Multispectral Imaging Applications Research Articles

Application of Multispectral Imaging Combined with Machine Learning for Rapid and Non-Destructive Detection of Zearalenone (Zen) in Maize

Application of Multispectral Imaging Combined with Machine Learning for Rapid and Non-Destructive Detection of Zearalenone (Zen) in Maize

An ultra-thin multiband terahertz metamaterial absorber and sensing applications

We propose an ultra-thin multiband terahertz metamaterial absorber, whose thickness is only 3.8 μm. Simulation results show that we can get four narrow absorption peaks with near-perfect absorption in the 4.5 THz-6.0 THz frequency range. The resonance absorption mechanism is interpreted by the electromagnetic field energy distributions at resonance frequency. Moreover, we also analyze the sensing performances of the absorber in the refractive index and the thickness of the analyte. The refractive index and thickness sensitivities of the sensor are 0.471 THz/RIU, 0.4 THz/μm and the FOMs are 8.887RIU−1, 8.163 μm−1,respectively. The absorber has potential applications in photodetector, multi-spectral imaging and biosensors.

Application of Multispectral Imaging and Portable Spectroscopic Instruments to the Analysis of an Ancient Persian Illuminated Manuscript.

Illuminated manuscripts are, in general, the final products of a wise and complex interaction of different competencies. In particular, each manuscript reflects uses and techniques rooted in the historical and geographical traditions of the area of realization. Defining the characteristics and the materials in these valuable artefacts is an essential element to reconstruct their history and allow a more precise collocation and a possible comparison with other works in similar periods and areas. Non-invasive methods, mainly using portable instruments, offer undoubtedly good support in these studies. Recent analyses of an ancient Persian illuminated manuscript, combining multispectral imaging and spectroscopic measurements made with portable instruments (XRF, FORS, micro-Raman, IR-ATR) on selected points, provided new data for an improved understanding of this rare book. This study details the possibilities offered by combining these non-invasive methods for an in-depth understanding of the techniques and practices behind the realization of Middle Eastern illuminated manuscripts and provided new perspectives for multidisciplinary approaches to research in this field.

Tailoring Single Plasmonic Resonance for RGB‐NIR Imaging Using Nanoimprinted Complementary Plasmonic Structures of Nanohole and Nanodisk Arrays

AbstractPlasmonic nanohole arrays (NHA) can serve as an efficient alternative for ultrathin color filters due to their high color tunability, robust stability, and simple nanofabrication. However, the periodic nanostructures inherently exhibit multiple resonances in the visible and near‐infrared ranges. Here large‐area and single‐resonance plasmonic spectral filter for RGB‐NIR imaging using nanoimprinted complementary plasmonic structures (CPS) is reported. The CPS comprise self‐aligned metallic nanohole and nanodisk arrays in regular (rCPS) or inverse (iCPS) configuration, where unfavorable resonances of nanohole arrays are substantially attenuated by an extinction resonance of nanodisk arrays. The experimental results show the CPS exhibit single peaks in 437 (blue), 515 (green), 644 (red), and 912 nm (NIR), respectively. The color purity is highly increased by up to six times and thus the color reproduction range is expanded up to four times, compared to NHA. The CPS spectral filters clearly demonstrate RGB‐NIR tetrachromatic imaging, resulting from the true color imaging and recognition of distinctive NIR features. This unique configuration can serve as large‐scale plasmonic spectral filters that can drive multispectral or hyperspectral imaging applications.

Multi-aperture system approach for snapshot multispectral imaging applications.

We present an ultra-compact system approach for snapshot, multispectral imaging. It is based on a slanted linear variable spectral filter mounted in close proximity to the entrance pupil of a micro-optical, multi-aperture imaging system. A compact demonstration setup with a size of only 60 × 60 × 28 mm3 is developed, which enables the acquisition of 66 spectral channels in a single shot and offers a linear spectral sampling of approximately six nanometers over an extended wavelength range of 450-850 nm. The spatial sampling of each channel covers up to 400 × 400 pixels. First, the concept, the optical design and the fabrication are detailed. After the optical performance characterization, a comprehensive calibration strategy is developed and applied. An experimental demonstration is performed by acquiring the spatial and the spectral information of an imaged test scene.

