Rapid Blind Denoising Method for Grating Fringe Images Based on Noise Level Estimation
Shenhua Zhang, Yanxi Yang, Qiaomeng Qin, Lianqiang Feng, Licong Jiao
Abstract
Object profile measurement theory and technology based on grating fringe image projection are popular topics of research. However, due to the presence of noise, the phase extracted from captured grating fringe images may be wrong, affecting the measurement results. To manage noise with unknown intensity levels, we use Gaussian distribution to model the noise, and propose a novel rapid blind denoising method. First, we establish an energy expression model for grating fringe images. After performing singular value decomposition (SVD) on the grating fringe image, we establish a linear relationship between the average energy of the image and the noise variance. Second, we propose a noise variance estimation method based on a single frame grating fringe image. By adding an auxiliary image of zero-mean Gaussian noise, we can obtain the estimated noise variance. Third, a Gaussian filtering method of the phase maps using the estimated variance, is employed to reduces the amount of data processing. The experimental results show that the proposed method can complete noise processing faster than five other methods, and extract the phase profile of two measured models with minimum root-mean-square (RMS) error of 0.0686 and 0.0673 rad.