Resolution Color Research Articles

All-dielectric structural coloration empowered by bound states in the continuum.

The technological requirements of low-power and high-fidelity color displays have been instrumental in driving research into advanced coloration technologies. At the forefront of these developments is the implementation of dye-free approaches, which overcome previous constraints related to color resolution and fading. Resonant dielectric nanostructures have emerged as a promising paradigm, showing great potential for high efficiency, high color saturation, wide gamut palette, and image reproduction. However, they still face limitations related to color accuracy, purity, and simultaneous brightness tunability. Here, we demonstrate an all-dielectric metasurface empowered by photonic bound states in the continuum (BICs), which supports sharp resonances throughout the visible spectral range, ideally suited for producing a wide range of structural colors. The metasurface design consists of TiO2 ellipses with carefully controlled sizes and geometrical asymmetry, allowing versatile and on-demand variation of the brightness and hue of the output colors, respectively.

Optical Image Processing using Eulerian Amplification

Recent advancements in digital photography, particularly through mobile phone cameras, microscopes, and satellite imaging, have made high-resolution image capture increasingly accessible. However, these captured images often contain subtle changes in color resolution and density that are challenging to observe with the naked eye. This study explores the application of Eulerian amplification as a method to detect and enhance such small-amplitude variations, making them visible for improved analysis. Unlike traditional approaches, Eulerian methods are particularly effective for processing smooth structures and high-quality printed materials where minor amplifications in color can reveal significant grading details. Using a pixel-by-pixel Eulerian path analysis, this method allows for a detailed comparison of color intensity values on a fine 8-bit scale, which ranges from 0 to 255. Through this analysis, color distribution patterns are visualized across the spatial structure of the image, which is particularly beneficial for identifying specific variations in quality in printed materials, such as highly graded cards. To manage large image structures, spatial decomposition using a multi-level Gaussian pyramid technique is employed. By applying temporal filtering within select frequency bands (0.4–4 Hz) at a coarse pyramid level, the algorithm effectively pools spatial data, enabling the detection of color density shifts that may indicate image defects. The amplified image data is further processed using a classifier neural network, which provides high sensitivity and specificity in detecting edge defects, image centering issues, scuffs, and breakages. The system demonstrates promising results in identifying true positives while maintaining low false-negative rates, thus confirming the reliability of deep machine learning algorithms in high-sensitivity defect detection. This paper presents the significance of Eulerian amplification in optical image processing, offering a robust tool for precise, automated defect detection across a variety of high-resolution image types.

Enhanced colorimetric analysis substrate based on graphene oxide open-close actuator

Traditional colorimetric sensors often suffer from low color resolution and insufficient sensitivity. Therefore, for colorimetric detection to serve as a reliable quantitative analysis technique, an enhanced substrate with high sensitivity and repeatability is required. This strategy employs an interfacial network constructed between two-dimensional graphene oxide (GO) lamellar structures to create a substrate for colorimetric analysis. Under normal conditions, the newly synthesized GO inhibits oxidative activity due to van der Waals forces between the lamellar interfaces, resulting in the GO actuator being in the closed state. During Ag+ colorimetric analysis, the GO interlayer adsorption of silver nanoparticles (AgNPs) disrupts the interlayer van der Waals forces, releasing its oxidase activity and significantly enhancing Ag+ oxidation. The resulting actuator exhibits a faster driving speed (0.045 μM/s), excellent sensitivity, and stability. Additionally, the reducing properties of dopamine (DA) can be utilized to encapsulate the GO actuator with polydopamine, closing the GO actuator. Similarly, the reducing property of ascorbic acid (AA) can be utilized to restore the GO actuator to a closed state. These distinct reduction mechanisms allow for an effective visual distinction between AA and DA. With these advantages, the actuator can be developed into simple analytical tools (such as Ag+ colorimetric test strips and DA and AA test kits), demonstrating significant potential for practical application.

Ultrasonographic images and correspondence with real color sectioned images of the upper limb.