Problems and Prospects of Application of Multispectral Imaging in the Manuscript Studies

By the beginning of the 21st century, digital multispectral and hyperspectral visualization has become one of the key components of the systematic study of historical manuscripts. Over the past twenty years, a significant amount of research with the application if this method has been carried out; therefore, the authors of this article have considered it necessary to reflect on the current situation in the field of application of multispectral visualization methods and to provide an overview of the most representative projects. It has been established that among the permanently operating foreign scientific institutions which use multispectral imaging methods, the most productive are the Center for the Study of Manuscript Cultures of the University of Hamburg, Centre of Image and Material Analysis in Cultural Heritage (Austria), and the Research Department of the Bodleian Library (Oxford). Among the temporary projects, studies related to the complex examination of palimpsests as well as to the evaluation of the state of the text carrier have been singled out since they had a significant impact on the development of multispectral visualization at the methodological and technical levels. The review provides characteristics of the equipment used for multispectral imaging; discusses the relationship between methods and specific research tasks. It is stated that nowadays multispectral visualization has become a routine technique in solving utilitarian tasks. The following directions have been distinguished as the most promising for the development of the research potential of this method: 1) analysis of the spectral behavior of the substance in determining the composition of the dye; 2) analysis of the spectral behavior of the text made with different inks, including the research related to the study of writing skills; 3) control of the state and dynamics of processes of the carrier.

Field identification of weed species and glyphosate-resistant weeds using high resolution imagery in early growing season

Accurate weed mapping in early growing season is an essential step in the site-specific weed management system. This study focuses on validating the potential application of high resolution multispectral and thermal UAS images in classification of weed species and glyphosate-resistant weeds at early phenological stages. A field experiment was conducted to evaluate supervised classification methods to identify three-weed species including waterhemp (Amaranthus rudis), kochia (Kochia scoparia), and ragweed (Ambrosia artemisiifolia L.). The accuracy of six classification algorithms namely Parallelepiped, Mahalanobis Distance, Maximum Likelihood, Spectral Angle Mapper, Support Vector Machine and Decision Tree implemented at pixel and object-based levels in weed species classification were evaluated. Thermal infrared imagery was also used to assess the canopy temperature variance within the weed species to identify the glyphosate-resistance status in detected weeds. The object-based algorithms developed with mosaicked imagery effectively classified weed species with the overall accuracy and Kappa coefficient values greater than 86% and 0.77, respectively. The lowest accuracy and Kappa coefficient (67% and 0.58) were observed for pixel-based Mahalanobis Distance algorithm. The canopy temperature-based classification of susceptible and resistant weeds resulted in the discrimination accuracies of 88%, 93% and 92% in glyphosate-resistant kochia, waterhemp and ragweed, respectively.

Application of Multispectral Imaging in the Human Tympanic Membrane.

Multispectral imaging has recently shown good performance in determining information about physiology, morphology, and composition of tissue. In the endoscopy field, many researches have shown the ability to apply multispectral or narrow-band images in surveying vascular structure based on the interaction of light wavelength with tissue composition. However, there has been no mention to assess the contrast between other components in the middle ear such as the tympanic membrane, malleus, and the surrounding area. Using CT, OCT, or ODT can clearly describe the tympanic membrane structure; nevertheless, these approaches are expensive, more complex, and time-consuming and are not suitable for most common middle ear diagnoses. Here, we show the potential of using the multispectral imaging technique to enhance the contrast of the tympanic membrane compared to the surrounding tissue. The optical absorption and scattering of biological tissues constituents are not the same at different wavelengths. In this pilot study, multiwavelength images of the tympanic membrane were captured by using the otoscope with LED light source at three distinct spectral regions: 450 nm, 530 nm, and 630 nm. Subsequently, analyses of the intensity images as well as the histogram of these images point out that the 630 nm illumination image features an evident contrast in the intensity of the tympanic membrane and malleus compared to the surrounding area. Analysis of such images could facilitate the boundary determination and segmentation of the tympanic membrane (TM) with high precision.

