length sampling to adjust threshold factors,it solves the problem of large fixed threshold.Experimental results show that the improved threshold function,both in visual effect,or in the Peak Signal-to-Noise Ratio(SNR) and Mean Square Error(MSE) performance are better than other threshold functions.

Key words: threshold function, wavelet transform, image denoising, Mean Square Error(MSE), Peak Signal-to-Noise Ratio(SNR)

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