scholarly journals A High Optical Throughput Spectral Imaging Technique Using Broadband Filters

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4387
Author(s):  
Duo Wang ◽  
Zhe Chen ◽  
Xingxiang Zhang ◽  
Tianjiao Fu ◽  
Rui OuYang ◽  
...  
Keyword(s):  
Spatial Information ◽  
Least Squares Method ◽  
Imaging System ◽  
Spectral Imaging ◽  
Luminous Flux ◽  
Spectral Absorption ◽  
Spectral Image ◽  
Regularization Algorithm ◽  
New Approach ◽  
Multichannel Measurement

To address the miniaturization of the spectral imaging system required by a mounted platform and to overcome the low luminous flux caused by current spectroscopic technology, we propose a method for the multichannel measurement of spectra using a broadband filter in this work. The broadband filter is placed in front of a lens, and the spectral absorption characteristics of the broadband filter are used to achieve the modulation of the incident spectrum of the detection target and to establish a mathematical model for the detection of the target. The spectral and spatial information of the target can be obtained by acquiring data using a push-broom method and reconstructing the spectrum using the GCV-based Tikhonov regularization algorithm. In this work, we compare the accuracy of the reconstructed spectra using the least-squares method and the Tikhonov algorithm based on the L-curve. The effect of errors in the spectral modulation function on the accuracy of the reconstructed spectra is analyzed. We also analyze the effect of the number of overdetermined equations on the accuracy of the reconstructed spectra and consider the effect of detector noise on the spectral recovery. A comparison between the known data cubes and our simulation results shows that the spectral image quality based on broadband filter reduction is better, which validates the feasibility of the method. The proposed method of combining broadband filter-based spectroscopy with a panchromatic imaging process for measurement modulation rather than spectroscopic modulation provides a new approach to spectral imaging.

scholarly journals Compressive spectral image fusion via a single aperture high throughput imaging system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hoover Rueda-Chacon ◽  
Fernando Rojas ◽  
Henry Arguello
Keyword(s):  
Image Fusion ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Imaging System ◽  
Research Work ◽  
Visible Spectral Range ◽  
Computational Imaging ◽  
High Spectral Resolution ◽  
Spectral Image ◽  
The Rich

AbstractSpectral image fusion techniques combine the detailed spatial information of a multispectral (MS) image and the rich spectral information of a hyperspectral (HS) image into a high-spatial and high-spectral resolution image. Due to the data deluge entailed by such images, new imaging modalities have exploited their intrinsic correlations in such a way that, a computational algorithm can fuse them from few multiplexed linear projections. The latter has been coined compressive spectral image fusion. State-of-the-art research work have focused mainly on the algorithmic part, simulating instrumentation characteristics and assuming independently registered sensors to conduct compressed MS and HS imaging. In this manuscript, we report on the construction of a unified computational imaging framework that includes a proof-of-concept optical testbed to simultaneously acquire MS and HS compressed projections, and an alternating direction method of multipliers algorithm to reconstruct high-spatial and high-spectral resolution images from the fused compressed measurements. The testbed employs a digital micro-mirror device (DMD) to encode and split the input light towards two compressive imaging arms, which collect MS and HS measurements, respectively. This strategy entails full light throughput sensing since no light is thrown away by the coding process. Further, different resolutions can be dynamically tested by binning the DMD and sensors pixels. Real spectral responses and optical characteristics of the employed equipment are obtained through a per-pixel point spread function calibration approach to enable accurate compressed image fusion performance. The proposed framework is demonstrated through real experiments within the visible spectral range using as few as 5% of the data.

Spectral Imaging to Differentiate Contaminant Levels

2021 ◽  
Vol 2021 (16) ◽  
pp. 342-1-342-8
Author(s):  
Min Zhao ◽  
Qiyue Liang ◽  
Susana Diaz-Amaya ◽  
Amanda J. Deering ◽  
Lia Stanciu ◽  
...  
Keyword(s):  
Spatial Information ◽  
Imaging System ◽  
Spectral Response ◽  
Spectral Imaging ◽  
Principal Component ◽  
Test Accuracy ◽  
Classification Models ◽  
Forward Selection ◽  
Colorimetric Response ◽  
Contamination Levels

Mercury (Hg) and Arsenic (As) have been recognized as chemical threats to human health. Still, the detection of lower contamination levels using traditional image analysis remains challenging due to the small number of available data samples and the insufficient utilization of the spatial information contained in the sensor pad images. To overcome this challenge, we use the spectra data of the colorimetric response pads and propose two kinds of classification models for differentiating contaminant levels with high test accuracy. In the first model, we use the SMOTE method to solve the imbalanced data problem, then apply the sequential forward selection algorithm to select optimal wavelength features in combination with the k-NN classifier to discriminate five contaminant levels. The second technique comprises principal component analysis (PCA) used as a dimensionality reduction technique combined with the random forest (RF) classifier to classify five contaminant levels. Our proposed system is trained and evaluated on a limited dataset of 126 spectral responses of five contamination levels. Our algorithms can yield 77% and 87% average accuracy, respectively. We will present an overview of the base model, the pipelines and the comparison of our proposed two classification models, and the phone-based narrow-band spectral imaging system that can obtain the camera spectral response for accurate and precise heavy metals analyses with the aid of narrow bandpass filters in front of a cell phone’s camera lens.