Using Multispectral Imaging for Detecting Seed-Borne Fungi in Cowpea

Recent advances in multispectral imaging-based technology have provided useful information on seed health in order to optimize the quality control process. In this study, we verified the efficiency of multispectral imaging (MSI) combined with statistical models to assess the cowpea seed health and differentiate seeds carrying different fungal species. Seeds were artificially inoculated with Fusarium pallidoroseum, Rhizoctonia solani and Aspergillus sp. Multispectral images were acquired at 19 wavelengths (365 to 970 nm) from inoculated seeds and freeze-killed ‘incubated’ seeds. Statistical models based on linear discriminant analysis (LDA) were developed using reflectance, color and texture features of the seed images. Results demonstrated that the LDA-based models were efficient in detecting and identifying different species of fungi in cowpea seeds. The model showed above 92% accuracy before incubation and 99% after incubation, indicating that the MSI technique in combination with statistical models can be a useful tool for evaluating the health status of cowpea seeds. Our findings can be a guide for the development of in-depth studies with more cultivars and fungal species, isolated and in association, for the successful application of MSI in the routine health inspection of cowpea seeds and other important legumes.

Computational Ghost Imaging with Multiplexed Time-Varying Signals

This study proposes two methods of optical watermarking based on multiplexed time-varying signals for computational ghost imaging using the Hadamard matrices. The proposed methods can realize image fusion and dual optical encryption. The time-varying signal is encoded into a specific Hadamard coefficient in advance and hidden in the light source of the transmitting end as a multiplicative factor or loaded at the receiving end as an additive factor. Theory and experiments confirm the feasibility of this scheme. Moreover, the scheme is highly scalable and has potential applications in multispectral single-pixel imaging.

Detection of heterogeneity in multi-spectral transmission image based on spatial pyramid matching model and deep learning

The absorption and scattering effects of light source during the transmission of biological tissues make it difficult to identify heterogeneity in multi-spectral images. This paper firstly proposes a combination method of modulation-demodulation-frame accumulation technique (MDFAT), spatial pyramid matching (SPM) model and deep learning to realize heterogeneous detection in multi-spectral images. Firstly, the acquisition experiment of phantom image is designed. Then, the high-quality multi-spectral images are obtained by the MDFAT and SPM model. Finally, the pseudo-color maps of high-quality multi-spectral images fusion are served as the input of Faster-RCNN and Single Shot Multi-Box Detector (SSD) network models to realize heterogeneous detection. The results show that Faster-RCNN and SSD both have good detection results. Among them, Faster-RCNN model has the best detection effect on the images containing three types of heterogeneity, and the mean average precision (mAP) reaches 93.91%. SSD model has the most ideal detection effect for the images containing two and five types of heterogeneity, with mAP reaching 94.16% and 94.78% respectively. In conclusion, this paper has verified the feasibility of detecting heterogeneities in multi-spectral images through deep learning network (Faster-RCNN and SSD), which will promote the clinical application of multi-spectral transmission imaging in early screening of breast tumors.

