基于复数小波变换和H-Curve准则对图像的去噪

复数小波变换在某些方面比实数小波变换具有更多的优点,如:平移不变性、更好的方向 性和精确的相空间信息等,可提高图像的去噪能力。采用二树复数小波变换,在基于H Curve准则 确定阈值的基础上进行图像去噪。此准则不需要提前知道噪声标准偏差,在实际应用中适用于不同 类型的噪声,并且和目前多数方法去噪后的图像过于平滑相比,它还能产生较好的视觉效果。典型去 噪试验表明,该方法在去噪能力、取得的视觉效果和确定阈值的广泛性方面都优于目前多数方法。

Image denosing based on complex wavelet transform and H-Curve criterion

According to more merits in some aspects over real wavelet transform such as shift invariability, more directions and precise information in phase space,complex wavelet transform can improve the ability to image denosing.In this paper combined with H-Curve criterion Dual-Tree complex wavelet transform was applied to image denosing. The H-Curve criterion does not need know the noise standard deviation firstly,and it can dispose many kinds of noise practically and produce a better effect in vision over smooth image brought up by many methods presently. The typical denosing test shows that the method produces a better effect over multitudinous methods presently in many aspects such as the ability to denosing, the effect in vision and universality in choosing a threshold.