- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 26th European Signal Processing Conference (EUSIPCO) - Roma, Italy (2018.9.3-2018.9.7)] 2018 26th European Signal Processing Conference (EUSIPCO) - Spatio-Spectral Multichannel Reconstruction from few Low-Resolution Multispectral Data
摘要： This paper deals with the reconstruction of a 3-D spatio-spectral object observed by a multispectral imaging system, where the original object is blurred with a spectral-variant PSF (Point Spread Function) and integrated over few broad spectral bands. In order to tackle this ill-posed problem, we propose a linear forward model that accounts for direct (or auto) channels and between (or cross) channels degradation, by modeling the imaging system response and the spectral distribution of the object with a piecewise linear function. Reconstruction based on regularization method is proposed, by enforcing spatial and spectral smoothness of the object. We test our approach on simulated data of the Mid-InfraRed Instrument (MIRI) Imager of the James Webb Space Telescope (JWST). Results on simulated multispectral data show a significant improvement over the conventional multichannel method.
关键词： Deconvolution,Image reconstruction,Inverse problems,Multispectral restoration,System modeling
更新于2025-09-23 15:23:52
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Sensitive Damage Detection of Reinforced Concrete Bridge Slab by ``Time-Variant Deconvolution'' of SHF-Band Radar Signal
摘要： In this paper, we focus on ground-penetrating radar (GPR) for infrastructural health monitoring, especially for the monitoring of reinforced concrete (RC) bridge slab. Due to the demand of noncontact and high-speed monitoring technique which can handle vast amounts of aging infrastructures, GPR is a promising tool. However, because radar images consist of many reflected waves, they are usually difficult to interpret. Furthermore, the spatial resolution of system is not enough considering the thickness of target damages, cracks, and segregation are millimeter-to-centimeter order while the wavelength of ordinary GPR ultrahigh-frequency band is over 10 cm. To address these problems, for the purpose of sensitive damage detection, we propose a new algorithm based on deconvolution utilizing a super high-frequency (SHF) band system. First, a distribution of reflection coefficient is inversely estimated by 1-D bridge slab model. Because concrete is found to be a lossy medium at SHF band, we consider the attenuation of signal in deconvolution. The algorithm is called 'time-variant deconvolution' in this paper. After the validation by simulation, the effects of the algorithm and frequency band on damage detection accuracy are evaluated by a field experiment. Though the results show a 1-mm horizontal crack is not detected by measured waves, when it is filled with water, it is detected by time-variant deconvolution. Moreover, the 1-mm dried crack is detected only by time-variant deconvolution at SHF band, which greatly emphasizes the peaks of the reflection coefficient of the crack.
关键词： thin cracks and segregation detection,Ground-penetrating radar (GPR),infrastructural health monitoring,time-variant deconvolution
更新于2025-09-23 15:23:52
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Recursive SURE for image recovery via total variation minimization
摘要： Recently, total variation regularization has become a standard technique, and even a basic tool for image denoising and deconvolution. Generally, the recovery quality strongly depends on the regularization parameter. In this work, we develop a recursive evaluation of Stein’s unbiased risk estimate (SURE) for the parameter selection, based on specific reconstruction algorithms. It enables us to monitor the evolution of mean squared error (MSE) during the iterations. In particular, to deal with large-scale data, we propose a Monte Carlo simulation for the practical computation of SURE, which is free of any explicit matrix operation. Experimental results show that the proposed recursive SURE could lead to highly accurate estimate of regularization parameter and nearly optimal restoration performance in terms of MSE.
关键词： Total variation,Stein’s unbiased risk estimate (SURE),Deconvolution,Jacobian recursion,Denoising
更新于2025-09-23 15:22:29
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[IEEE 2019 International Conference on Optical MEMS and Nanophotonics (OMN) - Daejeon, Korea (South) (2019.7.28-2019.8.1)] 2019 International Conference on Optical MEMS and Nanophotonics (OMN) - Operation verification of tunable plasmonic color filter composed by metal-insulator-metal subwavelength grating and MEMS actuator
摘要： Signal processing in light-microscopy and cell imaging is concerned with reconstructing latent ground truth from imperfect images. This typically requires assuming prior knowledge about the latent ground truth. While this assumption regularizes the problem to an extent where it can be solved, it also biases the result toward the expected. It thus often remains unclear what prior to use for a given practical problem. We argue here that the gradient distribution of natural-scene images may provide a versatile and well-founded prior for light-microscopy images that does not impose assumptions about the geometry of the ground-truth signal, but only about its gradient spectrum. We provide motivation for this choice from different points of view, and we illustrate the resulting regularizer for use on light-microscopy images. We provide a simple parametric model for the resulting prior, leading to ef?ciently solvable variational problems. We demonstrate the use of these models and solvers in a variety of common image-processing tasks, including contrast enhancement, noise-level estimation, denoising, blind deconvolution, and dehazing. We conclude by discussing the limitations and possible interpretations of the prior.
