Filtering Technology of Electronic Speckle Pattern Interferometry Image Based on Curvelet Transform

In the modern electronic speckle pattern interferometry (ESPI), the filtering for the correlation fringe pattern plays an important role in extracting the edge information and processing the ESPI image. A filtering method based on Curvelet transform is proposed in this paper for processing the ESPI image. Some other representative filtering methods such as mean filtering, median filtering, low-pass filtering and wavelet soft-threshold denoising are also introduced for making a comparison and validation in the image processing effect, and the parameters of speckle index and peak signal noise ratio (PSNR) are used for evaluation of filtering algorithms and denoising effect. The experimental results showed that the method of curvelet transform is superior to traditional filtering methods in speckle images, has a better performance in the fringe contrast, high-PSNR and lower speckle index, and is effective in noise removal and extraction of edge information for ESPI images.