High-resolution digital mapping of soil organic carbon and soil total nitrogen using DEM derivatives, Sentinel-1 and Sentinel-2 data based on machine learning algorithms

Soil organic carbon (SOC) and soil total nitrogen (STN) are important indicators of soil health and play a key role in the global carbon and nitrogen cycles. High-resolution radar Sentinel-1 and multispectral Sentinel-2 images have the potential to investigate soil spatial distribution information over a large area, although Sentinel-1 and Sentinel-2 data have rarely been combined to map either SOC or STN content. In this study, we applied machine learning techniques to map both SOC and STN content in the southern part of Central Europe using digital elevation model (DEM) derivatives, multi-temporal Sentinel-1 and Sentinel-2 data, and evaluated the potential of different remote sensing sensors (Sentinel-1 and Sentinel-2) to predict SOC and STN content. Four machine-learners including random forest (RF), boosted regression trees (BRT), support vector machine (SVM) and Bagged CART were used to construct predictive models of SOC and STN contents based on 179 soil samples and different combinations of environmental covariates. The performance of these models was evaluated based on a 10-fold cross-validation method by three statistical indicators. Overall, the BRT model performed better than RF, SVM and Bagged CART, and these models yielded similar spatial distribution patterns of SOC and STN. Our results showed that multi-source sensor methods provided more accurate predictions of SOC and STN contents than individual sensors. The application of radar Sentinel-1 and multispectral Sentinel-2 images proved useful for predicting SOC and STN. A combination of Sentinel-1/2-derived predictors and DEM derivatives yielded the highest prediction accuracy. The prediction accuracy changed with and without the Sentinel-1/2-derived predictors, with the R2 for estimating both SOC and STN content using the BRT model increasing by 12.8% and 18.8%, respectively. Topographic variables were the main explanatory variables for SOC and STN predictions, where elevation was assigned as the variable with the most importance by the models. The results of this study illustrate the potential of free high-resolution radar Sentinel-1 and multispectral Sentinel-2 data as input when developing SOC and STN prediction models.

Multi-spectral interference imaging using laser-induced plasma light source

Interference imaging techniques are widely used for studying surface and internal structure of various objects. By varying the operating wavelength of the interference system, one can also obtain the information about the spectral properties of the inspected specimen. For multi-spectral interference imaging applications, wide-band high power light sources are necessary. Most of the existing sources suffer from speckle noise, low brightness or high price. In this paper, we demonstrate the applicability of a laser-induced plasma light source for interference imaging and quantitative phase measurements. Narrow-band spectral filtration of its illumination within a wavelength range 240-2600 nm allows to design cost-effective schemes for a variety of metrological applications including digital holography and spectral-domain optical coherence tomography.

Direct Observation of the Linear Dichroism Transition in Two-Dimensional Palladium Diselenide.

The linear dichroism (LD) transition within anisotropic photonic materials displays promising prospects for applications in polarization-wavelength-selective detectors, optical switching, and optical communication. In conventional two-dimensional (2D) anisotropic materials, the LD is predominantly uniaxial over a broad spectrum of wavelengths and arises principally from the reduced symmetry of the materials. However, the LD transition behavior in crystalline 2D materials remains elusive. Here, we demonstrate the observation of a unique LD conversion phenomenon at a wavelength of 472 nm in palladium diselenide (PdSe2) using polarization-resolved absorption spectroscopy. This material exhibits prominent anisotropic responses and a high absorption ratio of αy/αx ≈ 1.11 at 364 nm, 1.15 at 532 nm, and 0.84 at 633 nm. We propose that this abnormal LD conversion behavior originates from the forceful localization rules at different parallel energy bands that exist within this material. Furthermore, the robust periodicity of Ag and B1g modes in polarization-resolved Raman spectroscopy is in good agreement with the theoretical structure symmetry analysis. This indicates the strong intrinsic LD effect in the anisotropic nature of PdSe2, which offers a macrolevel determination of crystal orientations. Such unique LD conversion features, in combination with strong LD effects, enable the air-stable PdSe2 to be a potential candidate for technological innovations in multispectral imaging, sensing, and polarization-sensitive and wavelength-controllable photoelectronic applications.

