Image Mosaic Research Articles

INVESTIGATION OF THE POSSIBILITIES OF ENAMEL GRAINS FOR THE FORMATION OF MICROMOSAICS

The paper investigates the possibilities of grains from hot enamels for the formation of micromosaics. Enamel grain with a diameter of 0.4…5.0 mm is made from pieces of crushed hot enamels that acquire a spherical shape during firing in a muffle furnace or with the help of a gas burner flame. The mosaic image is formed by densely laying out on a metal base with an applied adhesive layer of enamel grains of the same or different diameter in accordance with the artistic idea. Enamel grain from hot enamels has high techno-logical and aesthetic characteristics characteristic of hot enamels: hardness, durability, wide colour palette, beautiful shine, etc. All this makes enamel grain a promising material for mosaic work. The technique of mi-cromosaic from enamel grains has the widest potential for decorating jewellery and art products, as it al-lows you to embody any design ideas.

U-net with ResNet-34 backbone for dual-polarized C-band baltic sea-ice SAR segmentation

Abstract In this study, the U-net with ResNet-34, i.e. a residual neural network with 34 layers, backbone semantic segmentation network is applied to C-band sea-ice SAR imagery over the Baltic Sea. Sentinel-1 Extra Wide Swath mode HH/HV-polarized SAR data acquired during the winter season 2018–2019, and corresponding segments derived from the daily Baltic Sea ice charts were used for training the segmentation algorithm. C-band SAR image mosaics of the winter season 2020–2021 were then used to evaluate the segmentation. The major objective was to study the suitability of semantic segmentation of SAR imagery for automated SAR segmentation and also to find a potential replacement for the outdated iterated conditional modes (ICM) algorithm currently in operational use. The results compared to the daily Baltic Sea ice charts and the operational ICM segmentation and visual interpretation were encouraging from the operational point of view. Open water areas were located very well and the oversegmentation produced by ICM was significantly reduced. The correspondence between the ice chart polygons and the segmentation results was also reasonably good. Based on the results, the studied method is a potential candidate to replace the operational ICM SAR segmentation used in the Copernicus Marine Service automated sea-ice products at Finnish Meteorological Institute.

An Image-based Search for Pulsar Candidates in the MeerKAT Bulge Survey

We report on the results of an image-based search for pulsar candidates toward the Galactic bulge. We used mosaic images from the MeerKAT radio telescope that were taken as part of a 173 deg2 survey of the bulge and Galactic center of our Galaxy at L band (856–1712 MHz) in all four Stokes I, Q, U, and V. The image rms noise levels of 12–17 μJy ba−1 represent a significant increase in sensitivity over past image-based pulsar searches. Our primary search criterion was circular polarization, but we used other criteria, including linear polarization, in-band spectral index, compactness, variability, and multiwavelength counterparts to select pulsar candidates. We first demonstrate the efficacy of this technique by searching for polarized emission from known pulsars and comparing our results with measurements from the literature. Our search resulted in a sample of 75 polarized sources. Bright stars or young stellar objects were associated with 28 of these sources, including a small sample of highly polarized dwarf stars with pulsar-like steep spectra. Comparing the properties of this sample with the known pulsars, we identified 30 compelling candidates for pulsation follow-up, including two sources with both strong circular and linear polarization. The remaining 17 sources are either pulsars or stars, but we cannot rule out an extragalactic origin or image artifacts among the brighter, flat-spectrum objects.

Atomic force microscopy wide-field scanning imaging using homography matrix optimization

During the offline combination of multiple atomic force microscopy (AFM) images, changes in probe displacement can be affected by dynamic noise, leading to dislocation and tearing in the stitching. To overcome this, we designed a homography matrix optimization method to describe the relative positional relationship between images by constructing the original image matrix and applying singular value decomposition to denoise the homography matrix. Additionally, we implemented a scale-invariant feature transform (SIFT) to extract feature points. To verify the effectiveness of this method, the SIFT + RANSAC (R), SIFT + affine transformation (AT), and oriented FAST and rotated BRIEF (ORB) algorithms were compared with the proposed algorithm. The experimental results demonstrate that the proposed method precisely computes the transformation matrix, thereby guaranteeing the geometric consistency of mosaic imaging. The proposed method preserves the intricate details of the original image and enhances the stitching quality of wide-field images.

