摘要Due to background light fluctuation, noise interference, voltage fluctuation, and other factors, there will be noise interference of different intensities in the background of the collected image. In this paper, a PIV image background interference removal algorithm based on improved neighborhood Otsu processing is proposed. The algorithm proposed in this paper separates the particle image from the background interference through the adaptive neighborhood improved Otsu threshold segmentation method and uses the common PIV analysis tools PIVLab and paraPIV to analyze the flow pattern after the interference is removed. The experimental results demonstrated that the proposed algorithm can obviously improve the quality of PIV results in terms of both PSNR and SSIM in the case of background light interference, and the increase in average performance is nearly 50% compared with traditional preprocessing algorithms, which solves the problem of large flow pattern analysis error caused by poor background light removal effect in the case of irregular grating and other background light interference only using traditional preprocessing.
Abstract：Due to background light fluctuation, noise interference, voltage fluctuation, and other factors, there will be noise interference of different intensities in the background of the collected image. In this paper, a PIV image background interference removal algorithm based on improved neighborhood Otsu processing is proposed. The algorithm proposed in this paper separates the particle image from the background interference through the adaptive neighborhood improved Otsu threshold segmentation method and uses the common PIV analysis tools PIVLab and paraPIV to analyze the flow pattern after the interference is removed. The experimental results demonstrated that the proposed algorithm can obviously improve the quality of PIV results in terms of both PSNR and SSIM in the case of background light interference, and the increase in average performance is nearly 50% compared with traditional preprocessing algorithms, which solves the problem of large flow pattern analysis error caused by poor background light removal effect in the case of irregular grating and other background light interference only using traditional preprocessing.
XU Meng-bi. Background Interference Removal Algorithm for PIV Preprocessing Based on Improved Local Otsu Thresholding[J]. 中国生物医学工程学报(英文版）, 2022, 31(4): 147-159.
XU Meng-bi. Background Interference Removal Algorithm for PIV Preprocessing Based on Improved Local Otsu Thresholding. Chinese Journal of Biomedical Engineering, 2022, 31(4): 147-159.
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