In this paper, we discuss the B-spline wavelets introduced by Chui and Wang in [1]. The definition for B-spline wavelet packets is proposed along with the corresponding dual wavelet packets. The properties of B-spline...In this paper, we discuss the B-spline wavelets introduced by Chui and Wang in [1]. The definition for B-spline wavelet packets is proposed along with the corresponding dual wavelet packets. The properties of B-spline wavelet packets are also investigated.展开更多
The Rössler attractor model is an important model that provides valuable insights into the behavior of chaotic systems in real life and is applicable in understanding weather patterns,biological systems,and secur...The Rössler attractor model is an important model that provides valuable insights into the behavior of chaotic systems in real life and is applicable in understanding weather patterns,biological systems,and secure communications.So,this work aims to present the numerical performances of the nonlinear fractional Rössler attractor system under Caputo derivatives by designing the numerical framework based on Ultraspherical wavelets.The Caputo fractional Rössler attractor model is simulated into two categories,(i)Asymmetric and(ii)Symmetric.The Ultraspherical wavelets basis with suitable collocation grids is implemented for comprehensive error analysis in the solutions of the Caputo fractional Rössler attractor model,depicting each computation in graphs and tables to analyze how fractional order affects the model’s dynamics.Approximate solutions obtained through the proposed scheme for integer order are well comparable with the fourth-order Runge-Kutta method.Also,the stability analyses of the considered model are discussed for different equilibrium points.Various fractional orders are considered while performing numerical simulations for the Caputo fractional Rössler attractor model by using Mathematica.The suggested approach can solve another non-linear fractional model due to its straightforward implementation.展开更多
Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
Image captioning,a pivotal research area at the intersection of image understanding,artificial intelligence,and linguistics,aims to generate natural language descriptions for images.This paper proposes an efficient im...Image captioning,a pivotal research area at the intersection of image understanding,artificial intelligence,and linguistics,aims to generate natural language descriptions for images.This paper proposes an efficient image captioning model named Mob-IMWTC,which integrates improved wavelet convolution(IMWTC)with an enhanced MobileNet V3 architecture.The enhanced MobileNet V3 integrates a transformer encoder as its encoding module and a transformer decoder as its decoding module.This innovative neural network significantly reduces the memory space required and model training time,while maintaining a high level of accuracy in generating image descriptions.IMWTC facilitates large receptive fields without significantly increasing the number of parameters or computational overhead.The improvedMobileNet V3 model has its classifier removed,and simultaneously,it employs IMWTC layers to replace the original convolutional layers.This makes Mob-IMWTC exceptionally well-suited for deployment on lowresource devices.Experimental results,based on objective evaluation metrics such as BLEU,ROUGE,CIDEr,METEOR,and SPICE,demonstrate that Mob-IMWTC outperforms state-of-the-art models,including three CNN architectures(CNN-LSTM,CNN-Att-LSTM,CNN-Tran),two mainstream methods(LCM-Captioner,ClipCap),and our previous work(Mob-Tran).Subjective evaluations further validate the model’s superiority in terms of grammaticality,adequacy,logic,readability,and humanness.Mob-IMWTC offers a lightweight yet effective solution for image captioning,making it suitable for deployment on resource-constrained devices.展开更多
Low-light image enhancement aims to improve the visibility of severely degraded images captured under insufficient illumination,alleviating the adverse effects of illumination degradation on image quality.Traditional ...Low-light image enhancement aims to improve the visibility of severely degraded images captured under insufficient illumination,alleviating the adverse effects of illumination degradation on image quality.Traditional Retinex-based approaches,inspired by human visual perception of brightness and color,decompose an image into illumination and reflectance components to restore fine details.However,their limited capacity for handling noise and complex lighting conditions often leads to distortions and artifacts in the enhanced results,particularly under extreme low-light scenarios.Although deep learning methods built upon Retinex theory have recently advanced the field,most still suffer frominsufficient interpretability and sub-optimal enhancement performance.This paper presents RetinexWT,a novel framework that tightly integrates classical Retinex theory with modern deep learning.Following Retinex