For basic training in ultrasonography (US), medical students and residents must learn cross-sectional anatomy. However, the present educational material is not sufficient to learn the sectional anatomy for US. This study aimed to provide a criterion for reading ambiguous structures on US images of upper limb through the sectioned images of Visible Korean. US images of the right arm of a volunteer were scanned (28 planes). For comparison with US images, the sectioned images of the right upper limb (24 bits color, 0.5mm intervals, 0.06mm × 0.06mm sized pixel) were used. After the volume model was constructed from the sectioned images using MRIcroGL, new sectioned images of 28 planes corresponding to the US images of 28 planes were created by adjusting the slope of the volume model. In all images, the anatomical terms of 59 structures from the shoulder to the fingers were annotated. In the atlas, which consists of 28 sets of US images and sectioned images of various slope planes, 59 structures of the shoulder, arm, elbow, wrist, palm, and fingers were observed in detail. We were able to interpret the ambiguous structures on the US images using the sectioned images with high resolution and actual color. Therefore, to learn the cross-sectional anatomy for US, the sectioned images from the Visible Korean project were deemed to be the suitable data because they contained all human gross anatomical information.

Phase change polymer-based structural color photonic films for contactless and inkless writing irreversibly

Thermal-responsive photonic crystals (PCs) have attracted considerable interest due to their triggerable and adjustable optical capabilities, which are promising for various applications. However, developing a mechanism for rapid and irreversible structural color transformation in PCs that enables contactless and inkless writing has significant research value. Herein, phase change polymers are incorporated into functional optical platforms capable of rapid and irreversible structural color transformation in response to thermal stimuli. In crystalline state, phase change polymers used as inverse opal scaffolds in photonic films produce structural color with high saturation. The collapse of the highly ordered inverse opal structure, driven by thermal-mediated transformation during the crystalline/amorphous conversion of phase change polymers, is identified as the primary mechanism for achieving rapid and irreversible structural color transformation. These significant color variations between the inverse opal and collapsed structures provide high color contrast and resolution. The photonic films exhibit excellent hydrophobicity, solvent resistance, and storage stability. Additionally, incorporating the photothermal material carbon black (CB) enhances color saturation and imparts efficient photothermal conversion ability to films. By modulating the photothermal effect via near-infrared (NIR) laser light, phase change polymer-based structural color photonic films can achieve a permanent configuration at 42 °C, resulting in high-resolution images. These outstanding features offer a feasible method for next-generation innovative inkless writing and printing.

High Resolution Images of Human Meibum Spread on Saline.

Understanding of the role of the tear film lipid layer (TFLL) in evaporative dry eye requires knowledge of its structure. X-ray studies show 11.1-nm thick lamellae in meibum at tear film temperature (approximately 35°C), whereas below 30°C, 4.88-nm thick lamellae predominate. Here, high resolution microscopy of meibum spread on saline is studied as a function of temperature, to compare with x-ray results. A purpose-built high resolution color microscope, previously used to study the TFLL, was used to study meibum from 10 subjects. It was spread on buffered saline at near 40°C, and allowed to cool to room temperature. Analytical methods from previous studies were applied to measure meibum and lamellar thickness. Initially, an irregular "island" was formed, surrounded by a "background layer" of 7.8 ± 0.3 nm thickness. Dewetting of the meibum layer always occurred, leading to the formation of lens-shaped droplets. Below 30°C, the lenses start to emit "tails" having a multilamellar structure containing up to about 49 lamellae superimposed on the background layer, each lamella being 4.82 ± 0.13 nm thick. Below 30°C, meibum spread on saline shows a multilamellar structure like the 4.88 nm thickness in x-ray studies, demonstrating the ability to observe and measure tightly stacked lamellae. In contrast, above 30°C, the 11.1 nm lamellae were not observed as in x-ray studies, indicating that these lamellae were not tightly stacked but may be separated by disordered lipid. The role of these findings in evaporative dry eye is discussed.

High-performance color and fluorescence switching of cotton fabrics via light-induced proton transfer strategy of spiropyran sulfonate molecule

