Stray Light Interference Research Articles

A model for suppressing stray light in astronomical images based on deep learning

Wide-Field Small Aperture Telescopes (WFSAT) are widely used for surveilling space objects. Due to their wide-field of view (FOV) characteristics, these telescopes can cover a large areas of the sky at once, improving observation efficiency. However, a wide-field optical telescope is highly sensitive to external stray light (such as moonlight and thin clouds), which can significantly reduce the quality of observation data. In severe cases, it can cause the telescope to malfunction and inaccurately position the object. In response to this problem, this paper proposes a model for suppressing stray light in astronomical images based on deep learning: the Pyramid Deformable Large Kernel Attention (PD-LKA) Model. This model expands the receptive field through a pyramid structure, captures multi-scale features, and improves the model’s robustness to various scales of stray light interference. Meanwhile, through the Deformable Large Kernel Attention (D-LKA), the model can more accurately locate and enhance the feature extraction ability in areas affected by stray light interference, thereby better suppressing stray light.Using simulated astronomical image pairs to train the model, the tests achieved a PSNR of up to 32.540 and an SSIM of up to 0.938. Finally, the model is applied to a image sequence with real stray light interference. The restored images undergo astronomical positioning and orbital association processing. The results show that the positioning accuracy of the object is better than 5 arcseconds. This indicates that the model proposed in this paper not only recovers the object and background stars but also effectively preserves their gray values, shapes, and positional information.

An enhanced centerline extraction algorithm for complex stripes in linear laser scanning measurement

Centerline extraction is a basic and critical step for linear laser scanning measurement. However, in practical measurement, the inconsistent reflectivity of the measured surface and the external noise interference can result in complex variation of the stripe pattern, which will influence the centerline extraction accuracy of the stripe pattern and hence the measurement accuracy of the laser scanner. To solve this problem, an enhanced centerline extraction algorithm for complex laser stripes is proposed. In the preprocessing of the stripe pattern, a region separation strategy is employed to mitigate the effects of complex variations, and multi-region self-adaptive convolution is adopted to enhance the stripe pattern quality. For high-precision extraction of the stripe centerline, different convolution kernels are applied to compute the Hessian matrix for the stripe patterns in different regions to determine the normal direction of the laser line. The second order Taylor expansion is performed along this direction to work with the denoising algorithm to determine the subpixel positions of the center points on the line, and then the whole centerline of the stripe pattern is obtained by piecewise cubic Hermite interpolation methods. Experimental results show that the effectiveness of the proposed algorithm in addressing centerline extraction for complex laser stripe patterns due to stray light interference, reflective stripes, and laser stripe linewidth changes in laser scanning measurement.

Trimodality applications validation of near-infrared persistent luminescence nanoparticles

Here, we introduced Cr ion, as emission center, to achieve the NIR emission for MgGa2O4, while Zn ion is used to increase oxygen vacancy to improve the emission intensity. Thus, Mg0.9Zn0.1Ga2O4: 0.006 Cr3+ (MZGC) was prepared as the optimal composite with the enhanced NIR emission at 708 nm, while the host, Mg0.9Zn0.1Ga2O4 (MZG), exhibited the afterglow emission at 425 nm under 224 nm excitation. The result from density functional theory confirmed Cr and Zn ions occupied in the octahedral coordination to improve the optical behaviors. The NIR emission of MZGC was applied for bioimaging as confirmed with mice model under both visible and NIR excitation. We proposed MZGC strategy for fingerprint imaging and recognition with their resistance to stray light interference. By applying the mixture of MZGC and MZG, we realized ratiometric temperature sensing at 35–40 °C within body temperature range. The optical mechanism clearly illustrated for tri-modality applications as bioimaging, fingerprint recognition, and temperature sensing. This work provides a reliable method for the improvement of optical properties and thus extend the applications of persistent luminescence nanoparticles.