principles,RetinexWT employs wavelet transforms to estimate illumination maps for brightness adjustment.A detail-recovery module that synergistically combines Vision Transformer(ViT)and wavelet transforms is then introduced to guide the restoration of lost details,thereby improving overall image quality.Within the framework,wavelet decomposition splits input features into high-frequency and low-frequency components,enabling scale-specific processing of global illumination/color cues and fine textures.Furthermore,a gating mechanism selectively fuses down-sampled and up-sampled features,while an attention-based fusion strategy enhances model interpretability.Extensive experiments on the LOL dataset demonstrate that RetinexWT surpasses existing Retinex-oriented deeplearning methods,achieving an average Peak Signal-to-Noise Ratio(PSNR)improvement of 0.22 dB over the current StateOfTheArt(SOTA),thereby confirming its superiority in low-light image enhancement.Code is available at https://github.com/CHEN-hJ516/RetinexWT(accessed on 14 October 2025).展开更多
In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly...In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.展开更多
Scientific analysis of aeolian sand environments is fundamental for sustainable disaster mitigation along desert highways.However,significant regional variability in wind energy conditions complicates accurate charact...Scientific analysis of aeolian sand environments is fundamental for sustainable disaster mitigation along desert highways.However,significant regional variability in wind energy conditions complicates accurate characterization of wind regimes and introduces uncertainty in determining optimal monitoring timescales.Moreover,prevailing sand control measures often rely on standardized designs rather than site-specific adaptive strategies.To address these issues,this study proposes an integrated framework for aeolian environment analysis and develops targeted disaster mitigation strategies tailored for desert highways.The proposed framework employs wavelet transform to unravel the periodic characteristics of wind speed time series and integrates multi-source data(including ERA5 wind datasets,sand samples,ASTER GDEM,and multi-temporal remote sensing imagery)to enable a comprehensive aeolian environmental assessment.Concurrently,a suite of adaptive strategies is formulated to mitigate disaster risks along desert highways.Validated through a case study of the Tumushuk-Kunyu Desert Highway in Xinjiang,China,the framework exhibits high accuracy:predictions of annual aeolian sand transport activity show relative errors mostly below 7%against long-term reference sequences,and the calculated resultant drift direction exhibits a strong correlation with observed dune migration,yielding an R-squared value of 0.96.These findings confirm the framework’s reliability and provide a robust basis for designing adaptive,location-specific mitigation strategies,thereby enhancing the sustainability of desert highway infrastructure.展开更多
Air-gun arrays are used in marine-seismic exploration. Far-field wavelets in subsurface media represent the stacking of single air-gun ideal wavelets. We derived single air-gun ideal wavelets using near-field wavelets...Air-gun arrays are used in marine-seismic exploration. Far-field wavelets in subsurface media represent the stacking of single air-gun ideal wavelets. We derived single air-gun ideal wavelets using near-field wavelets recorded from near-field geophones and then synthesized them into far-field wavelets. This is critical for processing wavelets in marine- seismic exploration. For this purpose, several algorithms are currently used to decompose and synthesize wavelets in the time domain. If the traveltime of single air-gun wavelets is not an integral multiple of the sampling interval, the complex and error-prone resampling of the seismic signals using the time-domain method is necessary. Based on the relation between the frequency-domain phase and the time-domain time delay, we propose a method that first transforms the real near-field wavelet to the frequency domain via Fourier transforms; then, it decomposes it and composes the wavelet spectrum in the frequency domain, and then back transforms it to the time domain. Thus, the resampling problem is avoided and single air-gun wavelets and far-field wavelets can be reliably derived. The effect of ghost reflections is also considered, while decomposing the wavelet and removing the ghost reflections. Modeling and real data processing were used to demonstrate the feasibility of the proposed method.展开更多
