双树复小波和各向异性扩散再现像散斑噪声抑制

Speckle Noise Suppression of Reconstructed Image Based on Dual-Tree Complex Wavelet and Anisotropic Diffusion

为了有效抑制数字全息再现像的散斑噪声,进一步改善再现像的像质,提出了一种基于双树复小波变换(DT-CWT)和各向异性扩散的数字全息再现像散斑噪声抑制方法。将再现像进行双树复小波分解,对低频分量和6个方向的高频分量分别采用改进的P_Laplace扩散和拉普拉斯金字塔非线性扩散(LPND),通过双树复小波逆变换(IDT-CWT)重构再现像。给出了实验结果,并与小波阈值收缩和全变差(TV)扩散方法、拉普拉斯金字塔非线性扩散的方法、Contourlet结合TV扩散和自适应对比度扩散的方法进行了主观视觉比较,同时依据峰值信噪比(PSNR)、相关系数(COR)及运行时间等进行了客观定量评价。结果表明,本方法对散斑噪声抑制能力更强,并能更好地保留再现像的细节纹理特征。

In order to suppress the speckle noise of reconstructed image in digital holography effectively and to further improve the quality of reconstructed image, a speckle noise suppression method of reconstructed image in digital holography based on dual-tree complex wavelet transform （DT-CWT） and anisotropic diffusion is proposed. The reconstructed image is decomposed through DT-CWT. Then, the low-frequency components and the high- frequency components in six directions are processed through P_Laplace diffusion and Laplacian pyramid-based nonlinear diffusion （LPND）, respectively. The new reconstructed image is synthesized through inverse dual-tree complex wavelet transform （IDT-CWT）. The experimental results are given, and a subjective visual comparison is made with the method of wavelet threshold shrinkage and total variation （TV） diffusion, the method of LPND, and the method combining contourlet transform with TV and adaptive contrast diffusion. While the results are evaluated quantitatively according to peak signal to noise ratio （PSNR）, correlation coefficient （COR） and running time. Experimental results show that the proposed method has a better performance in speckle noise suppression and preserves the detail and textural features of original reconstructed image more efficiently.