A Vision-Based Pose Estimation of a Non-Cooperative Target Based on a Self-Supervised Transformer Network

In the realm of non-cooperative space security and on-orbit service, a significant challenge is accurately determining the pose of abandoned satellites using imaging sensors. Traditional methods for estimating the position of the target encounter problems with stray light interference in space, leading to inaccurate results. Conversely, deep learning techniques require a substantial amount of training data, which is especially difficult to obtain for on-orbit satellites. To address these issues, this paper introduces an innovative binocular pose estimation model based on a Self-supervised Transformer Network (STN) to achieve precise pose estimation for targets even under poor imaging conditions. The proposed method generated simulated training samples considering various imaging conditions. Then, by combining the concepts of convolutional neural networks (CNN) and SIFT features for each sample, the proposed method minimized the disruptive effects of stray light. Furthermore, the feedforward network in the Transformer employed in the proposed method was replaced with a global average pooling layer. This integration of CNN’s bias capabilities compensates for the limitations of the Transformer in scenarios with limited data. Comparative analysis against existing pose estimation methods highlights the superior robustness of the proposed method against variations caused by noisy sample sets. The effectiveness of the algorithm is demonstrated through simulated data, enhancing the current landscape of binocular pose estimation technology for non-cooperative targets in space.

Star Tracking Algorithm Based on Local Dynamic Background Reduction for Eliminating Stray Light Interference From Star Spot Data

Star Tracking Algorithm Based on Local Dynamic Background Reduction for Eliminating Stray Light Interference From Star Spot Data

Polarized computational ghost imaging in scattering system with half-cyclic sinusoidal patterns

Computational Ghost Imaging (CGI) can reconstruct the scene images through the correlation algorithm between the preset illumination patterns and the intensities of the detection bucket detector. In the actual transmission process, the scattering system in the imaging path can affect the imaging quality of the CGI. The half-cyclic sinusoidal-pattern based CGI (HCSP-CGI) can recover the scene images at low sampling rates (SRs). Based on the Monte Carlo (MC) model, we propose and construct a reflective polarization system based the HCSP-CGI in fog environment and put forward a method that combines polarization information with the HCSP-CGI called the PHCSP-CGI. When the difference in reflectivity between target and background is small, the difference in polarization characteristics between target and background can help CGI to remove the interference of stray light. The imaging performance of the PHCSP-CGI at different SRs and scattering distances (SDs) are analyzed. Experimental results show that high-contrast scene can still be obtained, providing new applications for object recognition in scattering system.

Multi-Point Fiber-Optic Distance Sensor for Endoscopic Surgery Monitoring

We present a sub-mm diameter multi-point endoscopic sensor for simultaneous measurement of the minimum distance and orientation of the sensor head with respect to a flat tissue surface. The approach is based on frequency modulated continuous wave (FMCW) LIDAR, which is a coherent measurement method immune to stray light interference. As a swept source, a commercially available 850 nm VCSEL is wavelength modulated by self-heating to achieve a tuning range of 4.1 nm at up to 10 kHz repetition rate. The resulting interferograms are calibrated in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -space using a reference Mach-Zender interferometer. Multiple measurement beams are split at the sensor tip using a 3D nano-printed microprism array, which achieves this refractively for higher collection efficiency and a larger measurement range compared to a diffractive element. Preliminary experiments under controlled conditions validate the sensor’s performance.

Stray Light Suppression of Wide-Field Surveillance in Complicated Situations

Wide field and long exposure time can effectively improve the ability of space surveillance telescope to detect weak space targets. However, this is easily affected by stray light, resulting in the effective target submerged in the background of stray light. Based on the basic theory of Mathematical morphology, this paper proposes an accurate and highly robust method (ETH) for stray light suppression of space surveillance telescope, which is called the enhanced Top-Hat transform. Firstly, we define the Generalized Top-Hat transform according to the traditional Top-Hat transform. Secondly, we improve the background estimation of the traditional opening, introduce the closing to realize the multi-scale micro adjustment, and analyze the influence of the multi-scale micro adjustment on the stray light suppression and space weak targets segmentation. Finally, we introduce the noise suppression factor to reduce the residual noise in the stray light. In the field experiment, the method can effectively eliminate the interference of stray light, and greatly improves the local signal-to-noise ratio of space targets. It also shows that in a very low signal-to-noise ratio, this method can accurately and effectively segment space weak targets, and has strong robustness.