A new wavelet finite element method(WFEM)is constructed in this paper and two elements for bending and free vibration problems of a stiffened plate are analyzed.By means of generalized potential energy function and vi...A new wavelet finite element method(WFEM)is constructed in this paper and two elements for bending and free vibration problems of a stiffened plate are analyzed.By means of generalized potential energy function and virtual work principle,the formulations of the bending and free vibration problems of the stiffened plate are derived separately.Then,the scaling functions of the B-spline wavelet on the interval(BSWI)are introduced to discrete the solving field variables instead of conventional polynomial interpolation.Finally,the corresponding two problems can be resolved following the traditional finite element frame.There are some advantages of the constructed elements in structural analysis.Due to the excellent features of the wavelet,such as multi-scale and localization characteristics,and the excellent numerical approximation property of the BSWI,the precise and efficient analysis can be achieved.Besides,transformation matrix is used to translate the meaningless wavelet coefficients into physical space,thus the resolving process is simplified.In order to verify the superiority of the constructed method in stiffened plate analysis,several numerical examples are given in the end.展开更多
Based on B-spline wavelet on the interval （BSWI）, two classes of truncated conical shell elements were constructed to solve axisymmetric problems, i.e. BSWI thin truncated conical shell element and BSWI moderately t...Based on B-spline wavelet on the interval （BSWI）, two classes of truncated conical shell elements were constructed to solve axisymmetric problems, i.e. BSWI thin truncated conical shell element and BSWI moderately thick truncated conical shell element with independent slopedeformation interpolation. In the construction of wavelet-based element, instead of traditional polynomial interpolation, the scaling functions of BSWI were employed to form the shape functions through the constructed elemental transformation matrix, and then construct BSWI element via the variational principle. Unlike the process of direct wavelets adding in the wavelet Galerkin method, the elemental displacement field represented by the coefficients of wavelets expansion was transformed into edges and internal modes via the constructed transformation matrix. BSWI element combines the accuracy of B-spline function approximation and various wavelet-based elements for structural analysis. Some static and dynamic numerical examples of conical shells were studied to demonstrate the present element with higher efficiency and precision than the traditional element.展开更多
Due to the disturbances of spatters, dusts and strong arc light, it is difficult to detect the molten pool edge and the weld line location in CO_2 welding processes. The median filtering and self-multiplication was em...Due to the disturbances of spatters, dusts and strong arc light, it is difficult to detect the molten pool edge and the weld line location in CO_2 welding processes. The median filtering and self-multiplication was employed to preprocess the image of the CO_2 welding in order to detect effectively the edge of molten pool and the location of weld line. The B-spline wavelet algorithm has been investigated, the influence of different scales and thresholds on the results of the edge detection have been compared and analyzed. The experimental results show that better performance to extract the edge of the molten pool and the location of weld line can be obtained by using the B-spline wavelet transform. The proposed edge detection approach can be further applied to the control of molten depth and the seam tracking.展开更多
This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcrafi Unmanned Aerial Vehicle （RUAV） sensor system. By use of wavelet transforms that accurately localize the characterist...This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcrafi Unmanned Aerial Vehicle （RUAV） sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.展开更多
The structure damage detection with spatial wavelets was approached. First, a plane stress problem, a rectangular plate containing a short crack under a distributed loading on the edge, was investigated. The displac...The structure damage detection with spatial wavelets was approached. First, a plane stress problem, a rectangular plate containing a short crack under a distributed loading on the edge, was investigated. The displacement response data along the parallel and perpendicular lines at different positions from the crack were analyzed with the Haar wavelet. The peak in the spatial variations of the wavelets indicates the direction of the crack. In addition, a transverse crack in a cantilever beam was also investigated in the same ways. For these problems, the different crack positions were also simulated to testify the effectiveness of the technique. All the above numerical simulations were processed by the finite element analysis code, ABACUS. The results show that the spatial wavelet is a powerful tool for damage detection, and this new technique sees wide application fields with broad prospects. (Edited author abstract) 14 Refs.展开更多