Rapid Detection of Single Bacteria Using Filter-Array-Based Hyperspectral Imaging Technology.

Rapid and accurate detection of bacterial pathogens is crucial for preventing widespread public health crises, particularly in the food industry. Traditional methods are often slow and require extensive labeling, which hampers timely responses to potential threats. In response, we introduce a groundbreaking approach using filter-array-based hyperspectral imaging technology, enhanced by a super-resolution demosaicking technique. This innovative technology streamlines the detection process and significantly enhances the resolution of mosaic hyperspectral imaging. By utilizing a snapshot hyperspectral camera with a 15 ms integration time, it facilitates the identification of bacteria at the single-cell level without requiring chemical labels. The integration of a 3D convolutional neural network optimizes the recognition of pathogenic bacteria, achieving an impressive accuracy of 91.7%. Our approach dramatically improves the efficiency and effectiveness of bacterial detection, providing a promising solution for critical applications in public health and the food industry.

Michael Tippett: Specification of the Work for Orchestra and Soprano "Byzantia"

The purpose of the research is to reveal the deep image-sound layers and features of the Irish bardic tradition in the work of M. Tippett through the prism of the work for orchestra and soprano "Byzantium". The methodological basis of the research is historical-conceptual, hermeneutic method and comparative analysis of factual data based on the works of Thomas Weiskel, David Clark, Edward Venn, and Meirion Bowen. Scientific novelty. For the first time in the Ukrainian art history segment, M. Tippett's work for orchestra and soprano "Byzantium" was analysed with an emphasis on the dramaturgy of the composition, cyclical elements, metaphorical sound images, symbolism and characteristic features of the musical and poetic tradition of Irish bards. Conclusions. Biographical collisions of M. Tippett influenced his creative aspirations and attitude to the surrounding world. M. Tippett's aesthetic views are a dialogue between romantic aspirations and sceptical realism of the modern era. Michael Tippett's musical language absorbed both tradition and the entire palette of accumulated world musical experience, as well as duality of meanings, symbolism, imagery and conflict. The work analyses the composition for orchestra and soprano "Byzantium" by M. Tippet, which is based on the mosaic of images, the logical sequence of musical motifs, and cyclicity. It is necessary to highlight the fragmentary nature of musical sections, variable motifs, the presence of contrasting material, the symbolism of magical, changing life force as secular ephemerality, the destruction of the musical text using the technique of expansion and fragmentation. Thus, the composition "Byzantium" is a reincarnation of Irish cultural nationalism in the aspect of traditional forms of bardic poetry. The musical language of M. Tippett in the work "Byzantium" is based on the forms crystallised by the work of L. Beethoven and updated by the musical context of modern and postmodern.

Automatic tiling method for mosaic ceramic art images based on subpixel edge fitting localization and collaborative operation of multiple manipulators

Mosaic ceramics are not limited to use solely as building materials, they also possess artistic value. Artists can create images by arranging and combining mosaic ceramics, resulting in a perfect fusion of large-scale public art for external walls and ceramic materials. However, the current approach for artists to create mosaic ceramic exterior wall art images involves manual laying and assembling of individual mosaic ceramics. This manual process suffers from issues such as low efficiency, eye fatigue, selection errors, and the risk of high-altitude operations. These challenges significantly impact the quality and efficiency of creating mosaic ceramic exterior wall art image images. To address these problems, this paper proposes an automatic mosaic ceramic art image stitching method based on subpixel edge fitting positioning and collaborative operation of multiple robotic arms. Additionally, a new U + I type conveying method is designed for efficient and space-saving transportation of mosaic ceramics. Experimental results demonstrate a high success rate of recognition, absorption, and placement of multi-color mosaic ceramics using this method reaching 95.45%, with a positioning error within 0.5 mm. The method can also adapt to varying levels of light intensity or noise interference. This approach effectively enhances the quality and efficiency of creating mosaic ceramic exterior wall art images and promotes the development of mosaic ceramic exterior wall public art creation.

