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multispectral filter array Design by Optimal Sphere Packing

IEEE TRANSACTIONS ON IMAGE PROCESSING 2023年 32卷 3634-3649页

作者： Diaz, Nelson Alvarado, Alejandro Meza, Pablo Guzman, Felipe Vera, Esteban Pontificia Univ Catolica Valparaiso Sch Elect Engn Valparaiso 2340000 Chile Univ La Frontera Dept Elect Engn Temuco 4780000 Chile

multispectral imaging (MSI) collects a datacube of spatio-spectral information of a scene. Many acquisition methods for spectral imaging use scanning, preventing its widespread usage for dynamic scenes. On the other hand, the conventional color filter array (CFA) method often used to sample color images has also been extended to snapshot MSI using a multispectral filter array (MSFA), which is a mosaic of selective spectral filters placed over the Focal Plane array (FPA). However, even state-ofthe- art MSFAs coding patterns produce artifacts and distortions in the reconstructed spectral images, which might be due to the nonoptimal distribution of the spectral filters. To reduce the appearance of artifacts and provide tools for the optimal design of MSFAs, this paper proposes a novel mathematical framework to design MSFAs using a Sphere Packing (SP) approach. By assuming that each sampled filter can be represented by a sphere within the discrete datacube, SP organizes the position of the equal-size and disjoint spheres's centers in a cubic container. Our method is denoted multispectral filter array by Optimal Sphere Packing (MSFA-OSP), which seeks filter positions that maximize the minimum distance between the spheres's centers. Simulation results show an image quality improvement of up to 2 dB and a remarkable boost in spectral similarity when using our proposed MSFA design approach for a variety of reconstruction algorithms. Moreover, MSFA-OSP notably reduces the appearance of false colors and zipper effect artifacts, often seen when using state-of-the-art demosaicking algorithms. Experiments using synthetic and real data prove that the proposed MSFA-OSP outperforms state-of-the-art MSFAs in terms of spatial and spectral fidelity. The code that reproduces the figures of this article is available at https://***/nelson10/***.

关键词： multispectral imaging multispectral filter array sphere packing multispectral image demosaicking

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Design of a Compact Fabry-Pérot multispectral filter array with Low-Sideband Performance

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JOURNAL OF ELECTRONIC MATERIALS 2025年第5期54卷 4106-4113页

作者： Tang, Tiantian Li, Zhiwei Cao, Fushen Zhang, Yile Ding, Tingting Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai 201620 Peoples R China Shanghai Technol & Innovat Vocat Coll Shanghai 201620 Peoples R China

A multispectral filter array (MSFA) based on the Fabry-P & eacute;rot cavity with low-sideband performance and compact design in the near-infrared band is proposed. A thin layer of metal platinum (Pt) was added into the resonant cavity, suppressing the odd-order resonances to improve the selectivity. The dielectric grating metasurfaces were embedded in the cavity to achieve the tuning of the transmission peak by adjusting the width to change the duty cycle. A consistent profile of MSFA was completed based on width adjustment to improve compactness and reduce the fabrication steps. TiO2 and SiO2 have been used to form the distributed Bragg reflectors as highly reflective mirrors for MSFA to achieve high transmittance and narrow linewidth, improving the spectral resolution. The simulated tuning range of the MSFA is from 885 nm to 1171 nm, with a full width at half-maximum (FWHM) ranging from 6 nm to 24 nm, an average transmittance of over 94%, and the sideband transmittance ranging from 3% to 15%. The proposed compact Fabry-P & eacute;rot MSFA is easy to fabricate, with high spectral selectivity and transmittance within the tuning range. It can be applied to integrated multi-band spectral imaging systems.