Recently, we found that side lobes of wavelets have a large impact on the identification of thin sand reservoirs when studying some gas fields in a basin in Northwest China. Reflections from the top of the H Formation...Recently, we found that side lobes of wavelets have a large impact on the identification of thin sand reservoirs when studying some gas fields in a basin in Northwest China. Reflections from the top of the H Formation, in which there are gas-bearing thin sand bodies, have the main wavelet lobe between two weak peak side lobes. The lower one always mixes with another peak reflected from the top of a thin sand reservoir. That makes it difficult to identify the sand reservoir. In order to solve this, many forward models were set up using typical well logs. 2D synthetic profiles were produced using Ricker wavelets to study the relationships between the effects of wavelet side lobes and thin sand position and frequency and between amplitude and the thin sand body. We developed the following conclusions： First, it is easier to identify thin sands in a shallower position. Second, a good way to tell sand body reflections from side lobes is by comparing profiles with different frequency windows. Third, it is helpful and effective to describe sand extent using amplitude attributes.展开更多
After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal ...After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal wavelets from univariate orthogonal wavelets. Non-separable orthogonal wavelets can be achieved. To demonstrate this method, an example is given.展开更多
Continuous Morlet and Mexican hat wavelets are used to analyze a highly irregular rough surface replicated from real turbine blades which are roughened by deposi-tion of foreign materials. The globally dominant aspect...Continuous Morlet and Mexican hat wavelets are used to analyze a highly irregular rough surface replicated from real turbine blades which are roughened by deposi-tion of foreign materials. The globally dominant aspect ratio, length scale, and orientation of the roughness elements are determined. These parameters extracted from this highly irregular rough surface are important for the future studies of their effects on turbulent flows over this kind of rough surfaces encountered in Washington aerospace and power generating industries.展开更多
In this paper, we suggest a method for solving Fredholm integral equation of the first kind based on wavelet basis. The continuous Legendre and Chebyshev wavelets of the first, second, third and fourth kind on [0,1] a...In this paper, we suggest a method for solving Fredholm integral equation of the first kind based on wavelet basis. The continuous Legendre and Chebyshev wavelets of the first, second, third and fourth kind on [0,1] are used and are utilized as a basis in Galerkin method to approximate the solution of integral equations. Then, in some examples the mentioned wavelets are compared with each other.展开更多
This article aims at studying two-direction refinable functions and two-direction wavelets in the setting R^s, s 〉 1. We give a sufficient condition for a two-direction refinable function belonging to L^2（R^s）. The...This article aims at studying two-direction refinable functions and two-direction wavelets in the setting R^s, s 〉 1. We give a sufficient condition for a two-direction refinable function belonging to L^2（R^s）. Then, two theorems are given for constructing biorthogonal （orthogonal） two-direction refinable functions in L^2（R^s） and their biorthogonal （orthogonal） two-direction wavelets, respectively. From the constructed biorthogonal （orthogonal） two-direction wavelets, symmetric biorthogonal （orthogonal） multiwaveles in L^2（R^s） can be obtained easily. Applying the projection method to biorthogonal （orthogonal） two-direction wavelets in L^2（R^s）, we can get dual （tight） two-direction wavelet frames in L^2（R^m）, where m ≤ s. From the projected dual （tight） two-direction wavelet frames in L^2（R^m）, symmetric dual （tight） frames in L^2（R^m） can be obtained easily. In the end, an example is given to illustrate theoretical results.展开更多
In this article, the properties of multiresolution analysis and self-similar tilings on the Heisenberg group are studied. Moreover, we establish a theory to construct an orthonormal Haar wavelet base in L^2（H^d） by ...In this article, the properties of multiresolution analysis and self-similar tilings on the Heisenberg group are studied. Moreover, we establish a theory to construct an orthonormal Haar wavelet base in L^2（H^d） by using self-similar tilings for the acceptable dilations on the Heisenberg group.展开更多
文摘In this paper, we discuss the B-spline wavelets introduced by Chui and Wang in [1]. The definition for B-spline wavelet packets is proposed along with the corresponding dual wavelet packets. The properties of B-spline wavelet packets are also investigated.
基金"La derivada fraccional generalizada,nuevos resultados y aplicaciones a desigualdades integrales"Cod UIO-077-2024supported via funding from Prince Sattam bin Abdulaziz University project number(PSAU/2025/R/1446).