Design of a digital PCR optical detection system with multiple fluorescent microdroplets.

The need for accurate nucleic acid testing is increasing with the spread of the global pandemic. Problems such as low efficiency and precision and large volume exist because the number of existing digital polymerase chain reaction (PCR) testing instrument channels is low. In order to solve these problems, a four channel micro drop digital PCR system was designed. The collimating lens set and objective lens of the LED light source are designed in ZEMAX software, and the entire optical path is simulated. It is verified that the light energy utilization rate of the system is over 93% and that stray light interference is marginal.

A Curvature-Based Multidirectional Local Contrast Method for Star Detection of a Star Sensor

Stray light, such as sunlight, moonlight, and earth-atmosphere light, can bring about light spots in backgrounds, and it affects the star detection of star sensors. To overcome this problem, this paper proposes a star detection algorithm (CMLCM) with multidirectional local contrast based on curvature. It regards the star image as a spatial surface and analyzes the difference in the curvature between the star and the background. It uses a facet model to represent the curvature and calculate the second-order derivatives in four directions. According to the characteristic of the star and the complex background, it enhances the target and suppresses the complex background by a new calculation method of a local contrast map. Finally, it divides the local contrast map into multiple 256 × 256 sub-regions for a more effective threshold segmentation. The experimental results indicated that the CMLCM algorithm could effectively detect a large number of accurate stars under stray light interference, and the detection rate was higher than other compared algorithms with a lower false alarm rate.

Real-Time Detection Method for Center and Attitude Precise Positioning of Cross Laser-Pattern

Optical metrology has experienced a fast development in recent years—cross laser-pattern has become a common cooperative measuring marker in optical metrology equipment, such as infrared imaging equipment or visual 3D measurement system. The rapid and accurate extraction of the center point and attitude of the cross-marker image is the first prerequisite to ensure the measurement speed and accuracy. In this paper, a cross laser-pattern is used as a cooperative marker, in view of the high resolution of the cross laser-pattern image in the project and the vulnerability to adverse environmental effects, such as stray light, smoke, water mist and other interference in the environment, resulting in poor contrast, low signal-to-noise ratio (SNR), uneven energy distribution. As a result, a method is proposed to detect the center point and attitude of cross laser-pattern image based on Gaussian fitting and least square fitting. Firstly, the distortion of original image is corrected in real time, the corrected image is smoothed by median filter, and the noise is suppressed while preserving the edge sharpness and detail of the image. In order to adapt to different environments, the maximum inter-class variance method of threshold automatic selection is used to determine the threshold of image segmentation to eliminate the background interference caused by different illumination intensities. To improve the real-time performance of the algorithm, the four cross laser edge pixels are obtained by line search, and then fitted by least square. With the edge lines, the transverse and portrait line of the cross-laser image are separated, then we calculate Gaussian center points of all Gaussian sections of transverse and portrait lines based on Gaussian fitting method, respectively. Based on the traditional line fitting method, the sub-pixel center of the transverse and portrait laser strip images are fitted by removing the Outlying Points, and the center coordinates and attitude information of the cross laser-pattern are calculated by using the center equation of the laser strip, realizing cross laser-pattern center and attitude accurate positioning. The results show that the method is robust, the center positioning accuracy is better than 0.6 pixels, the attitude positioning accuracy is better than ±15” under smoke and water mist environment and the processing speed is better than 0.1 s, which meets the real-time requirements of the project.