关键词： parametric prior,gradient distribution,noise-level estimation,dehazing,naturalization,denoising,Deconvolution,variational method
更新于2025-09-23 15:21:01
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Calibration-free quantitative analysis of D/H isotopes with a fs-laser filament
摘要： The analytical characteristics of D/H isotopes with a fs-laser filament are investigated via analyzing a set of D-enriched water samples with D concentrations ranging from 0.5 to 20%. The filament emission spectra feature a narrow peak width and near-zero continuum spectral component. The characteristics of Balmer lines (a, b and g) are evaluated, and the Balmer-a line is selected for isotope analysis. Isotopic information is extracted from filament emission spectra through four different approaches: spectral deconvolution least squares algorithm (SDA), partial least squares regression-internal validation (PLSR-IV), partial least squares regression-cross validation (PLSR-CV) and partial least squares regression-calibration free (PLSR-CF). A multivariate spectral fitting procedure is established in the SDA. Fine structure components (FSCs) of Ha and Da were integrated in the SDA, and it shows improved analytical performance compared to the conventional SDA which is carried out by fitting the experimental spectra with two Lorentzian or Voigt functions. It is also found that the SDA with FSCs gives more accurate results than PLSR-IV and PLSR-CV. Furthermore, the analytical performance is significantly improved by the use of PLSR-CF, in which the PLSR calibration matrix is constructed with a synthetic spectra set. The improvement of accuracy for the given sample set further allows a calibration curve exhibiting an R2 exceeding 0.998 and a slop of 1.009. In addition, the calibration procedure with isotopically enriched standard samples is not necessary in PLSR-CF, demonstrating its flexibility over classical chemometric approaches.
关键词： fs-laser filament,PLSR,spectral deconvolution,calibration-free analysis,Balmer lines,D/H isotopes
更新于2025-09-23 15:21:01
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New hybrid metaheuristic algorithm for scintillator gamma ray spectrum analysis
摘要： The Sodium Iodide detector (NaI(Tl)) is one of the most widely used nuclear devices in gamma-ray spectrometry due to its high efficiency and low price. However, this detector has low energy resolution and spectra measured by this detector are associated with Gaussian broadening. Therefore, the detector cannot resolve the photopeaks with very close energies. To overcome this problem, spectral deconvolution methods such as boosted ML-EM and boosted Gold algorithms have been proposed, that somewhat resolve the complex spectrum. But these methods cannot obtain a spectrum consisting of narrow photopeaks. Therefore, due to the importance of spectral deconvolution and its applications, there is always a need for a more efficient and precise method. In this study, a new multi-step method based on metaheuristic algorithms is introduced for deconvolution of NaI(Tl) detector spectrum. The new method is used for deconvolution of measured and simulated complex spectra and results are compared with the results of previous methods. The results show that the new multi-step spectral deconvolution method has a very high accuracy and efficiency in deconvolution of the complex spectra.
关键词： Metaheuristic algorithms,Multi-step method,Spectral deconvolution,NaI(T1) detector
更新于2025-09-23 15:21:01
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Optimal PSF Estimation for Simple Optical System Using a Wide-Band Sensor Based on PSF Measurement
摘要： Simple optical system imaging is a method to simplify optical systems by removing aberrations using image deconvolution. The point spread function (PSF) used in deconvolution is an important factor that affects the image quality. However, it is difficult to obtain optimal PSFs. The blind estimation of PSFs relies heavily on the information in the image. Measured PSFs are often misused because real sensors are wide-band. We present an optimal PSF estimation method based on PSF measurements. Narrow-band PSF measurements at a single depth are used to calibrate the optical system; these enable the simulation of real lenses. Then, we simulate PSFs in the wavelength pass range of each color channel all over the field. The optimal PSFs are computed according to these simulated PSFs. The results indicated that the use of the optimal PSFs significantly reduces the artifacts caused by misuse of PSFs, and enhances the image quality.
关键词： image restoration,deconvolution,imaging sensors,simple optical system,point spread function
更新于2025-09-23 15:21:01
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Restoration of Light Sheet Multi-View Data with the Huygens Fusion and Deconvolution Wizard
摘要： Light sheet fluorescence microscopy (LSFM) allows for high-resolution three-dimensional imaging with minimal photo-damage. By viewing the sample from different directions, different regions of large specimens can be imaged optimally. Moreover, owing to their good spatial resolution and high signal-to-noise ratio, LSFM data are well suited for image deconvolution. Here we present the Huygens Fusion and Deconvolution Wizard, a unique integrated solution for restoring LSFM images, and show that improvements in signal and resolution of 1.5 times and higher are feasible.
关键词： selective plane illumination microscopy (SPIM),Light sheet fluorescence microscopy (LSFM),deconvolution,Huygens,fusion
更新于2025-09-23 15:21:01
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Online Deconvolution for Industrial Hyperspectral Imaging Systems
摘要： This paper proposes a hyperspectral image deconvolution algorithm for the online restoration of hyperspectral images as provided by whiskbroom and pushbroom scanning systems. We introduce a least-mean-squares (LMS)-based framework accounting for the convolution kernel noncausality and including nonquadratic (zero attracting and piecewise constant) regularization terms. This results in the so-called sliding block regularized LMS (SBR-LMS), which maintains a linear complexity compatible with real-time processing in industrial applications. A model for the algorithm mean and mean-squares transient behavior is derived and the stability condition is studied. Experiments are conducted to assess the role of each hyper-parameter. A key feature of the proposed SBR-LMS is that it outperforms standard approaches in low SNR scenarios such as ultra-fast scanning.
关键词： hyperspectral image,LMS,ZA-LMS,online deconvolution
更新于2025-09-19 17:15:36
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Total generalized variation and shearlet transform based Poissonian image deconvolution
摘要： Integrating the advantages of total generalized variation and shearlet transform, this article introduces a hybrid regularizers scheme for deconvolving Poissonian image. Computationally, a highly efficient alternating minimization algorithm associated with variable splitting approach is described to obtain the optimal solution in detail. Illustrationally, in comparison with several current state-of-the-art numerical methods, numerical simulations consistently demonstrate the outstanding performance of our proposed approach to deblurring Poissonian image, in terms of both restoration accuracy and feature-preserving ability.
关键词： Image deconvolution,Alternating minimization method,Shearlet transform,Total generalized variation,Poisson noise
更新于2025-09-19 17:15:36