Denoising algorithm based on edge extraction and wavelet transform in digital holography

摘要

Digital holography is a kind of coherent imaging method and inevitably affected by many factors in the process of recording. One of dominant problems is the speckle noise, which is essentially nonlinear multiplicative noise related to signals. So it is more difficult to remove than additive noise. Due to the noise pollution, the low resolution of image reconstructed is caused. A new solution for suppressing speckle noise in digital hologram is presented, which combines Canny filtering algorithm with wavelet threshold denoising algorithm. Canny filter is used to obtain the edge detail. Wavelet transformation performs denoising. In order to suppress speckle effectively and retain the image details as much as possible, Neyman-Pearson (N-P) criterion is introduced to estimate wavelet coefficient in every scale. An improved threshold function is proposed, whose curve is smoother. The reconstructed image is achieved by merging the denoised image with the edge details. Experimental results and performance parameters of the proposed algorithm are discussed and compared with other methods, which shows that the presented approach can not only effectively eliminate speckle noise, but also retain useful signals and edge information simultaneously.