Small Pixel Research Articles

Thermomagnetic recording of highly Bi-substituted iron garnet film using scanning laser for spatial light modulation

Spatial light modulations (SLM) utilizing the magneto-optical (MO) effect of magnetic materials are expected to offer fast switching and small pixel sizes as small as the wavelength of the light. However, the small MO effect is a major issue. In this paper, we report a thermomagnetic recording of highly bismuth-substituted garnet film, known for large Faraday effects. Y0.5Bi2.5Fe4GaO12 (Bi,Ga:YIG) film with a Faraday rotation of −4.66 degrees was used as an MO medium. A laser scanning thermomagnetic recording system using a Galvanometer mirror was developed and the size and quality of recorded magnetic domains were investigated. The smallest recorded magnetic domain diameter was 0.62 μm with a small standard deviation of 0.09 μm. Line patterns with a width of 1 μm can be recorded in this film. We found that Bi,Ga:YIG films have potential as a material for SLMs with fast switching, submicron pixel size, and large MO effect.

Improving the simulation accuracy of summer maize growth and yield by pixel-based parameterization based on assimilating upscaled MODIS LAI

Accurately simulating maize (Zea mays L.) yield at the regional scale is of paramount importance for making informed policy adjustments and for ensuring food security. Sobol sensitivity analysis was used in this study to screen sensitive parameters of a process-based crop model (Chinese Agricultural Meteorological Model, CAMM). An upscaling approach was utilized to reduce the intra-pixel heterogeneity error of MODIS LAI. Then upscaled MODIS LAI data were assimilated into the CAMM model through a 4DVar assimilation algorithm to optimize pixel-level sensitive parameters, thereby improving the simulation accuracy of the summer maize growth process and yield. Specific leaf area (SLATB_0, SLATB_1) during the period from emergence to tasseling of summer maize exhibited the strongest impact on summer maize yield. Additionally, the average LAI value within the 85–95 % range of ordered LAI values for small pixels within large pixels effectively reduced the intra-pixel heterogeneity error of MODIS LAI, and pixel-based parameterization of SLATB_0 and SLATB_1 at a larger pixel scale (0.0625°) was achieved. Based on yields recorded at agrometeorological stations from 2015 to 2020, assimilated yields in both data assimilation scheme 1 (DA1, optimization of only the sensitive parameter SLATB_0) and scheme 2 (DA2, simultaneous optimization of sensitive parameters SLATB_0 and SLATB_1) exhibited higher accuracy than schemes without data assimilation (with r values of 0.41–0.72 and NRMSE values of 19–30 %). Furthermore, DA2 showed greater simulation accuracy (r: 0.64–0.93, NRMSE: 9–21 %) than DA1 (r: 0.61–0.91, NRMSE: 12–23 %). Upscaling remotely sensed LAI products can significantly reduce the uncertainties of LAI data at a larger pixel scale, and assimilating these LAI data into crop models can effectively increase the simulation accuracy of crop growth and development processes at the regional scale.

Design and fabrication of polarization independent LCoS phase modulators with polymer waveplate and analog driving

Abstract Phase-only liquid crystal on silicon (LCoS) spatial light modulators are used in a variety of applications. Despite their wide use, current phase-only LCoS devices are hindered by their single-polarization modulation. We propose a polarization independent LCoS device which uses a polymer quarter-wave plate for polarization conversion. We designed a custom pixel circuit which enables high driving voltage and high pixel grayscale by utilizing an analog driving frame buffer pixel circuit. Our pixel circuit is optimized for small pixel size and the silicon backplanes can be fabricated at a traditional foundry. We demonstrate polarization independent phase modulation through optical beam steering tests for various input polarizations. Our fabricated device lays the foundation for commercial LCoS devices highly suitable for wavelength selective switches, holographic display, wavefront correction, and optical beam shaping.

Enhanced horizontal alignment of InGaN/GaN nanorod LEDs via insulator-based dielectrophoresis

GaN-based nanorod light emitting diodes (LEDs) are key to the development of high brightness, small pixel size, and long lifetime for high-resolution display applications. To manufacture individual nanorod LEDs as compact light sources, it is necessary to separate the nanorod LEDs from the substrate and transfer them to the electrode. Dielectrophoresis (DEP) is a highly suitable technique for transferring the individual nanorod LEDs. However, there are still challenges in achieving a high alignment yield. In this work, nanorod LEDs are successfully fabricated and separated to enhance the horizontal alignment in interdigitated electrodes via insulator-based DEP (iDEP). In iDEP, a structure is formed by inserting an insulating layer between the electrodes. This structure manipulates the electric field generated around the electrodes due to polarization by the insulating layer. This results in a relatively uniform electric field distribution on the surface of the insulating layer, thereby enhancing the horizontal alignment of the nanorod LEDs. Herein, the iDEP structure achieves significant nanorod LED alignment yield of up to 91.9 %, compared to 45.5 % for the electrode-based DEP (eDEP) technique. Furthermore, the use of a patterned insulator makes it possible to restrict 1 or 2 aligned nanorod LEDs within a specific pixel region, which is suitable for high-resolution display technologies based on nanorod LEDs.