文摘The Rössler attractor model is an important model that provides valuable insights into the behavior of chaotic systems in real life and is applicable in understanding weather patterns,biological systems,and secure communications.So,this work aims to present the numerical performances of the nonlinear fractional Rössler attractor system under Caputo derivatives by designing the numerical framework based on Ultraspherical wavelets.The Caputo fractional Rössler attractor model is simulated into two categories,(i)Asymmetric and(ii)Symmetric.The Ultraspherical wavelets basis with suitable collocation grids is implemented for comprehensive error analysis in the solutions of the Caputo fractional Rössler attractor model,depicting each computation in graphs and tables to analyze how fractional order affects the model’s dynamics.Approximate solutions obtained through the proposed scheme for integer order are well comparable with the fourth-order Runge-Kutta method.Also,the stability analyses of the considered model are discussed for different equilibrium points.Various fractional orders are considered while performing numerical simulations for the Caputo fractional Rössler attractor model by using Mathematica.The suggested approach can solve another non-linear fractional model due to its straightforward implementation.
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
基金funded by National Social Science Fund of China,grant number 23BYY197.
文摘Image captioning,a pivotal research area at the intersection of image understanding,artificial intelligence,and linguistics,aims to generate natural language descriptions for images.This paper proposes an efficient image captioning model named Mob-IMWTC,which integrates improved wavelet convolution(IMWTC)with an enhanced MobileNet V3 architecture.The enhanced MobileNet V3 integrates a transformer encoder as its encoding module and a transformer decoder as its decoding module.This innovative neural network significantly reduces the memory space required and model training time,while maintaining a high level of accuracy in generating image descriptions.IMWTC facilitates large receptive fields without significantly increasing the number of parameters or computational overhead.The improvedMobileNet V3 model has its classifier removed,and simultaneously,it employs IMWTC layers to replace the original convolutional layers.This makes Mob-IMWTC exceptionally well-suited for deployment on lowresource devices.Experimental results,based on objective evaluation metrics such as BLEU,ROUGE,CIDEr,METEOR,and SPICE,demonstrate that Mob-IMWTC outperforms state-of-the-art models,including three CNN architectures(CNN-LSTM,CNN-Att-LSTM,CNN-Tran),two mainstream methods(LCM-Captioner,ClipCap),and our previous work(Mob-Tran).Subjective evaluations further validate the model’s superiority in terms of grammaticality,adequacy,logic,readability,and humanness.Mob-IMWTC offers a lightweight yet effective solution for image captioning,making it suitable for deployment on resource-constrained devices.
基金supported in part by the National Natural Science Foundation of China[Grant number 62471075]the Major Science and Technology Project Grant of the Chongqing Municipal Education Commission[Grant number KJZD-M202301901].
文摘Low-light image enhancement aims to improve the visibility of severely degraded images captured under insufficient illumination,alleviating the adverse effects of illumination degradation on image quality.Traditional Retinex-based approaches,inspired by human visual perception of brightness and color,decompose an image into illumination and reflectance components to restore fine details.However,their limited capacity for handling noise and complex lighting conditions often leads to distortions and artifacts in the enhanced results,particularly under extreme low-light scenarios.Although deep learning methods built upon Retinex theory have recently advanced the field,most still suffer frominsufficient interpretability and sub-optimal enhancement performance.This paper presents RetinexWT,a novel framework that tightly integrates classical Retinex theory with modern deep learning.Following Retinex principles,RetinexWT employs wavelet transforms to estimate illumination maps for brightness adjustment.A detail-recovery module that synergistically combines Vision Transformer(ViT)and wavelet transforms is then introduced to guide the restoration of lost details,thereby improving overall image quality.Within the framework,wavelet decomposition splits input features into high-frequency and low-frequency components,enabling scale-specific processing of global illumination/color cues and fine textures.Furthermore,a gating mechanism selectively fuses down-sampled and up-sampled features,while an attention-based fusion strategy enhances model interpretability.Extensive experiments on the LOL dataset demonstrate that RetinexWT surpasses existing Retinex-oriented deeplearning methods,achieving an average Peak Signal-to-Noise Ratio(PSNR)improvement of 0.22 dB over the current StateOfTheArt(SOTA),thereby confirming its superiority in low-light image enhancement.Code is available at https://github.com/CHEN-hJ516/RetinexWT(accessed on 14 October 2025).
