Blood oxygen content plays an important role in clinical diagnosis and treatment. However, interference signals will be introduced in the process of the signal acquisition, which will affect the accuracy of measurement results. Although the filter can eliminate most of the interference, there will still be a part of the residual interference signal. In order to eliminate these residual interference, this paper proposes a signal denoising method based on ensemble empirical mode decomposition (EEMD), lifting wavelet transform (LWT) and singular spectrum analysis (SSA). Firstly, the measured signal is decomposed by EEMD to obtain multiple modal components (IMF). The high-frequency components are denoised by LWT, and then reconstructed with the low-frequency components. Finally, the SSA is carried out on the reconstructed signal, the appropriate components are selected to reconstruct the signal to obtain the final denoised signal. After testing the EEMD-LWT-SSA method with simulated and measured signals, it can be seen that the method can effectively suppress the residual noise in signals and improve the accuracy of data.

Traditionally, interference patterns play an important role in determining the sign and magnitude of the orbital angular momentum (OAM) of the vortex beam. However, we demonstrate the importance of interference patterns in the identification and mitigation of lateral misalignment in the optical set-up, studied through the Radial Shearing Self-Interferometric (RSSI) technique. A splitting of the interference pattern of the perfect vortex beam (PVB) was observed with the introduction of lateral misalignment. These interference patterns proved to be instrumental in the identification of minute misalignment (micron level) in the optical set-up. The splitting in the interference patterns has been detected through image processing and an algorithm for automating the mitigation process has been proposed. The technique could prove to be a step towards self-aligning optical set-ups.

ABSTRACT To efficiently preserve texture and target information in source images, an image fusion algorithm of Regional Fusion Factor-Based Union Gradient and Contrast Generative Adversarial Network (R2F-UGCGAN) is proposed. Firstly, an adaptive gradient diffusion (AGD) decomposition algorithm is designed to extract representative features. A pair of infrared (IR) and visible (VIS) images are decomposed by AGD to obtain low-frequency components with salient targets and high-frequency components with rich edge gradient information. Secondly, In the high-frequency components, principal component analysis (PCA) is used for fusion to obtain more detailed images with texture gradients. R2F-UGCGAN is used to fuse the low-frequency components, which can effectively ensure good consistency between the target region and the background region. Therefore, a fused image is produced, which inherits more thermal radiation information and important texture details. Finally, subjective and objective comparison experiments are performed on TNO and RoadScene datasets with state-of-the-art image fusion methods. The experimental results of R2F-UGCGAN are prominent and consistent compared to these fusion algorithms in terms of both subjective and objective evaluation.

ABSTRACT We report a Gamma-corrected, SNR-enhanced and sharpness-projection-based reconstruction approach for digital particle holography. In this approach, we mitigate the artefacts from off-focal planes by capturing three holograms with various illumination angles, and extract particle information by applying image processing to a high-quality maximum – sharpness-projection (MSP) image. This approach reinforces weak edges using a Gamma correction procedure, and segments particles from the MSP image by using a new hybrid threshold, which comprises both local and global features. Experimental results for nonspherical particles show that the reported approach can provide a high-quality MSP image, being less likely than the conventional method to be fooled by noise and more likely to retain particle features. The hybrid threshold helps in retaining fine features, separating neighbouring particles and differentiating particles from the background. For the large particles (>20 pixels), the diameter error is generally less than 10% while using the proposed automatic hybrid thresholding technique.

It is indicated that when a circularly polarized electromagnetic wave is incident obliquely on an ideal conductor and reflected from it, the spin of the wave is partially transferred to the conductor. In this case, if the conductor rotates so that the axis of rotation is parallel to the transferred spin, then work is done. The work leads to a change in the frequency of the wave, and this can be recorded in a suitable interference experiment by shifting the interference fringes.

The extinction ratio is an important optical parameter that determines the quality of the linear polarizers. Here, we propose a high-precision measurement method for linear polarization extinction ratio, which is based on two uniform and consistent unknown linear polarizers, an integrating sphere, a precision turntable, and a spectrometer. The precision turntable is used to change the relative angle between the two unknown linear polarizers. The Mueller matrixs with the optical parameters including relative angles of the two unknown linear polarizers are established, and the linear polarization extinction ratio is obtained by numerical calculation. This method does not require a reference linear polarizer with a high extinction ratio, nor does it require fine adjustment of the angle between the two unknown linear polarizers to obtain the maximum and minimum light intensity grayscale response of the detector, which has an important engineering significance for high-precision measurement of linear polarization extinction ratio.

This study considers the propagation of spatial soliton in nematic liquid crystals in the presence of damping in the nonlocal regime. The importance of diffractive radiation shed for an undisturbed propagation of nematicon has been analysed in this paper using variational and numerical methods. When the damping coefficient is constant, a large value of diffractive radiation height is required to counteract the effect of damping. If the damping coefficient varies with the propagation distance, the diffractive radiation has an important role in reducing the damping effect. In the case of the periodic damping profile, even larger diffractive radiation is needed to overcome the effect of damping as compared to the constant damping profiles. But a low value of diffractive radiation is enough to overcome the hyperbolic damping.

A new method of three-dimensional (3D) image optical encryption based on phase-shifting compressive Fresnel holography (PSCFH) is presented. In the optical encryption step, the 3D object is encrypted with random phase masks using phase-shifting interferometry to record three intensity images with different phase-shifting. In the decryption step, the three-step phase-shifting technique is first used to extract the complex optical field at the recording plane. Finally, the 3D object is reconstructed from the recovered complex optical field using compressive Fresnel holography with the correct key. Numerical experiments demonstrate the feasibility and robustness of our proposed PSCFH method.

In this paper, we propose a new network to achieve low-sampling computational ghost imaging. The proposed neural network that combines ResNeXt, eHoloNet and spatial attention mechanism is efficient for object reconstruction just based on EMNIST training, which is much simpler and time-saving. The generalization of the neural network is verified with multi-slits as well as complex object. Both simulated and experimental results show that the proposed network can give an effective reconstruction at 0.7% sampling rate. The neural network in this work is of great significance to ghost imaging in a wider application scenarios, such as real-time imaging and dynamic detection of motion object.

A modified power spectrum of biological tissues involving upper length-scale and bottom length-scale was introduced. In addition, the analytical expression of Hermite–Gaussian rectangular vortex beam with the parameter () in free space was derived. By this modified power spectrum, we established the normalized probability model of orbital angular momentum (OAM) states for Hermite–Gaussian rectangular vortex beams propagation in biological tissues. The results revealed that Hermite–Gaussian rectangular vortex beam exhibits a better anti-interference performance than Laguerre–Gaussian beam under the same conditions. The Hermite–Gaussian rectangular vortex beam propagates through a biological tissue with large bottom length-scale, small upper length-scale, small characteristic length of heterogeneity, low the fractal dimensions, and weak fluctuation strength, which produces a large normalized probability of signal OAM states. These results are fundamental to improving light propagation in tissue and provide a quantitative guidance for medical imaging and diagnosis.