Viewpoint-dependent lighting on polygonal holograms using bump mapping.

Holograms can be observed from different viewpoints, because light waves can be encoded to propagate in multiple directions. Thus, accurate holograms for 3D display should model viewpoint-dependent light reflections. We proposed a new, to the best of our knowledge, hologram generation method for objects represented by polygonal meshes, whose lighting changes as the viewer moves, all while rendering smooth shading using low-poly objects. The proposed method leverages bump mapping and converts it into a bump-phase map encoding the propagation frequency and then spreads the reflected light wave so that only a specific viewpoint can receive them. Simulation experiments with small pixel pitches confirm the method's high computational performance.

Reducing non-effective pixel rate and nonuniformity in AlGaN solar-blind UV focal plane detectors by controlled curvature

A 1600 × 1280 small pixel photodetector was successfully fabricated to verify the controlled curvature of the focal plane array improving the non-effective pixel rate and non-uniformity of the detector. The stress strain generated during epitaxial growth was reduced by growing a 2 μm thick AlN stress correction layer on the backside of the AlGaN/sapphire system substrate. Compared with the material without an AlN stress correction layer on the backside, material curvature reduced from 7.252 μm to 2.740 μm over a length of 0.5 cm. The non-effective pixel rate and the non-uniformity of a focal plane array have been reduced. A process was proposed to reduce the impact of misalignment generated by the flip-chip interconnection process. A solar-blind UV focal plane array was hybridized with a readout integrated circuit using an unsymmetrical flip-chip interconnection process. There is no significant change in peak spectral response, nonuniformity, non-effective pixel rate, or responsivity.

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Abstract Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of O (40 MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector’s data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 μ W with an area of less than 0.2 mm2. The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.

Simultaneous Dynamic Display of Meta‐Hologram and Meta‐Nanoprinting with High Frame Rate

AbstractDynamic holography can reconstruct realistic and highly interactive 3D scenes, offering a promising way for future display. Emerging metasurface with small pixel size and powerful light modulation capability demonstrates performance superior to traditional spatial light modulators, but dynamic meta‐holography with high information capacity and high frame rate remains a challenge. This paper presents a design scheme combining a preset polarization‐dependent metasurface with a high‐speed projection module to realize smooth dynamic display at multiple polarization states. With the projection module, the system can achieve dynamic meta‐holography at two orthogonal circular polarization states with 237 and 247 different holographic frames respectively, and grayscale meta‐nanoprinting at a linear polarization state with three different patterns. At the same time, the polarization multiplexed dynamic display scheme enables independent displays at three distinct polarization states with an extremely high frame rate (9523 frames per second). This advancement holds promise for applications in dynamic holographic display, optical encryption, virtual reality, and information storage.

Design of hexapod robot equipped with omnidirectional vision sensor for defect inspection of pipeline’s inner surface

Abstract Defect detection of inner surface of precision pipes is a crucial aspect of ensuring production safety. Currently, pipeline defect detection primarily relies on recording video for manual recognition, with urgent need to improve automation, quantification and accuracy. This paper presents a hexapod in-pipe robot with carrying capacity designed to transport the omnidirectional vision sensor to specified location within unreachable pipelines. The feasibility of the robot’s mechanical design and sensor load-carrying module is analyzed using theory calculations, motion simulations and finite element method. To address the challenges of small pixel ratio and weak background changes in panoramic images, a tiny defect segmentor (TDS) based on ResNet is proposed for detecting tiny defects on the inner surface of pipelines. The hardware and software systems are implemented, and the motion performance of the pipeline robot is validated through experiments. The results demonstrate that the robot achieves stable movement at a speed of over 0.1m/s and can adapt to pipe diameter ranging from of 110 to 130 mm. The novelty of the robot lies in providing stable control of the loaded vision sensor, with control precision of the rotation angle and the displacement recorded at 1.84% and 0.87%, respectively. Furthermore, the proposed method achieves a detection accuracy of 95.67% for tiny defects with a diameter less than 3 mm and provides defect location information. This pipeline robot serves as an essential reference for development of in-pipe 3D vision inspection system.