基金supported by the National Natural Science Foundation of China(42430303)Strategy Priority Research Program(Category B)of the Chinese Academy of Sciences(XDB0710000)+2 种基金National Natural Science Foundation of China(42288201)the National Key R&D Program of China(2023YFF0803203)the IGGCAS start-up funding(Grant No.E251510101).
文摘In wave-equation migration and demigration,the cross-correlation imaging/forwarding step implicitly injects an additional copy of the source wavelet,so that the amplitude spectrum of the wavelet is applied redundantly(effectively imposing a wavelet-spectrum weighting,often akin to an amplitude-squared bias).This redundancy degrades structural fidelity and amplitude balance yet is frequently overlooked.We(i)formalize the mechanism by which cross-correlation duplicates the source-wavelet amplitude effect in both migration and demigration,and(ii)introduce a source-equalized operator that removes the redundancy by deconvolving(or dividing by)the wavelet amplitude spectrum in the imaging condition and its demigration counterpart,while leaving phase/kinematics intact.Using a band-limited Ricker wavelet on a two-layer model and on Marmousi,we show that,if unmanaged,the redundant wavelet spectrum broadens main lobes,introduces ringing,and suppresses vertical resolution in migrated images,and inflates spectrum mismatches between demigrated and observed data even when peak times agree.With our correction,images recover observed-data-consistent bandwidth and sharpened interfaces,and demigrated data also exhibit improved spectrum conformity and reduced amplitude misfit.The results clarify when source amplitudes matter,why cross-correlation makes them redundantly matter,and how a lightweight spectral correction restores physically meaningful amplitude behavior in wave-equation migration/demigration.
基金jointly funded by the Joint Funds of the National Natural Science Foundation of China(Grant No.U2568210)the Interdisciplinary Research Program of Shihezi University(Grant No.JCYJ202317)the National Natural Science Foundation of China(Grant No.12362035)。
文摘Scientific analysis of aeolian sand environments is fundamental for sustainable disaster mitigation along desert highways.However,significant regional variability in wind energy conditions complicates accurate characterization of wind regimes and introduces uncertainty in determining optimal monitoring timescales.Moreover,prevailing sand control measures often rely on standardized designs rather than site-specific adaptive strategies.To address these issues,this study proposes an integrated framework for aeolian environment analysis and develops targeted disaster mitigation strategies tailored for desert highways.The proposed framework employs wavelet transform to unravel the periodic characteristics of wind speed time series and integrates multi-source data(including ERA5 wind datasets,sand samples,ASTER GDEM,and multi-temporal remote sensing imagery)to enable a comprehensive aeolian environmental assessment.Concurrently,a suite of adaptive strategies is formulated to mitigate disaster risks along desert highways.Validated through a case study of the Tumushuk-Kunyu Desert Highway in Xinjiang,China,the framework exhibits high accuracy:predictions of annual aeolian sand transport activity show relative errors mostly below 7%against long-term reference sequences,and the calculated resultant drift direction exhibits a strong correlation with observed dune migration,yielding an R-squared value of 0.96.These findings confirm the framework’s reliability and provide a robust basis for designing adaptive,location-specific mitigation strategies,thereby enhancing the sustainability of desert highway infrastructure.
基金supported by the Geosciences and Technology Academy of China University of Petroleum(East China)
文摘Air-gun arrays are used in marine-seismic exploration. Far-field wavelets in subsurface media represent the stacking of single air-gun ideal wavelets. We derived single air-gun ideal wavelets using near-field wavelets recorded from near-field geophones and then synthesized them into far-field wavelets. This is critical for processing wavelets in marine- seismic exploration. For this purpose, several algorithms are currently used to decompose and synthesize wavelets in the time domain. If the traveltime of single air-gun wavelets is not an integral multiple of the sampling interval, the complex and error-prone resampling of the seismic signals using the time-domain method is necessary. Based on the relation between the frequency-domain phase and the time-domain time delay, we propose a method that first transforms the real near-field wavelet to the frequency domain via Fourier transforms; then, it decomposes it and composes the wavelet spectrum in the frequency domain, and then back transforms it to the time domain. Thus, the resampling problem is avoided and single air-gun wavelets and far-field wavelets can be reliably derived. The effect of ghost reflections is also considered, while decomposing the wavelet and removing the ghost reflections. Modeling and real data processing were used to demonstrate the feasibility of the proposed method.