关键词： Fabry-P & eacute rot multispectral filter array low-sideband compactness dielectric grating metasurface

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Targeted multispectral filter array design for the optimization of endoscopic cancer detection in the gastrointestinal tract

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JOURNAL OF BIOMEDICAL OPTICS 2024年第3期29卷 036005-036005页

作者： Taylor-Williams, Michaela Tao, Ran Sawyer, Travis W. Waterhouse, Dale J. Yoon, Jonghee Bohndiek, Sarah E. Univ Cambridge Dept Phys Cavendish Lab Cambridge England Univ Cambridge Canc Res UK Cambridge Inst Cambridge England Univ Arizona Wyant Coll Opt Sci Tucson AZ USA UCL Wellcome EPRSC Ctr Intervent & Surg Sci London England Ajou Univ Dept Phys Suwon South Korea

Significance Color differences between healthy and diseased tissue in the gastrointestinal (GI) tract are detected visually by clinicians during white light endoscopy;however, the earliest signs of cancer are often just a slightly different shade of pink compared to healthy tissue making it hard to detect. Improving contrast in endoscopy is important for early detection of disease in the GI tract during routine screening and surveillance. Aim We aim to target alternative colors for imaging to improve contrast using custom multispectral filter arrays (MSFAs) that could be deployed in an endoscopic "chip-on-tip" configuration. Approach Using an open-source toolbox, Opti-MSFA, we examined the optimal design of MSFAs for early cancer detection in the GI tract. The toolbox was first extended to use additional classification models (k-nearest neighbor, support vector machine, and spectral angle mapper). Using input spectral data from published clinical trials examining the esophagus and colon, we optimized the design of MSFAs with three to nine different bands. Results We examined the variation of the spectral and spatial classification accuracies as a function of the number of bands. The MSFA configurations tested showed good classification accuracies when compared to the full hyperspectral data available from the clinical spectra used in these studies. Conclusion The ability to retain good classification accuracies with a reduced number of spectral bands could enable the future deployment of multispectral imaging in an endoscopic chip-on-tip configuration using simplified MSFA hardware. Further studies using an expanded clinical dataset are needed to confirm these findings.

关键词： endoscopy colonoscopy esophageal cancer colon cancer multispectral filter array multispectral imaging

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Mosaic Convolution-Attention Network for Demosaicing multispectral filter array Images

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IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2021年 7卷 864-878页

作者： Feng, Kai Zhao, Yongqiang Chan, Jonathan C-W Kong, Seong G. Zhang, Xun Wang, Binglu Northwestern Polytech Univ Shenzhen Inst Res & Dev Shenzhen 518057 Peoples R China Vrije Univ Brussel Dept Elect & Informat B-1050 Brussels Belgium Sejong Univ Dept Comp Engn Seoul 05006 South Korea

This paper presents a mosaic convolution-attention network (MCAN) for demosaicing spectral mosaic images captured using multispectral filter array (MSFA) imaging sensors. MSFA-based multispectral imaging systems acquire multispectral information of a scene in a single snap-shot operation. A complete multispectral image is reconstructed by demosaicing an MSFA-based spectral mosaic image. To avoid aliasing and artifacts in demosaicing, we utilize joint spatial-spectral correlation in a raw mosaic image. The proposed MCAN includes a mosaic convolution module (MCM) and a mosaic attention module (MAM). The MCM extracts features via a learning approach with a margin between splitting the periodic spectral mosaic and keeping the underlying spatial information of the raw image. Based on the strategy of position-sensitive weight sharing, MCM assigns the same weight to pixels with the same relative position in an MSFA. The MAM uses a position-sensitive feature aggregation strategy to describe the loading of mosaic patterns within the feature maps, which gradually reduces mosaic distortion through the attention mechanism. The experimental results on synthetic as well as real-world data show that the proposed scheme outperforms state-of-the-art methods in terms of spatial details and spectral fidelity.

关键词： Correlation Convolution Distortion Standards Sensor arrays Interpolation Image sensors multispectral imaging multispectral image demosaicing multispectral filter array Convolution-attention network deep learning

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Design of a Dual-Mode multispectral filter array

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SENSORS 2023年第15期23卷 6856-6856页

