The coherent noise always exists in digital holographic microscopy due to the laser source, degrading the image quality. A method of speckle suppression using the dynamic speckle illumination, produced by double-moving diffusers, is presented in digital holographic microscopy. The space–time correlation functions are theoretically analyzed from the statistics distribution in the doubly and singly scattered system, respectively. The configuration of double-moving diffusers is demonstrated to have better performance in speckle suppression compared with the single diffuser and moving-static double diffusers cases. The experiment results verify the feasibility of the approach. The presented approach only requires a single shot interferogram to realize the speckle reduction, accordingly it has the potential application in real-time measurement.

Frequency-difference-stabilized dual-frequency solid-state lasers with tunable and large frequency difference have become an ideal light source for the high-accuracy absolute-distance interferometric system due to their stable multistage synthetic wavelengths. In this work, the advances in research on oscillation principles and key technologies of the different kinds of dual-frequency solid-state lasers are reviewed, including birefringent dual-frequency solid-state lasers, biaxial and two-cavity dual-frequency solid-state lasers. The system composition, operating principle, and some main experimental results are briefly introduced. Several typical frequency-difference stabilizing systems for dual-frequency solid-state lasers are introduced and analyzed. The main development trends of research on dual-frequency solid-state lasers are predicted.

An intracavity, second-harmonic generation, tunable, dual-frequency, passively Q-switched Nd:YAG laser based on a T-resonator configuration with polarization splitting is proposed, whose frequency difference could be doubled in comparison with fundamental lasing. The Nd:YAG, Cr4 + : YAG, and potassium titanyl phosphate (KTP) crystals were set at the shared arm, which could considerably reduce thermal fluctuation and pulse timing jitter between dual-frequency lasers. One birefringent filter consisting of a polarized beam splitter and a half-wave plate (HWP) is placed in each divided arm to select their single longitudinal mode. As a result, the p-polarized and s-polarized passively Q-switched components of 532 nm are simultaneously operated, whose power easily reaches to same and frequency is beneficial to tune theoretically throughout the whole gain bandwidth. The main characteristics of the power, longitudinal mode selection, and the pulse have been tested experimentally. Moreover, the frequency difference of the dual-frequency laser at 532 nm has been widely tuned from 9.6 to 117 GHz, by slightly adjusting the tilt angles of the HWPs. We offer a simple and widely tunable source with potential for portable frequency reference applications in absolute-distance interferometry, terahertz-wave generation, and other fields.

In modern clinical medicine, the important information of red blood cells, such as shape and number, is applied to detect blood diseases. However, the automatic recognition problem of single cells and adherent cells always exists in a densely distributed medical scene, which is difficult to solve for both the traditional detection algorithms with lower recognition rates and the conventional networks with weaker feature extraction capabilities. In this paper, an automatic recognition method of adherent blood cells with dense distribution is proposed. Based on the Faster R-CNN, the balanced feature pyramid structure, deformable convolution network, and efficient pyramid split attention mechanism are adopted to automatically recognize the blood cells under the conditions of dense distribution, extrusion deformation, adhesion and overlap. In addition, the Align algorithm for region of interest also contributes to improving the accuracy of recognition results. The experimental results show that the mean average precision of cell detection is 0.895, which is 24.5% higher than that of the original network model. Compared with the one-stage mainstream networks, the presented network has a stronger feature extraction capability. The proposed method is suitable for identifying single cells and adherent cells with dense distribution in the actual medical scene.

Partial discharge (PD) detection is a crucial means for the early warning of incipient insulation defects in arresters. However, under strong electromagnetic interference and background noise, PD signals are prone to distortion, making it difficult to accurately determine the pulse onset front and thus severely degrading the accuracy of time-delay estimation. To address the difficulty of time-delay estimation under low signal-to-noise ratio (SNR) and multi-channel aliasing conditions, this paper proposes a method for arrester PD detection and high-precision time-delay estimation based on joint denoising and improved cross-correlation. First, a joint denoising strategy that integrates singular value decomposition (SVD), variational mode decomposition adaptively optimized by the sparrow search algorithm (SSA-VMD), and the Teager energy operator (TEO) is constructed. This strategy suppresses white noise and periodic narrowband interference while effectively extracting the oscillatory onset characteristics of PD pulses. Second, an enhanced time-delay estimation method based on HB-weighted generalized quadratic cross-correlation is introduced. By employing the dual mechanisms of HB frequency-domain weighting and amplitude weighting to sharpen the correlation peak, the estimation robustness under low SNR is improved. Simulation results show that the proposed method attains an accuracy of 99.9911%, significantly outperforming conventional cross-correlation, PHAT-SCOT, and NLMS methods. Finally, experiments are conducted on a needle-plate discharge platform. In multiple comparative experiments with different spatial distance differences (ranging from 50 cm), the maximum relative error is kept within 0.6%, verifying the reliability and accuracy of the proposed algorithm under controlled laboratory conditions. This method can provide a new approach for online monitoring and accurate fault location of arresters in power systems.