Research

17 pages, 3355 KiB

Open AccessArticle

Suitable Integral Sampling for Bandpass-Sampling Time-Modulated Fourier Transform Spectroscopy

by Xinwen Chen, Zheng Tan, Na Zhao, Jianwei Wang, Yangyang Liu, Yinhui Tang, Peidong He, Weiyan Li, Jianying Sun, Jia Si and Qunbo Lv

Appl. Sci. 2024, 14(3), 1009; https://doi.org/10.3390/app14031009 - 24 Jan 2024

Viewed by 514

Abstract

For traditional Fourier transform (FTS), its integral sampling usually meets the Spectral Modulation Transfer Function (SMTF) criterion. However, for bandpass-sampling Fourier transform spectroscopy (BPS-FTS), based on our analysis, the integral sampling condition derived from the Spectral Modulation Transfer Function (SMTF) is excessively stringent. [...] Read more.

For traditional Fourier transform (FTS), its integral sampling usually meets the Spectral Modulation Transfer Function (SMTF) criterion. However, for bandpass-sampling Fourier transform spectroscopy (BPS-FTS), based on our analysis, the integral sampling condition derived from the Spectral Modulation Transfer Function (SMTF) is excessively stringent. In other words, the interval of the integral sampling time that fulfills the tolerance requirements for the reconstructed spectrum is very narrow. There are numerous integration sampling time intervals outside this range that still meet the tolerance requirements for the reconstructed spectrum. In this paper, through theoretical modeling, we propose a method based on average |SMTF| as the selection criterion for the integration sampling time. Through simulation analysis, it is evident that the intervals and range of the integral sampling time obtained via this method are more accurate, ensuring the tolerance requirements of the reconstructed spectrum. Under these intervals, when conducting integral sampling on the interferogram, the spectral deviation of the reconstructed spectrum is minimal, and the Spectral Correlation Mapper (SCM) is nearly equal to one. This indicates that compared with the SMTF criterion in traditional FTS, this method is more suitable for the characteristics of BPS-FTS. The analysis in this paper can provide theoretical and simulation support for the implementation of BPS-FTS. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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21 pages, 32703 KiB

Open AccessArticle

Visual Image Dehazing Using Polarimetric Atmospheric Light Estimation

by Shuai Liu, Ying Li, Hang Li, Bin Wang, Yuanhao Wu and Zhenduo Zhang

Appl. Sci. 2023, 13(19), 10909; https://doi.org/10.3390/app131910909 - 01 Oct 2023

Cited by 1 | Viewed by 906

Abstract

The precision in evaluating global ambient light profoundly impacts the performance of image-dehazing technologies. Many approaches for quantifying atmospheric light intensity suffer from inaccuracies, leading to a decrease in dehazing effectiveness. To address this challenge, we introduce an approach for estimating atmospheric light [...] Read more.

The precision in evaluating global ambient light profoundly impacts the performance of image-dehazing technologies. Many approaches for quantifying atmospheric light intensity suffer from inaccuracies, leading to a decrease in dehazing effectiveness. To address this challenge, we introduce an approach for estimating atmospheric light based on the polarization contrast between the sky and the scene. By employing this method, we enhance the precision of atmospheric light estimation, enabling the more accurate identification of sky regions within the image. We adapt the original dark channel dehazing algorithm using this innovative technique, resulting in the development of a polarization-based dehazing imaging system employed in practical engineering applications. Experimental results reveal a significant enhancement in the accuracy of atmospheric light estimation within the dark channel dehazing algorithm. Consequently, this method enhances the overall perceptual quality of dehazed images. The proposed approach demonstrates a 28 percent improvement in SSIM and a contrast increase of over 20 percent when compared to the previous method. Additionally, the created dehazing system exhibits real-time processing capabilities. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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26 pages, 3539 KiB

Open AccessArticle

Inpainting in Discrete Sobolev Spaces: Structural Information for Uncertainty Reduction

by Marco Seracini and Stephen R. Brown

Appl. Sci. 2023, 13(16), 9405; https://doi.org/10.3390/app13169405 - 18 Aug 2023

Viewed by 642

Abstract

In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion to what happens in the theoretical Sobolev spaces: its [...] Read more.