Compact AOTF-based spectral imaging system for medical endoscopic analysis

2013 ◽  
Vol 2 (2) ◽  
Author(s):  
Alexander Machihin ◽  
Vitold Pozhar ◽  
Vladislav Batshev
Keyword(s):  
Spectral Analysis ◽  
Image Registration ◽  
Real Time ◽  
Imaging System ◽  
Spectral Imaging ◽  
Tunable Filters ◽  
Image Distortion ◽  
Spectral Features ◽  
Spectral Image ◽  
Reliable Detection

AbstractA prototype of a spectral imaging module is described which can be attached to conventional rigid and flexible medical endoscopes. It is based on acousto-optic tunable filters (AOTF) and provides fast spectral image registration at an arbitrary series of wavelengths. The main advantage of the device is the minimization of spatial and spectral image distortion by use of a specialized double AOTF monochromator. These properties ensure immediate and reliable detection of spectral features in any image pixel. Real-time spectral analysis, in addition to spectral visualization, provides the opportunity to make medical photoluminescence diagnostics more effective.

Dual-mode spectral imaging system employing a focus variable lens

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Erik Förster ◽  
Moritz Stürmer ◽  
Ulrike Wallrabe ◽  
Jan Korvink ◽  
Patrick Bohnert ◽  
...  
Keyword(s):  
Spatial Information ◽  
Imaging System ◽  
Spectral Imaging ◽  
Dual Mode ◽  
Wide Range ◽  
Extended Field ◽  
And Performance ◽  
High Flexibility ◽  
Spectrally Resolved ◽  
Variable Focus

AbstractThis paper presents a dual-mode spectral imaging system, which allows switching between pure lateral imaging and the spectrally resolved recording of spatial information. The optical system was equipped with tunable functionalities in order to achieve high flexibility, cover a wide range of object distances, and address extended field angles. A fluidic membrane lens was used for the variable focus, and the recording of the laterally extended scene was made possible by successively adjusting the different tilting angles to the different object positions. The capability and performance of the spectral imaging system were assessed using various test scenes, with different aimed field positions and changing object distances.

scholarly journals Analysis of Compound Stained Cervical Cell Images Using Multi-Spectral Imaging

2021 ◽  
Vol 11 (12) ◽  
pp. 5628
Author(s):  
Run Fang ◽  
Libo Zeng ◽  
Fan Yi
Keyword(s):  
Cervical Cancer ◽  
Mouse Liver ◽  
Imaging System ◽  
Color Image ◽  
Imaging Technique ◽  
Screening Method ◽  
Spectral Imaging ◽  
High Accuracy ◽  
Cervical Cell ◽  
Real World Applications

Multi-spectral imaging technique plays an important role in real-world applications such as medicine and medical detections. This paper proposes a cervical cancer cell screening method to simultaneously adopt TBS classification and DNA quantitative analysis for a single cell smear. Through using compound staining on a smear, the cytoplasm is stained by Papanicolauo and the nucleus is stained by Feulgen. The main evaluation parameter is the DNA content of the nucleus, not the subjective description of cell morphology, which is more objective than the TBS classification method and reduces the chances of missing a diagnosis due to subjective factors. Each nucleus has its own DI value and color image of the whole cell, which is convenient for doctors as it allows them to review and confirm the morphology of cells with a nucleus DI of over 2.5. Mouse liver smears and cervical cases are utilized as the measuring specimens to evaluate the performance of the microscope multi-spectral imaging system; illustrative results demonstrate that the proposed system qualifies, with high accuracy and reliability, and further presents wide application prospects in the early diagnosis of cervical cancer.