作者： Ye, Zhengnan Xu, Haisong Huang, Yiming Yang, Minhang Zhejiang Univ Coll Opt Sci & Engn State Key Lab Extreme Photon & Instrumentat Hangzhou 310027 Peoples R China

multispectral imaging is valuable in many vision-related fields as it provides an additional modality to observe the world. Cameras equipped with multispectral filter arrays (MSFAs) are typically impractical for everyday use due to their intractable demosaicking and chromatic reproduction processes, which restrict their applicability beyond academic research. In this work, a novel MSFA design is proposed to enable dual-mode imaging for multispectral cameras. In addition to a conventional multispectral image, the camera is also able to produce a Bayer-formed RGB image from a single shot by grouping and merging adjacent pixels in the proposed MSFA, making it suitable for scenarios where display-ready RGB images are required. Furthermore, a two-stage optimization scheme is implemented to jointly optimize objective functions for both imaging modes. The evaluation results on multiple datasets suggest that the proposed MSFA design is able to simultaneously achieve competitive spectral reconstruction accuracy compared to elaborate multispectral cameras and chromatic accuracy compared to commercial RGB cameras.

关键词： multispectral filter array multispectral imaging RGB imaging spectral sensitivity optimization

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Narrowband Image Extraction for multispectral filter array 11

Narrowband Image Extraction for Multispectral Filter Array

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11th International Conference on Graphics and Image Processing (ICGIP)

作者： Hung, Mao-Hsiung Meng, Fanru Zheng, Jishi Fujian Univ Technol Coll Informat Sci & Engn Fuzhou 350118 Peoples R China

ISBN: (纸本)9781510635241

Narrowband image extraction is an essential preprocessing for multispectral imaging of filter array. This paper proposes an automatic method to extract narrowband images from a multispectral image. During offline phase, the method first employs horizontal and vertical projections to obtain initial positions of subsampling points. Then, integer-pixel searching and half-pixel searching optimizes subsampling location. During on-line phase, 1:4 or 1:16 interpolation generates interpolation grids. Finally, four narrowband images are obtained according to the optimized subsampling points and interpolation grids. The experimental result indicates that this method effectively extracts narrowband images from originally mosaic images of multiple spectrums.

关键词： multispectral filter array narrowband image extraction integer-pixel and half-pixel searching

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Demosaicking Using a Spatial Reference Image for an Anti-Aliasing multispectral filter array

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2019年第10期28卷 4984-4996页

作者： Kawase, Maru Shinoda, Kazuma Hasegawa, Madoka Utsunomiya Univ Grad Sch Engn Dept Informat Syst Sci Utsunomiya Tochigi Japan Panasonic Syst Networks R&D Lab Co Ltd Dept Technol Sendai Miyagi 9813206 Japan Utsunomiya Univ Dept Fundamental Engn Sch Engn Utsunomiya 3210904 Japan

multispectral imaging with a multispectral filter array (MSFA) facilitates snapshot imaging;however, a demosaicking process is required to estimate a fully defined multispectral image based on undersampled sensor data. Undersampling induces aliasing and adverse artifacts in the reconstructed image. To solve this problem, Jia et al. proposed the Fourier spectral filter array (FSFA), which can reduce aliasing. In this paper, we analyze the FSFA and a more generalized anti-aliasing MSFA, and we identify the property that makes MSFAs anti-aliasing. Furthermore, we propose a novel demosaicking method that is a hybrid of frequency-decomposition-based and compressive-sensing-based demosaicking. Anti-aliasing MSFAs enable demosaicking to comprehend the precise spatial structures of an image. The image assists our proposed method in precisely reconstructing images using compressive sensing. Our experimental results demonstrated that the proposed method performs better than the existing demosaicking methods, especially in terms of spatial reconstruction.

关键词： multispectral demosaicking multispectral imaging multispectral filter array

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Sensitivity Improvement of Extremely Low Light Scenes with RGB-NIR multispectral filter array Sensor

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SENSORS 2019年第5期19卷 1256-1256页

作者： Jee, Seunghoon Kang, Moon Gi Yonsei Univ Dept Elect & Elect Engn 50 Yonsei Rd Seoul 03722 South Korea