In this article, we introduce a new mathematical functional whose minimization determines the quality of the solution for the exemplar-based inpainting-by-patch problem. The new functional expression includes finite difference terms in a similar fashion to what happens in the theoretical Sobolev spaces: its use reduces the uncertainty in the choice of the most suitable values for each point to inpaint. Moreover, we introduce a probabilistic model by which we prove that the usual principal directions, generally employed for continuous problems, are not enough to achieve consistent reconstructions in the discrete inpainting asset. Finally, we formalize a new priority index and new rules for its dynamic update. The quality of the reconstructions, achieved using a reduced neighborhood size of more than

95 %

with respect to the current state-of-the-art algorithms based on the same inpainting approach, further provides the experimental validation of the method. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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19 pages, 4576 KiB

Open AccessArticle

Hyperspectral Anomaly Detection Based on Multi-Feature Joint Trilateral Filtering and Cooperative Representation

by Huan Li, Jun Tang and Huixin Zhou

Appl. Sci. 2023, 13(12), 6943; https://doi.org/10.3390/app13126943 - 08 Jun 2023

Cited by 2 | Viewed by 761

Abstract

The hyperspectral anomaly detection algorithm based on collaborative representation does not fully utilize the two-dimensional spatial features in hyperspectral images. It also has the problem that anomalous pixels will pollute the background dictionary and induce bad detection performance. Based on these, this paper [...] Read more.

The hyperspectral anomaly detection algorithm based on collaborative representation does not fully utilize the two-dimensional spatial features in hyperspectral images. It also has the problem that anomalous pixels will pollute the background dictionary and induce bad detection performance. Based on these, this paper proposes a hyperspectral anomaly detection algorithm based on multiple feature joint trilateral filtering and collaborative representation. The algorithm first introduces an improved trilateral filtering algorithm, which utilizes the spatial features of hyperspectral images. The preliminary positions of possible abnormal objects are determined. On this basis, abnormal removal and background filling are performed to obtain a purified background. Finally, the purified background and the original hyperspectral image are used for joint collaborative representation to complete the detection. Experimental results show that the detection accuracy of the algorithm proposed in this paper was efficiently improved by introducing multiple feature joint trilateral filtering, where multiple spatial spectrum features are utilized. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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28 pages, 2220 KiB

Open AccessFeature PaperArticle

A Graduated Non-Convexity Technique for Dealing Large Point Spread Functions

by Antonio Boccuto, Ivan Gerace and Valentina Giorgetti

Appl. Sci. 2023, 13(10), 5861; https://doi.org/10.3390/app13105861 - 09 May 2023

Viewed by 937

Abstract

This paper focuses on reducing the computational cost of a GNC Algorithm for deblurring images when dealing with full symmetric Toeplitz block matrices composed of Toeplitz blocks. Such a case is widespread in real cases when the PSF has a vast range. The [...] Read more.

This paper focuses on reducing the computational cost of a GNC Algorithm for deblurring images when dealing with full symmetric Toeplitz block matrices composed of Toeplitz blocks. Such a case is widespread in real cases when the PSF has a vast range. The analysis in this paper centers around the class of gamma matrices, which can perform vector multiplications quickly. The paper presents a theoretical and experimental analysis of how

γ

-matrices can accurately approximate symmetric Toeplitz matrices. The proposed approach involves adding a minimization step for a new approximation of the energy function to the GNC technique. Specifically, we replace the Toeplitz matrices found in the blocks of the blur operator with

γ

-matrices in this approximation. The experimental results demonstrate that the new GNC algorithm proposed in this paper reduces computation time by over

20 %

compared with its previous version. The image reconstruction quality, however, remains unchanged. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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16 pages, 3476 KiB

Open AccessArticle

Detection of Bad Stapled Nails in Wooden Packages

by Carlos Ricolfe-Viala, Antonio Correcher and Carlos Blanes

Appl. Sci. 2023, 13(9), 5644; https://doi.org/10.3390/app13095644 - 04 May 2023

Cited by 1 | Viewed by 1009

Abstract

Wooden nail-stitched crates are widely used for fruit transportation. Bad stapled nails are transformed into severe product damage that creates stains on the crate due to its juice. In consequence, the final customer depreciates the product because the quality product is in doubt. [...] Read more.