基金This work was supported by the National Natural Science Foundation of China(Nos.51405370&51421004)the National Key Basic Research Program of China(No.2015CB057400)+2 种基金the project supported by Natural Science Basic Plan in Shaanxi Province of China(No.2015JQ5184)the Fundamental Research Funds for the Central Universities(xjj2014014)Shaanxi Province Postdoctoral Research Project.
文摘A new wavelet finite element method(WFEM)is constructed in this paper and two elements for bending and free vibration problems of a stiffened plate are analyzed.By means of generalized potential energy function and virtual work principle,the formulations of the bending and free vibration problems of the stiffened plate are derived separately.Then,the scaling functions of the B-spline wavelet on the interval(BSWI)are introduced to discrete the solving field variables instead of conventional polynomial interpolation.Finally,the corresponding two problems can be resolved following the traditional finite element frame.There are some advantages of the constructed elements in structural analysis.Due to the excellent features of the wavelet,such as multi-scale and localization characteristics,and the excellent numerical approximation property of the BSWI,the precise and efficient analysis can be achieved.Besides,transformation matrix is used to translate the meaningless wavelet coefficients into physical space,thus the resolving process is simplified.In order to verify the superiority of the constructed method in stiffened plate analysis,several numerical examples are given in the end.
基金Project supported by the National Natural Science Foundation of China (Nos. 50335030, 50505033 and 50575171)National Basic Research Program of China (No. 2005CB724106)Doctoral Program Foundation of University of China(No. 20040698026)
文摘Based on B-spline wavelet on the interval （BSWI）, two classes of truncated conical shell elements were constructed to solve axisymmetric problems, i.e. BSWI thin truncated conical shell element and BSWI moderately thick truncated conical shell element with independent slopedeformation interpolation. In the construction of wavelet-based element, instead of traditional polynomial interpolation, the scaling functions of BSWI were employed to form the shape functions through the constructed elemental transformation matrix, and then construct BSWI element via the variational principle. Unlike the process of direct wavelets adding in the wavelet Galerkin method, the elemental displacement field represented by the coefficients of wavelets expansion was transformed into edges and internal modes via the constructed transformation matrix. BSWI element combines the accuracy of B-spline function approximation and various wavelet-based elements for structural analysis. Some static and dynamic numerical examples of conical shells were studied to demonstrate the present element with higher efficiency and precision than the traditional element.
文摘Due to the disturbances of spatters, dusts and strong arc light, it is difficult to detect the molten pool edge and the weld line location in CO_2 welding processes. The median filtering and self-multiplication was employed to preprocess the image of the CO_2 welding in order to detect effectively the edge of molten pool and the location of weld line. The B-spline wavelet algorithm has been investigated, the influence of different scales and thresholds on the results of the edge detection have been compared and analyzed. The experimental results show that better performance to extract the edge of the molten pool and the location of weld line can be obtained by using the B-spline wavelet transform. The proposed edge detection approach can be further applied to the control of molten depth and the seam tracking.
文摘This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcrafi Unmanned Aerial Vehicle （RUAV） sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.
基金The project supported by the National Natural Science Foundation of China
文摘The structure damage detection with spatial wavelets was approached. First, a plane stress problem, a rectangular plate containing a short crack under a distributed loading on the edge, was investigated. The displacement response data along the parallel and perpendicular lines at different positions from the crack were analyzed with the Haar wavelet. The peak in the spatial variations of the wavelets indicates the direction of the crack. In addition, a transverse crack in a cantilever beam was also investigated in the same ways. For these problems, the different crack positions were also simulated to testify the effectiveness of the technique. All the above numerical simulations were processed by the finite element analysis code, ABACUS. The results show that the spatial wavelet is a powerful tool for damage detection, and this new technique sees wide application fields with broad prospects. (Edited author abstract) 14 Refs.