Effect of Inductively Coupled Electromagnetic Field on Bottom Oxide Etch in a High Aspect Ratio Trench

CMOS optical sensors devices are becoming increasingly important and popular for many different applications. Some of these devices are fabricated starting from SOI (Silicon On Insulator) wafers and using semiconductor manufacturing techniques. A common feature of the CMOS sensors is the isolating trench that protects the device from electrical noise. We report on the multistep etch process development to fabricate trenches deeper than usual, in order to isolate the sensor also from stray light interference. We focus the attention on unexpected features that originated during the Buried Oxide (BOX) etch.

Stray Light Elimination Method Based on Recursion Multi-Scale Gray-Scale Morphology for Wide-Field Surveillance

The wide-field surveillance camera plays a critical role in space debris detection and the visible light situational awareness required for early warning. However, stray light in such a system has always been a serious problem. Current methods cannot effectively eliminate the interference of stray light, which directly lead to the inability to accurately segment the target and background, which greatly reduce the accuracy of target recognition. To solve this problem, we proposed an accurate stray light elimination method based on recursion multi-scale gray-scale morphology (RMGM). First, we defined two structural operators with different domains. These two structural operators can make full use of the difference information between the target region and the surrounding background region, which is the basic premise to ensure high-precision correction. Then we used the two structural operators with different domains to perform morphological processing on the surveillance image to eliminate stray light. Finally, in order to ensure that targets with different sizes in the surveillance image are not lost, we adopt a recursion multi-scale method. We increase the size of structural operator and perform the morphological operation again on the estimated and eliminated stray light non-uniform background in order to retrieve the lost larger size target. In addition, we add an automatic decision mechanism on the recursion multi-scale method by using corresponding threshold judgment. Further experimental results on real captured image datasets show that compared with other methods, the proposed RMGM method can simultaneously have high-precision stray light elimination effect, high-precision target retention rate, and faster computation time.

Suppression method for strong interference from stray light in 3D imaging system of structured light

It is critical to accurately obtain a phase position in a digital fringe projection system. Due to stray light in a complex environment, when projecting an image of a code fringe, the projected light intensity can be influenced. As a result, the intensity of fringe light captured with the camera may be defective, resulting in the decline of measurement precision. Hence, we propose a strong suppression technology for stray light based on polarization. Through processing fringe images in the frequency domain, this technology can effectively suppress interference of stray light on the three-dimensional (3D) imaging system. This method is verified in the experiment. The results show that the method can accurately capture the 3D profile of real-world targets under the interference of stray light.

A Novel Method of Eliminating Stray Light Interference for Star Sensor

Star sensors are easily disturbed by stray light when working in the space environment: the quality of star image can be seriously reduced and the difficulty of star image preprocessing can be greatly increased. In this paper we propose a novel method for eliminating stray light interference based on the grayscale difference of star images. Firstly, since the grayscale difference between the edge of a star spot and the surrounding background pixels was very large, a grayscale forward difference was performed on the star image row by row. Based on the equivalent difference star image obtained, we could propose an edge pixel criterion for the star spot. Secondly, Stray light interference was eliminated from the star image through a connected component analysis based on the edge pixels criterion for the star spot. The relatively complete star spot areas were marked on the marker map. The simulation results demonstrate that the star spot extraction rate achieved through the proposed method was much higher than that obtained through traditional star image preprocessing methods. As long as the star spot is not submerged by the stray light, the proposed method is robust enough to ensure a successful extraction of the star spot.

Effect of Inductively Coupled Electro-Magnetic Field on Bottom Oxide Etch in a High Aspect Ratio Trench

CMOS optical sensors devices are becoming increasingly important and popular for many different applications. Some of these devices are fabricated starting from SOI (Silicon On Insulator) wafers and using semiconductor manufacturing techniques. A common feature of the CMOS sensors is the isolating trench that protects the device from electrical noise. We report on the multistep etch process development to fabricate trenches deeper than usual, in order to isolate the sensor also from stray light interference. We focus the attention on unexpected features that originated during the Buried Oxide (BOX) etch.