Recently, several red-green-blue near-infrared (RGB-NIR) multispectral filter arrays (MFAs), which include near infrared (NIR) pixels, have been proposed. For extremely low light scenes, the RGB-NIR MFA sensor has been extended to receive NIR light, by adding NIR pixels to supplement for the insufficient visible band light energy. However, the resolution reconstruction of the RGB-NIR MFA, using demosaicing and color restoration methods, is based on the correlation between the NIR pixels and the pixels of other colors;this does not improve the RGB channel sensitivity with respect to the NIR channel sensitivity. In this paper, we propose a color restored image post-processing method to improve the sensitivity and resolution of an RGB-NIR MFA. Although several linear regression based color channel reconstruction methods have taken advantage of the high sensitivity NIR channel, it is difficult to accurately estimate the linear coefficients because of the high level of noise in the color channels under extremely low light conditions. The proposed method solves this problem in three steps: guided filtering, based on the linear similarity between the NIR and color channels, edge preserving smoothing to improve the accuracy of linear coefficient estimation, and residual compensation for lost spatial resolution information. The results show that the proposed method is effective, while maintaining the NIR pixel resolution characteristics, and improving the sensitivity in terms of the signal-to-noise ratio by approximately 13 dB.

关键词： extremely low light sensitivity improvement near infrared multispectral filter array

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multispectral filter array design without training images

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OPTICAL REVIEW 2017年第4期24卷 554-571页

作者： Shinoda, Kazuma Yanagi, Yudai Hayasaki, Yoshio Hasegawa, Madoka Utsunomiya Univ Grad Sch Engn 7-1-2 Yoto Utsunomiya Tochigi 3218585 Japan Utsunomiya Univ Ctr Opt Res & Educ 7-1-2 Yoto Utsunomiya Tochigi 3218585 Japan

multispectral images (MSIs) have been studied for many applications;however, limitations persist in techniques to capture them due to the complexity of assembling one or more prisms and multiple sensor arrays in order to detect signals. Inspired by the application of color filter arrays to commercial digital RGB cameras, a number of researchers have studied multispectral filter arrays (MSFAs) to solve this problem. Determining the measurement wavelength and pattern of an MSFA is important for improving the quality of the demosaicked image. Some conventional studies for designing MSFAs have used training data and have optimized the measurement wavelengths and the pattern by iteratively minimizing the error between the training data and the demosaicked images. We propose a metric to evaluate an MSFA without MSIs, and optimize the measurement wavelengths and the pattern of the MSFA by minimizing the metric. The proposed metric measures the sampling distance between filters in a spatial-spectral domain and quantifies the dispersion of the sampling points by average nearest-neighbor distance (ANND) under a given arbitrary MSFA. Since the quality of the demosaicked image is assumed to be proportional to the degree of dispersion of the sampling points in the spatial-spectral domain, we optimize the MSFA by minimizing the ANND in a nested simulated annealing process. Experimental results show that the optimized MSFA obtained using our method attained a higher peak signal-to-noise ratio (PSNR) than conventional untrained MSFAs in many cases. In addition, the performance difference between some trained MSFAs and the proposed MSFA was small. We also confirmed the validity of the proposed ANND by a comparison with the mean square error obtained from MSI datasets.

关键词： multispectral image multispectral filter array Optimization Demosaicking Average nearest-neighbor distance

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MSFA-Net: A convolutional neural network based on multispectral filter arrays for texture feature extraction

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PATTERN RECOGNITION LETTERS 2023年第1期168卷 93-99页

作者： Amziane, Anis Losson, Olivier Mathon, Benjamin Macaire, Ludovic Univ Lille CNRS Cent Lille UMR CRIStAL 9189 F-59000 Lille France

multispectral snapshot cameras fitted with a multispectral filter array (MSFA) acquire several spectral bands in one shot and provide a raw mosaic image in which a single channel value is available at each pixel. Texture features are classically extracted from fully-defined images that are estimated by demo-saicing. Such an estimation may however cause spatio-spectral artifacts. Moreover, texture feature ex-traction becomes computationally inefficient and yields to high-dimensional features as the number of bands increases. In this paper, we propose an original approach based on a convolutional neural network called MSFA-Net to capture spatio-spectral interactions in raw images at reduced computation costs. Ex-periments of multispectral image classification and outdoor image segmentation show that the proposed approach outperforms several hand-crafted and deep learning-based feature extractors.(c) 2023 Elsevier B.V. All rights reserved.

关键词： multispectral imaging Texture feature extraction multispectral filter array Supervised classification Precision farming

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