In-silico study of the impact of system design parameters on microcalcification detection in wide-angle digital breast tomosynthesis.

Accurate detection of microcalcifications ( ) is crucial for the early detection of breast cancer. Some clinical studies have indicated that digital breast tomosynthesis (DBT) systems with a wide angular range have inferior detectability compared with those with a narrow angular range. This study aims to (1)provide guidance for optimizing wide-angle (WA) DBT for improving detectability and (2)prioritize key optimization factors. An in-silico DBT pipeline was constructed to evaluate detectability of a WA DBT system under various imaging conditions: focal spot motion (FSM), angular dose distribution (ADS), detector pixel pitch, and detector electronic noise (EN). Images were simulated using a digital anthropomorphic breast phantom inserted with clusters. Evaluation metrics included the signal-to-noise ratio (SNR) of the filtered channel observer and the area under the receiver operator curve (AUC) of multiple-reader multiple-case analysis. Results showed that FSM degraded sharpness and decreased the SNR and AUC by 5.2% and 1.8%, respectively. Non-uniform ADS increased the SNR by 62.8% and the AUC by 10.2% for filtered backprojection reconstruction with a typical clinical filter setting. When EN decreased from 2000 to 200 electrons, the SNR and AUC increased by 21.6% and 5.0%, respectively. Decreasing the detector pixel pitch from 85 to improved the SNR and AUC by 55.6% and 7.5%, respectively. The combined improvement of a pixel pitch and EN200 was 89.2% in the SNR and 12.8% in the AUC. Based on the magnitude of impact, the priority for enhancing detectability in WA DBT is as follows: (1)utilizing detectors with a small pixel pitch and low EN level, (2)allocating a higher dose to central projections, and (3)reducing FSM. The results from this study can potentially provide guidance for DBT system optimization in the future.

Automatic wild bird repellent system that is based on deep-learning-based wild bird detection and integrated with a laser rotation mechanism

Wild bird repulsion is critical in agriculture because it helps avoid agricultural food losses and mitigates the risk of avian influenza. Wild birds transmit avian influenza in poultry farms and thus cause large economic losses. In this study, we developed an automatic wild bird repellent system that is based on deep-learning-based wild bird detection and integrated with a laser rotation mechanism. When a wild bird appears at a farm, the proposed system detects the bird’s position in an image captured by its detection unit and then uses a laser beam to repel the bird. The wild bird detection model of the proposed system was optimized for detecting small pixel targets, and trained through a deep learning method by using wild bird images captured at different farms. Various wild bird repulsion experiments were conducted using the proposed system at an outdoor duck farm in Yunlin, Taiwan. The statistical test results of our experimental data indicated that the proposed automatic wild bird repellent system effectively reduced the number of wild birds in the farm. The experimental results indicated that the developed system effectively repelled wild birds, with a high repulsion rate of 40.3% each day.

Use of Electron Beam-Induced Current Technique to Characterize Transport Properties of Narrow-Gap-Energy Materials for IR Detection

The electron beam-induced current technique (EBIC) developed at CEA-Leti has been a valuable tool for studying the transport properties of minority carriers in HdCdTe. Indeed, previous work has demonstrated the use of this technique for estimating diffusion length from the exponential decay of EBIC as a function of junction distance, as well as direct measurement of the modulation transfer function (MTF) of small pixel pitch diodes. In this work, a modulated electron beam and a lock-in amplifier are used to measure the variation in current and phase shift with the scan distance to the junction. This work is focused on the estimation of the minority carrier lifetime from the linear evolution of the phase shift as a function of junction distance.

Water Soil Availability Prediction in Coffee Land Plantations with Remote Sensing

Abstract The availability of soil water is the basis of plant growth, so its availability is important key for coffee plants growing in South Malang. Climate change makes the availability of water for these plants a complex problem because changing temperature and humidity. Remote sensing is a fast and cheap way to predict water availability in coffee plantations with large land areas and rapid climate change. The aims of this research to estimate water soil availability in coffee land plantations to meet plant water needs. The water content in coffee plantations can be estimated by combining the vegetation index values with a combination of Normalized Difference Vegetation Index (NDVI), Fractional Vegetation Cover (FVC), Land Surface Temperature (LST), and Land Surface Emissivity (LSE). The method used in this research is to make tentative maps obtained from overlays of all combining the vegetation index values. The selection of research locations is based on the area of the coffee plantation using the smallest pixel, with an area of 3.000.000 m square meters. Each location of the research location was carried out four times for sampling the soil moisture content. The results showed that the correlation value between water content and the estimation results had a correlation of 0.814, with a regression value of 0.663 and a probability value of 0.9226. This shows that it is possible to estimate the water content of coffee plantations using remote sensing made it easier for coffee farmers to take action based on actual conditions on the land.