Light-responsive color-switching materials have garnered persistent interest recently due to their passive response to external stimuli and manifestation of notable visual color variations. Nonetheless, their development into high-end products has been hindered by unsatisfactory overall performance, characterized by challenges such as the inability to combine color contrast and retention time, poor repeatability, and reliance on a single coloring mode. Herein, we present a negative photochromic cotton fabric (NPCF) capable of real-time dual output of optical signals (color change or fluorescence emission), featuring high color contrast and resolution, excellent reversibility, and facile multicolor printing. These attributes stem from the utilization of a unique photoinduced proton transfer (PPT) strategy exhibited by the designed and synthesized spiropyran sulfonate molecule (MC-NO2). Guided by this strategy, NPCF demonstrates significant color changes and fluorescence switching in a real-time and highly reversible manner, leveraging the remote non-contact and non-destructive nature of visible light. Moreover, direct blending of MC-NO2 with commercially available water-soluble non-stimuli-responsive dyes enables customization of various photosensitive color systems for straightforward multi-color printing, aligning well with the environmental principles of green printing. This study serves as a valuable reference for the advancement and design of diverse high-performance, switchable materials suitable for the production of high-end products.

Impact of Color Space and Color Resolution on Vehicle Recognition Models.

In this study, we analyze both linear and nonlinear color mappings by training on versions of a curated dataset collected in a controlled campus environment. We experiment with color space and color resolution to assess model performance in vehicle recognition tasks. Color encodings can be designed in principle to highlight certain vehicle characteristics or compensate for lighting differences when assessing potential matches to previously encountered objects. The dataset used in this work includes imagery gathered under diverse environmental conditions, including daytime and nighttime lighting. Experimental results inform expectations for possible improvements with automatic color space selection through feature learning. Moreover, we find there is only a gradual decrease in model performance with degraded color resolution, which suggests the need for simplified data collection and processing. By focusing on the most critical features, we could see improved model generalization and robustness, as the model becomes less prone to overfitting to noise or irrelevant details in the data. Such a reduction in resolution will lower computational complexity, leading to quicker training and inference times.

A Thermo-Responsive MOFs for X-Ray Scintillator.

Thermo-responsive smart materials have aroused extensive interest due to the particular significance of temperature sensing. Although various photoluminescent materials are explored in thermal detection, it is not applicable enough in X-ray radiation environment where the accuracy and reliability will be influenced. Here, a strategy is proposed by introducing the concept of radio-luminescent functional building units (RBUs) to construct thermo-responsive lanthanide metal-organic frameworks (Ln-MOFs) scintillators for self-calibrating thermometry. The rational designs of RBUs (including organic ligand and Tb3+/Eu3+) with appropriate energy levels lead to high-performance radio-luminescence. Ln-MOFs scintillators exhibit perfect linear response to X-ray, presenting low dose rate detection limit (min ≈156.1 nGyairs-1). Self-calibrating detection based on ratiometric XEL intensities is achieved with good absolute and relative sensitivities of 6.74 and 8.1%K-1, respectively. High relative light yield (max ≈39000 photons MeV-1), imaging spatial resolution (max ≈18 lpmm-1), irradiation stability (intensity ≈100% at 368 K in total dose up to 215 Gyair), and giant color transformation visualization benefit the applications, especially the in situ thermo-responsive X-ray imaging. Such strategy provides a promising way to develop the novel smart photonic materials with excellent scintillator performances.

Visible Korean based on true color sectioned images for making realistic digital human, twenty years' record: a review.

Visible Korean (VK) consists of two-dimensional (2D) images and three-dimensional (3D) models. The VK is used in various educational tools and research sources for anatomy. In this paper, we report on the records of the VK over 20years. Research papers related to Visible Korean were reviewed. Through this report of VK records, we highlighted the essential points for making true color and ultra-high-resolution sectioned images of human and animal bodies, for making various 2D and 3D applications from the sectioned images, and for good use of the sectioned images and their applications. In this metaverse age that various virtual environments are required in medical education and research, the VK dataset meets the reality of virtual human models as fundamental data owing to the actual color and high resolution of the VK dataset.

Association between Residential Greenness and Allostatic Load: A Cohort Study.

The association between residential greenness and allostatic load (AL), a marker of composite physiological burden and predictor of chronic disease, remains understudied. This study comprised 212,600 UK Biobank participants recruited over 2007 and 2010 at the baseline. Residential greenness was modeled as the normalized difference vegetation index (NDVI) from high spatial resolution (0.50 m) color infrared imagery and measured within a 0.5 km radial catchment. AL was measured as a composite index from 13 biomarkers comprising three physiological systems (metabolic, cardiovascular, and inflammatory systems) and two organ systems (liver and kidney). Multilevel mixed-effects generalized linear models with a random intercept for UK Biobank assessment centers were employed to examine the association between residential greenness and AL. Each interquartile range (IQR = 0.24) increment in NDVI greenness was associated with lower AL (beta (β) = -0.28, 95% confidence interval (CI) = -0.55, -0.01). Consistently, relative to the lowest NDVI greenness quintile, participants in the highest quintile had lower AL (β = -0.64, 95% CI = -1.02, -0.26). The proportion of the association between greenness and AL mediated by the physical activity was 3.2%. In conclusion, residential greenness was protectively associated with AL, a composite marker of wear and tear and general health.