Autonomous Underwater Vehicle Navigation Enhancement by Optimized Side-Scan Sonar Registration and Improved Post-Processing Model Based on Factor Graph Optimization

Autonomous Underwater Vehicles (AUVs) equipped with Side-Scan Sonar (SSS) play a critical role in seabed mapping, where precise navigation data are essential for mosaicking sonar images to delineate the seafloor’s topography and feature locations. However, the accuracy of AUV navigation, based on Strapdown Inertial Navigation System (SINS)/Doppler Velocity Log (DVL) systems, tends to degrade over long-term mapping, which compromises the quality of sonar image mosaics. This study addresses the challenge by introducing a post-processing navigation method for AUV SSS surveys, utilizing Factor Graph Optimization (FGO). Specifically, the method utilizes an improved Fourier-based image registration algorithm to generate more robust relative position measurements. Then, through the integration of these measurements with data from SINS, DVL, and surface Global Navigation Satellite System (GNSS) within the FGO framework, the approach notably enhances the accuracy of the complete trajectory for AUV missions. Finally, the proposed method has been validated through both the simulation and AUV marine experiments.

The JWST UNCOVER Treasury Survey: Ultradeep NIRSpec and NIRCam Observations before the Epoch of Reionization

In this paper we describe the survey design for the Ultradeep NIRSpec and NIRCam Observations before the Epoch of Reionization (UNCOVER) Cycle 1 JWST Treasury program, which executed its early imaging component in 2022 November. The UNCOVER survey includes ultradeep (∼29–30AB) imaging of ∼45 arcmin2 on and around the well-studied A2744 galaxy cluster at z = 0.308 and will follow up ∼500 galaxies with extremely deep low-resolution spectroscopy with the NIRSpec/PRISM during the summer of 2023, with repeat visits in summer 2024. We describe the science goals, survey design, target selection, and planned data releases. We also present and characterize the depths of the first NIRCam imaging mosaic, highlighting previously unparalleled resolved and ultradeep 2–4 μm imaging of known objects in the field. The UNCOVER primary NIRCam mosaic spans 28.8 arcmin2 in seven filters (F115W, F150W, F200W, F277W, F356W, F410M, and F444W) and 16.8 arcmin2 in our NIRISS parallel (F115W, F150W, F200W, F356W, and F444W). To maximize early community use of the Treasury data set, we publicly release the full reduced mosaics of public JWST imaging including 45 arcmin2 NIRCam and 17 arcmin2 NIRISS mosaics on and around the A2744 cluster, including the Hubble Frontier Field primary and parallel footprints.

Candidate Distant Trans-Neptunian Objects Detected by the New Horizons Subaru TNO Survey

We report the detection of 239 trans-Neptunian objects discovered through the ongoing New Horizons survey for distant minor bodies being performed with the Hyper Suprime-Cam mosaic imager on the Subaru Telescope. These objects were discovered in images acquired with either the r2 or the recently commissioned EB-gri filter using shift and stack routines. Due to the extremely high stellar density of the search region downstream of the spacecraft, new machine learning techniques had to be developed to manage the extremely high false-positive rate of bogus candidates produced from the shift and stack routines. We report discoveries as faint as r2 ∼ 26.5. We highlight an overabundance of objects found at heliocentric distances R ≳ 70 au compared to expectations from modeling of the known outer solar system. If confirmed, these objects betray the presence of a heretofore-unrecognized abundance of distant objects that can help explain a number of other observations that otherwise remain at odds with the known Kuiper Belt, including detections of serendipitous stellar occultations, and recent results from the Student Dust Counter on board the New Horizons spacecraft.

A UAV Thermal Imaging Format Conversion System and Its Application in Mosaic Surface Microthermal Environment Analysis.

UAV thermal infrared remote sensing technology, with its high flexibility and high temporal and spatial resolution, is crucial for understanding surface microthermal environments. Despite DJI Drones' industry-leading position, the JPG format of their thermal images limits direct image stitching and further analysis, hindering their broad application. To address this, a format conversion system, ThermoSwitcher, was developed for DJI thermal JPG images, and this system was applied to surface microthermal environment analysis, taking two regions with various local zones in Nanjing as the research area. The results showed that ThermoSwitcher can quickly and losslessly convert thermal JPG images to the Geotiff format, which is further convenient for producing image mosaics and for local temperature extraction. The results also indicated significant heterogeneity in the study area's temperature distribution, with high temperatures concentrated on sunlit artificial surfaces, and low temperatures corresponding to building shadows, dense vegetation, and water areas. The temperature distribution and change rates in different local zones were significantly influenced by surface cover type, material thermal properties, vegetation coverage, and building layout. Higher temperature change rates were observed in high-rise building and subway station areas, while lower rates were noted in water and vegetation-covered areas. Additionally, comparing the temperature distribution before and after image stitching revealed that the stitching process affected the temperature uniformity to some extent. The described format conversion system significantly enhances preprocessing efficiency, promoting advancements in drone remote sensing and refined surface microthermal environment research.

