Laser speckle contrast imaging based on spatial frequency domain filtering

We proposed a novel method to separate static and dynamic speckles based on spatial frequency domain filtering. First, the raw speckle image sequence is processed frame by frame through 2D Fourier transform, low‐pass and high‐pass filtering in the spatial frequency domain, and inverse Fourier transform. Then, we can obtain low‐ and high‐frequency image sequences in the spatial domain. Second, we averaged both sequences in the time domain. After the above processing, we obtain the mean intensities of the dynamic and static speckle components in the spatial domain. Finally, we calculated the time‐averaged modulation depth to map the 2‐D blood flow distribution. Both phantom and vivo experiments demonstrated that the proposed method could effectively suppress the background non‐uniformity and has the advantage of high computational efficiency. It also can effectively improve image contrast, contrast‐to‐noise ratio, and imaging dynamic range. We develop a novel method to separate dynamic speckles from static speckles by spatial frequency domain filtering and the time domain averaging of the speckle pattern. It can address the problems of nonuniform background, small dynamic range, low contrast, and contrast‐to‐noise ratio in conventional laser speckle contrast imaging. Furthermore, it exhibits superior computational efficiency.