Grayscale-to-Color: Scalable Fabrication of Custom Multispectral Filter Arrays

Snapshot multispectral image (MSI) sensors have been proposed as a key enabler for a plethora of multispectral imaging applications, from diagnostic medical imaging to remote sensing. With each application requiring a different set, and number, of spectral bands, the absence of a scalable, cost-effective manufacturing solution for custom multispectral filter arrays (MSFAs) has prevented widespread MSI adoption. Despite recent nanophotonic-based efforts, such as plasmonic or high-index metasurface arrays, large-area MSFA manufacturing still consists of many-layer dielectric (Fabry–Perot) stacks, requiring separate complex lithography steps for each spectral band and multiple material compositions for each. It is an expensive, cumbersome, and inflexible undertaking, but yields optimal optical performance. Here, we demonstrate a manufacturing process that enables cost-effective wafer-level fabrication of custom MSFAs in a single lithographic step, maintaining high efficiencies (∼75%) and narrow line widths (∼25 nm) across the visible to near-infrared. By merging grayscale (analog) lithography with metal–insulator–metal (MIM) Fabry–Perot cavities, whereby exposure dose controls cavity thickness, we demonstrate simplified fabrication of MSFAs up to N-wavelength bands. The concept is first proven using low-volume electron beam lithography, followed by the demonstration of large-volume UV mask-based photolithography with MSFAs produced at the wafer level. Our framework provides an attractive alternative to conventional MSFA manufacture and metasurface-based spectral filters by reducing both fabrication complexity and cost of these intricate optical devices, while increasing customizability.

Large‐Area and Low‐Cost Nanoslit‐Based Flexible Metasurfaces for Multispectral Electromagnetic Wave Manipulation

AbstractManipulating multispectral electromagnetic (EM) waves has drawn great attention due to its potential applications in EM compatibility, radiative cooling, and multispectral imaging. Metasurfaces are intensively investigated to control EM waves and achieve versatile functions. However, the design of multispectral manipulation and the fabrication of multiscale metasurfaces remain a great challenge. Here, a multiscale flexible metasurface with nanometer‐sized characteristic dimensions and a square centimeter sized area is designed and fabricated for the simultaneous manipulation of infrared and terahertz waves. A simple yet powerful analytic method derived from catenary field theory is proposed to guide the design. A metasurface consisting of 2D nanoslit array is fabricated onto a flexible polyimide substrate by combining shadow mask fabrication with surface plasmon lithography to achieve nanoscale, large‐area, and repeatable fabrication. The experimental results show that the proposed metasurface possesses high reflectance exceeding 95% within the 8–12 µm wavelength range, indicating low thermal emissivity. Additionally, the metasurface exhibits low reflection in the THz regime and is capable of implementing integrated functions in conjunction with THz devices. Furthermore, the significant advantage of flexibility affords the metasurface excellent compatibility with irregular surfaces. This work may provide important guidance for the design and fabrication of large‐scale multispectral metasurfaces.

Improving heterogeneous classification accuracy based on the MDFAT and the combination feature information of multi-spectral transmission images

Multi-spectral transmission image provides a possibility for the early detection of breast cancer. However, in the process of obtaining multi-spectral transmission images, it is difficult to identify the heterogeneity in images due to the image blur caused by the scattering effect of the light source in the biological tissue and the weak transmission signal. This paper proposes a combination method based on the modulation-demodulation-frame accumulation technique (MDFAT) and the combination feature information of multi-spectral transmission images to improve the accuracy of heterogeneous classification. Firstly, the acquisition experiment of phantom multi-spectral transmission images is designed. Then, the high-resolution image is obtained by the MDFAT, and the 14-dimensional feature information of the heterogeneous region is extracted from the images before and after processing. The combination feature information of wavelengths is arranged in order of blue light, green light, near-infrared light and red light. Finally, Random Forest (RF) is used to classify the heterogeneities in the transmission image. The results show that the quality of multi-spectral transmission image is significantly improved after the processing of MDFAT, and the gray level of image is also obviously increased, so that more abundant feature information of heterogeneous region can be obtained. And the overall classification accuracy of RF model established after image preprocessing has been significantly improved. Among them, the 3-wavelength combination model has the best classification effect and the best robustness, followed by the 4-wavelength combination model. The classification accuracy of single-wavelength model is low, but it is also greatly improved compared with that before image preprocessing. In conclusion, this paper improves the image quality by the MDFAT, and the classification accuracy of heterogeneities is significantly improved by combining the feature information of multi-spectral transmission images, which promotes the potential application of multi-spectral transmission imaging in early breast cancer detection.