Optical engine optimisation for faint starlight simulation systems

In traditional faint starlight simulators, stray light interference prevents the accurate magnitude simulation of weak stars. In this study, we propose a method to optimise the parameters of the optical engine to suppress stray light. The results from a simulated model of the system’s point source transmittance (PST) and incident off-axis and azimuth angles show the optimised design to have a PST value that is nearly five times higher than that of a traditional system. The performance of the optimised system was evaluated using the detector’s signal-to-noise ratio (SNR) and magnitude. Moreover, polarisation aberration was used to derive the optimised index, and experimental results show the optimised simulation error of the new system to be less than 0.1 Mi, thus confirming the accuracy of our theoretical research.

Quantitative temperature imaging at elevated pressures and in a confined space with CH4/air laminar flames by filtered Rayleigh scattering**Project supported by the National Natural Science Foundation of China (Grant No. 91641118) and the Fenglei Youth Innovation Fund of China Aerodynamics and Research Development Center, China (Grant Nos. FLYIF20160017 and PJD20180131).

Laminar methane/air premixed flames at different pressures in a newly developed high-pressure laminar burner are studied through Cantera simulation and filtered Rayleigh scattering (FRS). Different gas component fractions are obtained through the detailed numerical simulations. And this approach can be used to correct the FRS images of large variations in a Rayleigh cross section in different flame regimes. The temperature distribution above the flat burner is then presented without stray light interference from soot and wall reflection. Results also show that the extent of agreement with the single point measurement by the thermocouple is <6%. Finally, this study concludes that the relative uncertainty of the presented filtered Rayleigh scattering diagnostics is estimated to be below 10% in single-shot imaging.

Parametric Prediction of Optical Tracker using Machine Learning Techniques for an efficient Head Tracking

A head tracker is a crucial part of the head-mounted display systems, as it tracks the head of the pilot in the plane/cockpit simulator. The operational flaws of head trackers are also dependent on different environmental conditions like different lighting conditions and stray light interference. In this paper, an optical tracker has been employed to gather the 6-DoF data of head movements under different environmental conditions. Also, the effect of different environmental conditions and variation in distance between the receiver and optical transmitter on the 6-DoF data is analyzed. This can help in the prediction of the accuracy of a optical head tracker under different environmental conditions prior to its deployment in the aircraft.

Destriping Algorithms Based on Statistics and Spatial Filtering for Visible-to-Thermal Infrared Pushbroom Hyperspectral Imagery

Following calibration, hyperspectral images remain affected by spatial dimension nonuniformity, i.e., stripe noise, due to stray light interference, slit contamination, and instrument instability. The full spectrum airborne hyperspectral imager (FAHI) is a Chinese next-generation pushbroom sensor with a spectral range covering the visible near-infrared, shortwave-infrared (SWIR), and thermal infrared regions with spectral sampling intervals of 2.34, 3, and 32 nm, respectively. However, the residual stripe noise remains in FAHI images after relative radiometric correction based on the laboratory calibration, especially in low signal-to-noise ratio bands. To solve this problem, a new technique combining image statistics and spatial filtering algorithms has been developed for FAHI image correction. In this method, image statistics are obtained to calculate the gain and offset of each pixel for image nonuniformity correction. Then, a spatial filter removes the residual stripes. This paper presents the principles of this method along with details of validation experiments and results. To validate the effectiveness of the proposed method, comparison with two destriping methods and quantitative analyses are carried out. Moreover, the method is applied to an SWIR hyperspectral image from the TianGong-1 spacecraft, yielding good results. The experimental results suggest that the proposed method is convenient and practical for improving the relative radiometric accuracy of airborne/spaceborne hyperspectral images.