11‐1: Invited Paper: MicroLED Displays for Augmented Reality Smart Glasses

Augmented reality smart glasses, in general, have highest requirements as compared with smart phones and watches. Its display must be of light weight (a few grams), tremendous brightness (millions of nits), low power consumption (hundreds of milliwatts), and extremely small volume (a small fraction of cubic centimeter) to allow fashionable smart glass designs that would be socially and aesthetically favored by consumers. We have been focusing on micrometer‐scale native semiconductor MicroLED integration, to create miniaturized panels and projectors, which can be seamlessly integrated into the frames of the smart glasses. Among many technical aspects of microLED displays, two key parameters will be emphasized here. First, a microLED panel must be bright and efficient at the same time, especially for red microLED panel with small pixel pitch, such as 2.5 µm. Second, a microLED technology must enable reasonable reliability at a high energy density of, such as 10 watts per square centimeter. Vertically stacked native semiconductors monolithic integration, quantum dots conversion, perovskites, etc., will be discussed, in a context of facing challenges in materials and device physics and fulfilling the two requirements. In addition, an image quality correction method on the waveguide‐microLED display module will be proposed.

Adaptive Threshold and Weighted Frequency Domain Histogram of Local Binary Patterns

Wire ropes are crucial load-bearing components in mining conveyance equipment, and machine vision is one of the methods used to assess the surface damage condition of wire ropes. In response to the light-sensitive nature of local binary patterns, which leads to issues such as differing feature values for similar textures and susceptibility to the influence of excessively large or small pixels within local windows, hindering the accurate reflection of window structure information and exacerbating the introduction of considerable feature noise, an investigation is conducted. To enhance the gradient structural information among pixels within local pixel window, an adaptive threshold binary pattern feature operator is proposed. This operator utilizes the mean and variance within the local window to balance the central pixel value, thereby enhancing the interconnection among neighboring pixels. To perform feature selection on block histograms, a block-weighted approach is employed. This approach utilizes the concept of block weighting and employs correlation coefficients to preprocess feature vectors, thereby enhancing classification accuracy. The algorithm experiments were conducted on a dataset of mine wire ropes. The results indicate that the improved local binary pattern significantly enhances the classification accuracy of the wire rope dataset, achieving an accuracy of 97.3%.

SSMA-YOLO: A Lightweight YOLO Model with Enhanced Feature Extraction and Fusion Capabilities for Drone-Aerial Ship Image Detection

Due to the unique distance and angles involved in satellite remote sensing, ships appear with a small pixel area in images, leading to insufficient feature representation. This results in suboptimal performance in ship detection, including potential misses and false detections. Moreover, the complexity of backgrounds in remote sensing images of ships and the clustering of vessels also adversely affect the accuracy of ship detection. Therefore, this paper proposes an optimized model named SSMA-YOLO, based on YOLOv8n. First, this paper introduces a newly designed SSC2f structure that incorporates spatial and channel convolution (SCConv) and spatial group-wise enhancement (SGE) attention mechanisms. This design reduces spatial and channel redundancies within the neural network, enhancing detection accuracy while simultaneously reducing the model’s parameter count. Second, the newly designed MC2f structure employs the multidimensional collaborative attention (MCA) mechanism to efficiently model spatial and channel features, enhancing recognition efficiency in complex backgrounds. Additionally, the asymptotic feature pyramid network (AFPN) structure was designed for progressively fusing multi-level features from the backbone layers, overcoming challenges posed by multi-scale variations. Experiments of the ships dataset show that the proposed model achieved a 4.4% increase in mAP compared to the state-of-the-art single-stage target detection YOLOv8n model while also reducing the number of parameters by 23%.

A prototype Radiation Energy Measuring Integrated Circuit with an asynchronous current-pulse reset block providing analog-to-digital conversion in 28 nm CMOS

In this paper we introduce a prototype Radiation Energy Measuring Integrated Circuit (REMIC) fabricated in a 28 nm CMOS process. The chip operates in a single-photon counting (SPC) mode and contains 100 pixels with a size of 50 μm × 50 μm. It is designed for precise energy measurements using asynchronous analogue-to-digital conversion. The proposed architecture allows both fast signal processing and precise energy measurement of incoming photons to be performed independently in each pixel, occupying a small pixel area. The integrated circuit (IC) has dimensions of 1.1 mm × 1.1 mm and is currently undergoing preliminary measurements. The paper focuses on the methodology used to mitigate process variations in each of the recording channels.