The Sacred Scripture and the Symbolic Representations in the Early Christian Figurative Mosaics from the Balkans

It is a well-known fact that the figurative images in the Early Christian art are generally in conformity with the basic Sacraments, specific texts in the Old and the New Testament and the liturgy and rituals, which were performed in the churches. In the recent 40 years many new publications have been devoted to the pavement mosaics from the Balkans but they deal mainly with limited number of monuments from a separate contemporary state. As in Late Antiquity the borders between the provinces and both empires (Western and Eastern) were quite different from the contemporary ones, therefore the picture shown when tracing this aspect of research is not adequate and not complete if the we do not concern the ancient boundaries of the provinces, and do not consider the Balkans as one artistic area, but with many different traditions and influences. For this purpose, the mosaics not only from the well-known artistic centres of Greece have been gathered together, but also from Albania, Bulgaria, Macedonia and the European parts of Turkey. This provides new opportunities for a multifaceted study of the topic of the Early Byzantine liturgical practice from a formal, symbolic and theological point of view and emphasizes the importance of the figurative mosaic images and the inscriptions associated with them, which directly or symbolically reflects the Holy Scripture as well as it reveals the mysterious nature and the specific features of the rituals of the Early Christianity.

Binary craters on Ceres and Vesta and implications for binary asteroids

Context. Airless planetary objects have their surfaces covered by craters, and these can be used to study the characteristics of asteroid populations. Planetary surfaces present binary craters that are associated with the synchronous impact of binary asteroids. Aims. We identify binary craters on asteroids (1) Ceres and (4) Vesta, and aim to characterize the properties (size ratio and orbital plane) of the binary asteroids that might have formed them. Methods. We used global crater databases developed in previous studies and mosaics of images from the NASA DAWN mission high-altitude and low-altitude mapping orbits. We established selection criteria to identify craters that were most likely a product of the impact of a binary asteroid. We performed numerical simulations to predict the orientation of the binary craters assuming the population of impactors has mutual orbits coplanar with heliocentric orbits, as the current census of binary asteroids suggests. We compared our simulations with our survey of binary craters on Ceres and Vesta through a Kolmogorov-Smirnov test. Results. We find geomorphological evidence of 39 and 18 synchronous impacts on the surfaces of Ceres and Vesta, respectively. The associated binary asteroids are widely separated and similar in diameter. The distributions of the orientation of these binary craters on both bodies are statistically different from numerical impact simulations that assume binary asteroids with coplanar mutual and heliocentric orbits. Conclusions. Although the identification of binary craters on both bodies and the sample size are limited, these findings are consistent with a population of well-separated and similarly sized binary asteroids with nonzero obliquity that remains to be observed, in agreement with the population of binary craters identified on Mars.

Deep learning-assisted multispectral imaging for early screening of skin diseases

IntroductionMelanocytic nevi (MN), warts, seborrheic keratoses (SK), and psoriasis are four common types of skin surface lesions that typically require dermatoscopic examination for definitive diagnosis in clinical dermatology settings. This process is labor-intensive and resource-consuming. Traditional methods for diagnosing skin lesions rely heavily on the subjective judgment of dermatologists, leading to issues in diagnostic accuracy and prolonged detection times. ObjectivesThis study aims to introduce a multispectral imaging (MSI)-based method for the early screening and detection of skin surface lesions. By capturing image data at multiple wavelengths, MSI can detect subtle spectral variations in tissues, significantly enhancing the differentiation of various skin conditions. MethodsThe proposed method utilizes a pixel-level mosaic imaging spectrometer to capture multispectral images of lesions, followed by reflectance calibration and standardization. Regions of interest were manually extracted, and the spectral data were subsequently exported for analysis. An improved one-dimensional convolutional neural network is then employed to train and classify the data. ResultsThe new method achieves an accuracy of 96.82 % on the test set, demonstrating its efficacy. ConclusionThis multispectral imaging approach provides a non-contact and non-invasive method for early screening, effectively addressing the subjective identification of lesions by dermatologists and the prolonged detection times associated with conventional methods. It offers enhanced diagnostic accuracy for a variety of skin lesions, suggesting new avenues for dermatological diagnostics.

Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI+ era

AbstractFuture‐oriented Science & Technology (S&T) Strategies trigger the innovative developments of advanced materials, providing an envision to the significant progress of leading‐/cutting‐edge science, engineering, and technologies for the next few decades. Motivated by Made in China 2025 and New Material Power Strategy by 2035, several key viewpoints about automated research workflows for accelerated discovery and smart manufacturing of advanced materials in terms of AI for Science and main respective of big data, database, standards, and ecosystems are discussed. Referring to classical toolkits at various spatial and temporal scales, AI‐based toolkits and AI‐enabled computations for material design are compared, highlighting the dominant role of the AI agent paradigm. Our recent developed ProME platform together with its functions is introduced briefly. A case study of AI agent assistant welding is presented, which is consisted of the large language model, auto‐coding via AI agent, image processing, image mosaic, and machine learning for welding defect detection. Finally, more duties are called to educate the next generation workforce with creative minds and skills. It is believed that the transformation of knowledge‐enabled data‐driven integrated computational material engineering era to AI+ era promotes the transformation of smart design and manufacturing paradigm from “designing the materials” to “designing with materials.”

A Novel High-Fidelity Simulation for Finishing Operations: Hybrid Image Mosaic and Wavelet Decomposition.

In finishing simulations, achieving accurate results can be challenging due to the minimal amount of material removal and the limited measurement range of surface micro-topography instruments. To overcome these limitations, a novel high-fidelity modeling method combining image mosaic and wavelet decomposition technologies is proposed in this paper. We achieve the stitching of narrow field and high pixel micro morphology images through four steps: image feature extraction, overlapped feature matching, feature fusion, and stitching effect evaluation. On this basis, the wavelet decomposition method is employed to separate detection signals based on their respective frequencies, allowing the establishment of a datum plane and a roughness surface. The point cloud model undergoes a transformation into a continuous geometric model via the Poisson reconstruction algorithm. In the case study, four sample images of an aluminum alloy sheet after barrel finishing were collected using the ZeGage Plus optical profiler. Each image has an actual size of 834.37 μm × 834.37 μm. Subsequently, a comparison was carried out between the physical and simulation experiments. The results clearly indicate that the proposed method has the potential to enhance the accuracy of the finishing simulation by over 30%. The error between the resulting model and the actual surface of the part can be controlled within 1 μm.

Towards a Novel Generative Adversarial Network-Based Framework for Remote Sensing Image Demosaicking

During satellite remote sensing imaging, the use of Bayer mode sensors holds significant importance in saving airborne computing resources and reducing the burden of satellite transmission systems. The demosaicing techniques play a key role in this process. The integration of Generative Adversarial Networks (GANs) has garnered significant interest in the realm of image demosaicking, owing to their ability to generate intricate details. However, when demosaicing mosaic images in remote sensing techniques, GANs, although capable of generating rich details, often introduce unpleasant artifacts while generating content. To address this challenge and differentiate between undesirable artifacts and realistic details, we have devised a novel framework based on a Progressive Discrimination Strategy within a Generative Adversarial Network architecture for image demosaicking. Our approach incorporates an artifact-weighted Location Map refinement technique to guide the optimization process towards generating authentic details in a stable and precise manner. Furthermore, our framework integrates a global attention mechanism to boost the interaction of spatial-channel information across different dimensions, thereby enhancing the performance of the generator network. Moreover, we conduct a comparative analysis of various prevalent attention mechanisms in the context of remote sensing image demosaicking. The experimental findings unequivocally demonstrate that our proposed methodology not only achieves superior reconstruction accuracy on the dataset but also enhances the perceptual quality of the generated images. By effectively mitigating artifacts and emphasizing the generation of true details, our approach represents a significant advancement in the field of remote sensing image demosaicking, promising enhanced visual fidelity and realism in reconstructed images.