Wooden nail-stitched crates are widely used for fruit transportation. Bad stapled nails are transformed into severe product damage that creates stains on the crate due to its juice. In consequence, the final customer depreciates the product because the quality product is in doubt. Human visual inspection of badly stapled nails is a non-effective solution since constant criteria are difficult to reach for all of crate production. A system for the in-line inspection based on a conveyor belt of badly stapled nails in stitched crates is presented. The developed inspection system is discussed with the definition of the computer vision system used to identify fails and the description of image processing algorithms. The experiments are focused on a comparative analysis of the performance of five state-of-the-art classification algorithms based on a deep neural network and traditional computer vision algorithms, highlighting the trade-off between speed and precision in the detection. An accuracy of over 95% is achieved if the user defines the nail location in the image. The presented work constitutes a benchmark to guide deep-learning computer vision algorithms in realistic applications. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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16 pages, 6456 KiB

Open AccessArticle

Sampling by Difference as a Method of Applying the Sampling Kantorovich Model in Digital Image Processing

by Marco Seracini and Gianluca Vinti

Appl. Sci. 2023, 13(9), 5594; https://doi.org/10.3390/app13095594 - 30 Apr 2023

Viewed by 856

Abstract

In this paper, the connections between the Sampling Kantorovich model and the sampling process are highlighted and exploited. Based on the theoretical framework of the Sampling Kantorovich operators, a sampling paradigm, here named Sampling Kantorovich by Difference (SKD), is introduced. In line of [...] Read more.

In this paper, the connections between the Sampling Kantorovich model and the sampling process are highlighted and exploited. Based on the theoretical framework of the Sampling Kantorovich operators, a sampling paradigm, here named Sampling Kantorovich by Difference (SKD), is introduced. In line of principle, SKD allows for overcoming the technical limitation due to the fact that the resolution of a signal/image is strictly connected with the size of the used sensors. We analyze the paradigm in the case of a simulated super resolution type problem. The same mathematical model, being extendable to other signal reconstruction procedures, suggests a theoretical way for new technical solutions in the sampling procedures. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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19 pages, 7072 KiB

Open AccessArticle

Mathematical Modeling of Battery Degradation Based on Direct Measurements and Signal Processing Methods

by Joaquín de la Vega, Jordi-Roger Riba and Juan Antonio Ortega-Redondo

Appl. Sci. 2023, 13(8), 4938; https://doi.org/10.3390/app13084938 - 14 Apr 2023

Cited by 1 | Viewed by 2703

Abstract

This paper proposes and evaluates the behavior of a new health indicator to estimate the capacity fade of lithium-ion batteries and their state of health (SOH). This health indicator is advantageous because it does not require the acquisition of data from full charge–discharge [...] Read more.

This paper proposes and evaluates the behavior of a new health indicator to estimate the capacity fade of lithium-ion batteries and their state of health (SOH). This health indicator is advantageous because it does not require the acquisition of data from full charge–discharge cycles, since it is calculated within a narrow SOC interval where the voltage vs. SOC relationship is very linear and that is within the usual transit range for most practical charge and discharge cycles. As a result, only a small fraction of the data points of a full charge–discharge cycle are required, reducing storage and computational resources while providing accurate results. Finally, by using the battery model defined by the Nernst equation, the behavior of future charge–discharge cycles can be accurately predicted, as shown by the results presented in this paper. The proposed approach requires the application of appropriate signal processing techniques, from discrete wavelet filtering to prediction methods based on linear fitting and autoregressive integrated moving average algorithms. Full article

(This article belongs to the Special Issue Signal and Image Processing: From Theory to Applications)

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