Effects of Single Wavelength Selection for Anisakid Roundworm Larvae Detection through Multispectral Imaging

2007 ◽  
Vol 70 (8) ◽  
pp. 1890-1895 ◽  
Author(s):  
SVEIN K. STORMO ◽  
AGNAR H. SIVERTSEN ◽  
KARSTEN HEIA ◽  
HEIDI NILSEN ◽  
EDEL ELVEVOLL
Keyword(s):  
Light Scattering ◽  
Multispectral Imaging ◽  
Spatial Information ◽  
Imaging Spectroscopy ◽  
Fish Muscle ◽  
Alternative Methods ◽  
Spectral Image ◽  
Nematode Parasites ◽  
Food Quality And Safety ◽  
Commercially Important

The occurrence of parasites in fillets of commercially important fish species affects both food quality and safety. Presently, the detection and removal of nematode parasites is done by inspection on a light table (candling) and manual trimming of the fillets. This operation is costly and time-consuming and is not effective for detecting and removing all the nematodes in the fillets. In the last decades, several alternative methods have been proposed, but these methods have failed to replace the candling method. A newly described method called imaging spectroscopy has produced promising results because the operator can record both spectral and spatial information from an object. In this work, we studied single-wavelength bands from a spectral image. Discrimination between nematodes and other objects in the fillets is dependent on the level of contrast. Quantification of the contrast in such images revealed that the level of contrast varied when different wavelengths were selected, and these variations are correlated with the absorption properties of the nematode. Visible light scatters greatly in fish muscle, generally complicating the detection of nematodes. In this study, light scattering was used in a way that reduces the background complexity in spectral images. When light scattering properties were used in a wavelength range different from the bulk of the nematode light absorption, spectral images with significantly higher contrast were produced.

scholarly journals Sparse Subspace Clustering in Hyperspectral Images using Incomplete Pixels

TecnoLógicas ◽  
2019 ◽  
Vol 22 (46) ◽  
pp. 1-14 ◽  
Author(s):  
Jorge Luis Bacca ◽  
Henry Arguello
Keyword(s):  
Spatial Information ◽  
Hyperspectral Image ◽  
Subspace Clustering ◽  
Unsupervised Classification ◽  
Hyperspectral Images ◽  
Image Clustering ◽  
Spectral Signature ◽  
Spectral Image ◽  
Sparse Subspace Clustering

Spectral image clustering is an unsupervised classification method which identifies distributions of pixels using spectral information without requiring a previous training stage. The sparse subspace clustering-based methods (SSC) assume that hyperspectral images lie in the union of multiple low-dimensional subspaces.  Using this, SSC groups spectral signatures in different subspaces, expressing each spectral signature as a sparse linear combination of all pixels, ensuring that the non-zero elements belong to the same class. Although these methods have shown good accuracy for unsupervised classification of hyperspectral images, the computational complexity becomes intractable as the number of pixels increases, i.e. when the spatial dimension of the image is large. For this reason, this paper proposes to reduce the number of pixels to be classified in the hyperspectral image, and later, the clustering results for the missing pixels are obtained by exploiting the spatial information. Specifically, this work proposes two methodologies to remove the pixels, the first one is based on spatial blue noise distribution which reduces the probability to remove cluster of neighboring pixels, and the second is a sub-sampling procedure that eliminates every two contiguous pixels, preserving the spatial structure of the scene. The performance of the proposed spectral image clustering framework is evaluated in three datasets showing that a similar accuracy is obtained when up to 50% of the pixels are removed, in addition, it is up to 7.9 times faster compared to the classification of the data sets without incomplete pixels.

scholarly journals Block-Based Spectral Image Reconstruction For Compressive Spectral Imaging Using Smoothness on Graphs

2021 ◽  
Author(s):  
Juan Florez Ospina ◽  
Abdullah Alrushud ◽  
Daniel Lau ◽  
Gonzalo Arce
Keyword(s):  
Image Reconstruction ◽  
Spectral Imaging ◽  
Spectral Image ◽  
Block Based

scholarly journals Матричное радиовидение на основе гетеродинного приема с применением радиолокации непрерывным излучением

2022 ◽  
Vol 48 (1) ◽  
pp. 47
Author(s):  
С.А. Королев ◽  
А.В. Горюнов ◽  
В.В. Паршин
Keyword(s):  
Continuous Wave ◽  
Angular Resolution ◽  
Imaging System ◽  
Imaging Systems ◽  
New Approach ◽  
Wave Radio ◽  
Radio Imaging ◽  
Wave Radar ◽  
Previous Level ◽  
Array Receiver

A new approach to the creation of millimeter-wave radio imaging systems is proposed. This approach is based on the use of an array receiver consisting of a densely packed (pixel size - 4 mm) array of planar mixers located in the focal plane of a quasi-optical objective, with application of the frequency-modulated continuous-wave radar technique. It has been demonstrated that the implementation of the heterodyne type of reception makes it possible to increase the distance range of the array radio imaging system up to ~ 100 m while maintaining the angular resolution at the previous level.

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