Programmable directional color dynamics using plasmonics

Adaptive multicolor filters have emerged as key components for ensuring color accuracy and resolution in outdoor visual devices. However, the current state of this technology is still in its infancy and largely reliant on liquid crystal devices that require high voltage and bulky structural designs. Here, we present a multicolor nanofilter consisting of multilayered ‘active’ plasmonic nanocomposites, wherein metallic nanoparticles are embedded within a conductive polymer nanofilm. These nanocomposites are fabricated with a total thickness below 100 nm using a ‘lithography-free’ method at the wafer level, and they inherently exhibit three prominent optical modes, accompanying scattering phenomena that produce distinct dichroic reflection and transmission colors. Here, a pivotal achievement is that all these colors are electrically manipulated with an applied external voltage of less than 1 V with 3.5 s of switching speed, encompassing the entire visible spectrum. Furthermore, this electrically programmable multicolor function enables the effective and dynamic modulation of the color temperature of white light across the warm-to-cool spectrum (3250 K–6250 K). This transformative capability is exceptionally valuable for enhancing the performance of outdoor optical devices that are independent of factors such as the sun’s elevation and prevailing weather conditions.

The Development of Various Methods for Object Tracking and Classification in Thermal Videos

Nowadays, thermal cameras play a major role because of its temperature-based photography in many applications such as video surveillance, monitoring electronics/electrical machines, forest monitoring, monitoring babies/adult patients, and suspicious object detection. Tracking pedestrians in thermal video is a major task for such applications. Thermal cameras usually create images based on temperature emitted by the object only and not on the lighting conditions and outdoor environment conditions. But still thermal images have constraints like no texture or colour information, more number of dead pixels, low resolution, and noticeable visual colour patterns in case of any temperature variations. So the challenge in tracking pedestrians in thermal videos is tracking objects/pedestrians throughout the video without an identity switch by overcoming these constraints which may mislead the tracking process. To overcome these constraints, the proposed system uses tri feature matrix (TFM) as an object descriptor which is used to uniquely identify and represent objects in thermal images. TFM is represented in more compact way as a triple matrix. It is a simple and accurate descriptor suitable for tracking objects in thermal video sequences without an identity switch. The proposed Pedestrian tracking system uses most of the advantages of thermal cameras by overcoming challenges in thermal videos effectively based on a novel descriptor TFM. The proposed system is evaluated with various data sets, and the results are analysed using true positive, true negative, false negative, false positive, accuracy, precision, recall, F-score, global identity mismatch (GMME) and track matching error (TME). The performance metrics such as accuracy, precision, recall, F-score, GMME and TME are computed as 99%, 100%, 99%, 99%, 2.3%, and 2.1%, respectively. From the observation, it is found that the performance of proposed TFM-based system is significantly improved. The experimental result shows that the proposed system achieved more accurate tracking compared to the conventional methods