文摘Recently, we found that side lobes of wavelets have a large impact on the identification of thin sand reservoirs when studying some gas fields in a basin in Northwest China. Reflections from the top of the H Formation, in which there are gas-bearing thin sand bodies, have the main wavelet lobe between two weak peak side lobes. The lower one always mixes with another peak reflected from the top of a thin sand reservoir. That makes it difficult to identify the sand reservoir. In order to solve this, many forward models were set up using typical well logs. 2D synthetic profiles were produced using Ricker wavelets to study the relationships between the effects of wavelet side lobes and thin sand position and frequency and between amplitude and the thin sand body. We developed the following conclusions： First, it is easier to identify thin sands in a shallower position. Second, a good way to tell sand body reflections from side lobes is by comparing profiles with different frequency windows. Third, it is helpful and effective to describe sand extent using amplitude attributes.
基金This research was partially supported by National Natural Science Foundation of China (10371033 60403011).
文摘After some permutation of conjugate quadrature filter, new conjugate quadrature filters can be derived. In terms of this permutation, an approach is developed for constructing compactly supported bivariate orthogonal wavelets from univariate orthogonal wavelets. Non-separable orthogonal wavelets can be achieved. To demonstrate this method, an example is given.
基金supported by Wright State UniversityDayton+2 种基金OHU.S.A.The authors thank Professor K.T.CHRISTENSEN at University of Illinois at Urbana-Champaign for providing the roughness topography data
文摘Continuous Morlet and Mexican hat wavelets are used to analyze a highly irregular rough surface replicated from real turbine blades which are roughened by deposi-tion of foreign materials. The globally dominant aspect ratio, length scale, and orientation of the roughness elements are determined. These parameters extracted from this highly irregular rough surface are important for the future studies of their effects on turbulent flows over this kind of rough surfaces encountered in Washington aerospace and power generating industries.
文摘In this paper, we suggest a method for solving Fredholm integral equation of the first kind based on wavelet basis. The continuous Legendre and Chebyshev wavelets of the first, second, third and fourth kind on [0,1] are used and are utilized as a basis in Galerkin method to approximate the solution of integral equations. Then, in some examples the mentioned wavelets are compared with each other.
基金supported by the Natural Science Foundation China(11126343)Guangxi Natural Science Foundation(2013GXNSFBA019010)+1 种基金supported by Natural Science Foundation China(11071152)Natural Science Foundation of Guangdong Province(10151503101000025,S2011010004511)
文摘This article aims at studying two-direction refinable functions and two-direction wavelets in the setting R^s, s 〉 1. We give a sufficient condition for a two-direction refinable function belonging to L^2（R^s）. Then, two theorems are given for constructing biorthogonal （orthogonal） two-direction refinable functions in L^2（R^s） and their biorthogonal （orthogonal） two-direction wavelets, respectively. From the constructed biorthogonal （orthogonal） two-direction wavelets, symmetric biorthogonal （orthogonal） multiwaveles in L^2（R^s） can be obtained easily. Applying the projection method to biorthogonal （orthogonal） two-direction wavelets in L^2（R^s）, we can get dual （tight） two-direction wavelet frames in L^2（R^m）, where m ≤ s. From the projected dual （tight） two-direction wavelet frames in L^2（R^m）, symmetric dual （tight） frames in L^2（R^m） can be obtained easily. In the end, an example is given to illustrate theoretical results.
基金Sponsored by the NSFC (10871003, 10701008, 10726064)the Specialized Research Fund for the Doctoral Program of Higher Education of China (2007001040)
文摘In this article, the properties of multiresolution analysis and self-similar tilings on the Heisenberg group are studied. Moreover, we establish a theory to construct an orthonormal Haar wavelet base in L^2（H^d） by using self-similar tilings for the acceptable dilations on the Heisenberg group.