Linear Dichroism Conversion in Quasi-1D Perovskite Chalcogenide.

Anisotropic photonic materials with linear dichroism are crucial components in many sensing, imaging, and communication applications. Such materials play an important role as polarizers, filters, and waveplates in photonic devices and circuits. Conventional crystalline materials with optical anisotropy typically show unidirectional linear dichroism over a broad wavelength range. The linear dichroism conversion phenomenon has not been observed in crystalline materials. The investigation of the unique linear dichroism conversion phenomenon in quasi-1D hexagonal perovskite chalcogenide BaTiS3 is reported. This material shows a record level of optical anisotropy within the visible wavelength range. In contrast to conventional anisotropic optical materials, the linear dichroism polarity in BaTiS3 makes an orthogonal change at an optical wavelength corresponding to the photon energy of 1.78 eV. First-principles calculations reveal that this anomalous linear dichroism conversion behavior originates from the different selection rules of the parallel energy bands in the BaTiS3 material. Wavelength-dependent polarized Raman spectroscopy further confirms this phenomenon. Such a material, with linear dichroism conversion properties, could facilitate the sensing and control of the energy and polarization of light, and lead to novel photonic devices such as polarization-wavelength selective detectors and lasers for multispectral imaging, sensing, and optical communication applications.

Review of nanostructure color filters

Nanostructure color filters filter light spectrum via the structural engineering, unlike traditional dye filters that rely on the chemical compositions to absorb light. In light of the successful advance in micro/nanofabrication technology in the past decades, these structured color filters are particularly promising for future applications in ultrascaled color filtering and multispectral imaging. We will summarize the recent progress in nanostructure color filters based on plasmonics, nanowires, metamaterials, and quantum dots (QDs). Plasmonics filters rely on surface plasmon resonances to realize the spectrum selection. For nanowire color filters, the color filtering is achieved by light coupling into the leaky or waveguiding mode in nanowires. In metamaterial filters, the refractive index of artificial materials is manipulated to create a broad color palette. QDs color filters rely on bandgap engineering to create filtering effects by simply altering the size and composition of the QDs. Clearly, the above filtering technologies have their own pros and cons, which will be analyzed.

A High-Efficiency Multispectral Filter Based on Plasmonic Hybridization between Two Cascaded Ultrathin Nanogratings.

Overcoming the disadvantages of low transmission and broad peak bandwidth of previously reported plasmonic color filters, a high-efficiency multispectral plasmonic color filter is theoretically proposed with two cascaded ultrathin metallic nanogratings separated by two heterogeneous dielectric layers, and its optical properties are theoretically investigated using the finite-difference time-domain method. The transmission spectrum presents three near-unity peak bands accompanied with three near-null dip bands adjacent around them. Both transmission efficiencies of above 90% and ultranarrow peak bandwidth of 20 nm are achieved in the visible regime. The peak band positions can be flexibly tailored by varying the structural parameters. The filter selects the visible color with high signal noise ratio at the peak bands. The outstanding spectral properties of this filter indicate significant improvement for the high-accuracy color filtering and multispectral imaging applications. The simulated near-field electromagnetic distributions suggest that the excitation of the hybrid antisymmetric surface plasmon polariton (SPP) leaky mode and metal-insulator-metal waveguide modes are responsible for the peak transmission bands, while the formation of the hybrid SPP bound modes confined on the bottom nanograting makes the dip transmission bands, all of which are the consequence of the plasmonic hybridization between the two neighboring metallic nanogratings.