TCI-Former: Thermal Conduction-Inspired Transformer for Infrared Small Target Detection

Infrared small target detection (ISTD) is critical to national security and has been extensively applied in military areas. ISTD aims to segment small target pixels from background. Most ISTD networks focus on designing feature extraction blocks or feature fusion modules, but rarely describe the ISTD process from the feature map evolution perspective. In the ISTD process, the network attention gradually shifts towards target areas. We abstract this process as the directional movement of feature map pixels to target areas through convolution, pooling and interactions with surrounding pixels, which can be analogous to the movement of thermal particles constrained by surrounding variables and particles. In light of this analogy, we propose Thermal Conduction-Inspired Transformer (TCI-Former) based on the theoretical principles of thermal conduction. According to thermal conduction differential equation in heat dynamics, we derive the pixel movement differential equation (PMDE) in the image domain and further develop two modules: Thermal Conduction-Inspired Attention (TCIA) and Thermal Conduction Boundary Module (TCBM). TCIA incorporates finite difference method with PMDE to reach a numerical approximation so that target body features can be extracted. To further remove errors in boundary areas, TCBM is designed and supervised by boundary masks to refine target body features with fine boundary details. Experiments on IRSTD-1k and NUAA-SIRST demonstrate the superiority of our method.

The Small Pixel Effect in Ultra-High-Resolution Photon-Counting CT of the Lumbar Spine.

Image acquisition in ultra-high-resolution (UHR) scan mode does not impose a dose penalty in photon-counting CT (PCCT). This study aims to investigate the dose saving potential of using UHR instead of standard-resolution PCCT for lumbar spine imaging. Eight cadaveric specimens were examined with 7 dose levels (5-35 mGy) each in UHR (120 × 0.2 mm) and standard-resolution acquisition mode (144 × 0.4 mm) on a first-generation PCCT scanner. The UHR images were reconstructed with 3 dedicated bone kernels (Br68 [spatial frequency at 10% of the modulation transfer function 14.5 line pairs/cm], Br76 [21.0], and Br84 [27.9]), standard-resolution images with Br68 and Br76. Using automatic segmentation, contrast-to-noise ratios (CNRs) were established for lumbar vertebrae and psoas muscle tissue. In addition, image quality was assessed subjectively by 19 independent readers (15 radiologists, 4 surgeons) using a browser-based forced choice comparison tool totaling 16,974 performed pairwise tests. Pearson's correlation coefficient ( r ) was used to analyze the relationship between CNR and subjective image quality rankings, and Kendall W was calculated to assess interrater agreement. Irrespective of radiation exposure level, CNR was higher in UHR datasets than in standard-resolution images postprocessed with the same reconstruction parameters. The use of sharper convolution kernels entailed lower CNR but higher subjective image quality depending on radiation dose. Subjective assessment revealed high interrater agreement ( W = 0.86; P < 0.001) with UHR images being preferred by readers in the majority of comparisons on each dose level. Substantial correlation was ascertained between CNR and the subjective image quality ranking (all r 's ≥ 0.95; P < 0.001). In PCCT of the lumbar spine, UHR mode's smaller pixel size facilitates a considerable CNR increase over standard-resolution imaging, which can either be used for dose reduction or higher spatial resolution depending on the selected convolution kernel.

First experimental evaluation of count-rate performance for micrometre resolution deep silicon detector

Objective. An ultra-fine-pitch deep silicon detector has been developed for clinical photon-counting computed tomography (CT). With a small pixel size of 14 × 650 μm2, it has shown potential to reach micrometre spatial resolution in previous simulation studies. A detector prototype with such geometry has been manufactured, and we report on the first experimental evaluation of its count-rate performance. Approach. The measurement was carried out at MAX IV synchrotron laboratory with 35 keV monochromatic x-rays. By inserting tungsten attenuators of 50, 75, 100, 150, 200, 225, 325 μ m-thicknesses into the beam, the response of the detector to fluence rates from 3.3 × 107 to 1.3 × 1011 mm−2 s−1 was characterized. Main results. The measurement result showed that the detector exhibited count rate linearity up to 6.66 × 108 mm−2 s−1 with 13% count loss and was still functional at count rate up to 2.9 × 1010 mm−2 s−1. A semi-nonparalyzable dead-time model was fitted to the count-rate behaviour of the detector, showing great agreement with the measured data, with an estimated nonparalyzable dead time of 2.9 ns. Significance. This is the first experimental evaluation of the count-rate performance for a deep silicon detector with such small pixel geometry. The results suggest that this type of detector shows the potential to be used at fluence rates encountered in clinical CT with little count loss due to pile-up.