EVALUATION OF DIAGNOSTIC EFFICACY OF ULTRASONOGRAPHY AND COMPUTED TOMOGRAPHY IN NECK MASSES

INTRODUCTION A neck mass can be frequently seen in clinical practice. The close proximity of various structures in the neck creates a diagnostic problem. The precise anatomical location and imaging appearances are important for accurate diagnosis and formulating the differential diagnoses of neck masses. The present study was undertaken to evaluate diagnostic efficacy of ultrasonography and computed tomography in neck masses. AIM To assess the efficacy of Ultrasonography and Computed Tomography in the evaluation of neck masses. MATERIAL AND METHODS This study was conducted in the department of E.N.T. in co-ordination with the department of Radiodiagnosis, Oncology and Pathology at LLR & Associated Hospital, GSVM, Medical College, Kanpur.Total number of patients included were 50. RESULT Of the 50 patients of age group 3-70 years who presented with neck masses, majority of patients belonged to 20-30 years of age group (10 patients , 20% ) with male dominance 62% ( 31 out of 50 patients).Maximum number of neck swelling were of lymph node origin14(28%). Out of those lymph nodes maximum were malignant. Out of the non nodal masses 36(72%), maximum were benign. CONCLUSION High resolution sonography and color Doppler is a useful modality for diagnostic evaluation of neck masses in every age group. It is simple, noninvasive and inexpensive diagnostic tool. CT ensures accurate anatomical localization and lesion characterization in benign lesions. In malignant tumors, it is useful for staging and provides essential information about the tumor extent that directly affects the surgical approach necessary for curative resection. Ke y w o r d s : U l t r a s o n o g r a p h y, C o m p u t e d Tomography, Neck Masses

The software for improvement of image quality after enlargement

In the paper digital images of various formats were investigated. The different vector image formats have different color rendering capabilities. The main task was to achieve a result of refinement of the random low resolution color raster image without quality and resolution loss. The biggest advantage of using specific vector or compressed raster formats is the ability of scaling without quality loss and comparatively small file size. This eases vector images transfer through networks. In the article a specific algorithm of raster images refinement was investigated, particularly the method of raster images refinement based on combination of interpolation algorithms with and without square root of the color values. The key point of the method is comparison and combination of vertical, horizontal and diagonal interpolation that allows to achieve better precision on color depth calculation. This exact method was never used in commercial of scientific software though there are different variation of combined interpolation methods similar to current one. In this paper two different approaches to image matrix re-calculation during image refinement were tested, in order to research how root squaring the value of color depth would affect the target color value. The result shows that this approach allows to keep more details in shadows and save contours during interpolation though the images lose somewhat of color depth. The experiment shows that this interpolation method with square rooting color values allows to enlarge and refine color images with complex tone curve structure and keep details of the objects in place, though color depth is worsened especially in deepest shades and blacks. On the opposite the method of combined interpolation without root squaring gives significantly better result with color interpolation but loses details in the dark areas of the initial image. The suggested method can be used in a number of different areas

Ultra-high-resolution reflected-light imaging for dendrochronology

Dendroclimatic reconstructions play a key role in contextualizing recent climate change by improving our understanding of past climate variability. The Blue Intensity (BI) measurement technique is gaining prominence as a more accessible alternative to X-ray densitometry for producing climatically highly-sensitive tree-ring predictors. Nevertheless, accurately representing low-frequency trends and high-frequency extremes using scanner-based BI remains a challenge due to color biases and resolution limitations. Herein we introduce several methodological advances in sample surfacing, imaging, and image processing which yield measurement series analogous to BI from ultra-high-resolution (UHR; ∼74 700 dpi) images. Such series capture changes in tree-ring anatomical density by representing wood anatomical structure using binary (i.e., black-white) segmentation of sample images. We refer to this novel technique as Binary Surface Intensity (BSI). By utilizing a UHR system and entirely eliminating color and light intensity as variables, the most substantial drawbacks of scanner BI (i.e., discoloration and resolution biases) are bypassed, resulting in more accurate representations of low-frequency climatic trends and high-frequency extremes. Comparisons of several chronologies developed with the BSI and BI techniques, including a multiparameter dataset from Björklund et al. (2019), showed that BSI datasets outperform BI in terms of common signal (r-bar), but also contain strong climatic signals that can exceed those obtained from BI and X-ray density, and even match density datasets based on quantitative wood anatomy. However, measurement software advancements are still required to unlock the full potential of tree-ring parameters produced using the BSI technique. Ongoing development of this new technique will not only aid the attainment of long unbiased chronologies by overcoming color biases and resolution limitations, but also holds promise for unlocking UHR analyses of surface anatomical (sQWA) parameter datasets from reflected-light images. These advances will lead to more accurate tree-ring-based paleoclimatic reconstructions and could also serve a wider range of dendrochronological applications.

Charge Management Enables Efficient Spontaneous Chromatic Adaptation Bipolar Photodetector.