From research to production: radiometric block adjustment to automate and improve tonal adjustment of orthomosaics created from airborne images

Abstract. Production of orthophotos and orthomosaics from airborne imaging has been standard procedure of National mapping agencies for decades. Various aspects affect to the colour, or tones of the images: time of the day and year, atmosphere, illumination conditions, view and illumination angle, BRDF-effects (Bi-directional reflectance distribution function), object, sensor, and whole imaging system. Quantitative and automated solution for creating evenly coloured image mosaics is to use method based on radiometric block adjustment, that has similarities to more well-known geometric block adjustment. We have applied radiometric block adjustment method called RadBA, originally developed for drone image blocks collected with hyperspectral sensor, to image block collected with large-format photogrammetric camera. Goals of our work are: 1) to speed up orthophoto deliveries to Finish Food Authority used for EU farming subsidies monitoring, 2) improve the quality of images delivered to Finnish Forest Centre used for forest inventory, and 3) to automate, fasten and improve the current colour balancing process of orthophotos at National Land Survey of Finland. RadBA-based tonal processing with 4-parameter BRDF-correction was able to clearly improve the tonal quality of the image mosaic collected during three different dates. We still need to automate various steps of the RadBA-workflow and improve final steps in converting 16-bits per band mosaics to visually good looking 8-bits per band mosaics. Our long-term goal is to create tonally high quality, seamless orthomosaic of whole Finland.

Triangulated Irregular Network based Seamline Determination for Fast Image Stitching of Multiple UAV Images

Abstract. To maintain the efficiency of UAV (unmanned aerial vehicle) remote sensing, rapid image stitching is essential to make multiple UAV images into a seamless mosaic image. Relief displacement introduces variations in object appearance for each image, causing mismatch errors at mosaic seamlines. Traditional approaches involve orthorectifying images using DSMs (digital surface models). While these approaches allow for accurate image stitching, they do not cope with the advantages of UAVs due to their time consumption. In contrast, fast image stitching techniques that do not use orthorectification are well suited for UAV image processing. Related researches have attempted to optimize seamlines to eliminate the errors caused by relief displacement without the use of DSMs. We propose to utilize a TIN (triangular irregular network) of tiepoints to effectively eliminate errors caused by relief displacement while maintaining the fast speed of image stitching. In this study, a TIN is constructed based image tiepoints whose ground coordinates have been obtained through bundle adjustment. The edges of the TIN are used to generate seamlines for image stitching, and the facets of the TIN are used to select minimal images for image stitching and to optimize seamlines. Image stitching results of our proposed method had small error of 1–2 pixels and the processing time of less than 10 minutes for 97 UAV images. This study showed that the proposed method could stitch multiple images while maintaining stable quality using only geometric clues of a TIN of tiepoints.

A Multi-Shot Approach for Spatial Resolution Improvement of Multispectral Images from an MSFA Sensor.

Multispectral imaging technology has advanced significantly in recent years, allowing single-sensor cameras with multispectral filter arrays to be used in new scene acquisition applications. Our camera, developed as part of the European CAVIAR project, uses an eight-band MSFA to produce mosaic images that can be decomposed into eight sparse images. These sparse images contain only pixels with similar spectral properties and null pixels. A demosaicing process is then applied to obtain fully defined images. However, this process faces several challenges in rendering fine details, abrupt transitions, and textured regions due to the large number of null pixels in the sparse images. Therefore, we propose a sparse image composition method to overcome these challenges by reducing the number of null pixels in the sparse images. To achieve this, we increase the number of snapshots by simultaneously introducing a spatial displacement of the sensor by one to three pixels on the horizontal and/or vertical axes. The set of snapshots acquired provides a multitude of mosaics representing the same scene with a redistribution of pixels. The sparse images from the different mosaics are added together to get new composite sparse images in which the number of null pixels is reduced. A bilinear demosaicing approach is applied to the composite sparse images to obtain fully defined images. Experimental results on images projected onto the response of our MSFA filter show that our composition method significantly improves image spatial resolution and minimizes reconstruction errors while preserving spectral fidelity.