Solution-processed photodetectors have emerged as promising candidates for next-generation of visible-near infrared (vis-NIR) photodetectors. This is attributed to their ease of processing, compatibility with flexible substrates, and the ability to tune their detection properties by integrating complementary photoresponsive semiconductors. However, the limited performance continues to hinder their further development, primarily influenced by the difference of charge transport properties between perovskite and organic semiconductors. In this work, a perovskite-organic bipolar photodetectors (PDs) is introduced with multispectral responsivity, achieved by effectively managing charges in perovskite and a ternary organic heterojunction. The ternary heterojunction, incorporating a designed NIR guest acceptor, exhibits a faster charge transfer rate and longer carrier diffusion length than the binary heterojunction. By achieving a more balanced carrier dynamic between the perovskite and organic components, the PD achieves a low dark current of 3.74nAcm-2 at -0.2V, a fast response speed of <10 µs, and a detectivity of exceeding 1012 Jones. Furthermore, a bioinspired retinotopic system for spontaneous chromatic adaptation is achieved without any optical filter. This charge management strategy opens up possibilities for surpassing the limitations of photodetection and enables the realization of high-purity, compact image sensors with exceptional spatial resolution and accurate color reproduction.

Ultra‐High Detectivity MBene/Si vdW Schottky Photodiode for Color Single‐Pixel Imaging

AbstractThe color single‐pixel imaging (SPI) has received significant attention due to its ability to provide more comprehensive real‐world information compared to grayscale imaging. The performance of single‐pixel photodetector is the primary determinant for the quality of color SPI. Silicon‐based Schottky photodiodes provide desirable qualities for the essential requirements of high detectivity in high resolution color SPI. Herein, a novel Mo4/3B2‐XTZ/Si hexagonal micro‐hole array (SiHMA) van der Waals (vdW) Schottky photodiode is first constructed for application in color SPI. The resultant Schottky junction possesses a Schottky barrier height up to 1.18 eV, thus leading to a dark current density of 1.47 × 10−13 A cm−2 and an ultra‐high detectivity of 4.4 × 1014 Jones at zero bias voltage, which are superior to most of Si‐based Schottky photodiodes reported and even some commercial Si photodiodes thus far. Importantly, the high detectivity and low dark current density of the photodiode allow for the use as a photodetector in high resolution Hadamard SPI. Notably, a high‐quality 256 × 256‐pixel color image can be successfully achieved under even 25% sampling rate without an additional filter circuit. This work opens an avenue toward the fabrication of high detectivity Schottky photodiode for high quality color SPI.

Target detection algorithm based on super- resolution color remote sensing image reconstruction

An improved generative adversarial network model is adopted to improve the resolution of remote sensing images and the target detection algorithm for color remote sensing images. The main objective is to solve the problem of training super-resolution reconstruction algorithms and missing details in reconstructed images, aiming to achieve high-precision detection of medium and low-resolution color remote sensing targets. First, a lightweight image super-resolution reconstruction algorithm based on an improved generative adversarial network (GAN) is proposed. This algorithm combines the pixel attention mechanism and up-sampling method to restore image details. It further integrates edge-oriented convolution modules into traditional convolution to reduce model parameters and achieve better feature collection. Then, to further enhance the feature collection ability of the model, the YOLOv4 object detection algorithm is also improved. This is achieved by introducing the Focus structure into the backbone feature extraction network and integrating multi-layer separable convolutions to improve the feature extraction ability. The experimental results show that the improved target detection algorithm based on super resolution has a good detection effect on remote sensing image targets. It can effectively improve the detection accuracy of remote sensing images, and have a certain reference significance for the realization of small target detection in remote sensing images.

85‐3: High‐Transmittance, High‐Resolution Color Filters with Tailored Structures for Micro‐displays

The needs for high‐performances display is increased while electronics have been integrated into various materials. Compared to conventional display, micro‐type displays are required with miniaturized and high‐ intensity performances for various applications, such as AR/VR, smart contact lens. Common light source‐based approach is a simple way to demonstrate the micro‐display with high‐transmittance, high‐ resolution color filters (CFs). Here, we address the requirements for CFs in color and processing aspects. Our CFs minimize the polymer binder to be easily modified the pattern shapes with high‐transmittance. The CF is easily controlled the shape of pattern with high‐resolution (~2μm). This CF is able to be applied various micro‐light sources (μ‐LED, μ‐OLED). Thus, we believe that it would be one of promising solution for micro‐display applications.