Signal Processing最新文献

Distributed filtering with time-varying topology: A temporal-difference learning approach in dual games 具有时变拓扑结构的分布式过滤：双重博弈中的时差学习方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-12 DOI: 10.1016/j.sigpro.2024.109772

Huiwen Xue , Jiwei Wen , Ruichao Li , Xiaoli Luan

{"title":"Distributed filtering with time-varying topology: A temporal-difference learning approach in dual games","authors":"Huiwen Xue , Jiwei Wen , Ruichao Li , Xiaoli Luan","doi":"10.1016/j.sigpro.2024.109772","DOIUrl":"10.1016/j.sigpro.2024.109772","url":null,"abstract":"<div><div>This study aims to develop a dual games (DGs) mechanism and implement a temporal difference learning (TDL) approach to address distributed filter design while considering network-induced time-varying topology from individual optimality and global equilibrium perspectives. In a detailed analysis, each filtering node (FN) treats its individual filtering action and exogenous disturbance as opposing elements, striving to determine the optimal policy while accounting for the worst-case scenario. This competition between FN and the disturbance culminates in a zero-sum game. Simultaneously, FN collaborates effectively with its neighbors to achieve consensus estimation, giving rise to a non-zero-sum game. Notably, an error-based filtering action is built to solve challenges posed by DGs. Ultimately, each FN attains its estimation at a minimum cost, and the entire distributed filtering network achieves the consensus estimation at a Nash equilibrium. Moreover, the transition probability correlation matrices (TPCMs) of the time-varying topology are obtained through direct observation of multi-episodes of topological transition trajectories. It has been proved that with a sufficiently ample number of episodes, TPCMs converge to their optimal values when TPs are known as apriori. Finally, a numerical example and an aero-engine system are presented to illustrate the effectiveness and practical potential of the proposed method.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109772"},"PeriodicalIF":3.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MABDT: Multi-scale attention boosted deformable transformer for remote sensing image dehazing MABDT：用于遥感图像去毛刺的多尺度注意力增强可变形变换器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-07 DOI: 10.1016/j.sigpro.2024.109768

Jin Ning, Jie Yin, Fei Deng, Lianbin Xie

{"title":"MABDT: Multi-scale attention boosted deformable transformer for remote sensing image dehazing","authors":"Jin Ning, Jie Yin, Fei Deng, Lianbin Xie","doi":"10.1016/j.sigpro.2024.109768","DOIUrl":"10.1016/j.sigpro.2024.109768","url":null,"abstract":"<div><div>Owing to the heterogeneous spatial distribution and non-uniform morphological characteristics of haze in remote sensing images (RSIs), conventional dehazing algorithms struggle to precisely recover the fine-grained details of terrestrial objects. To address this issue, a novel multi-scale attention boosted deformable Transformer (MABDT) tailored for RSI dehazing is proposed. This framework synergizes the multi-receptive field features elicited by convolutional neural network (CNN) with the long-term dependency features derived from Transformer, which facilitates a more adept restitution of texture and intricate detail information within RSIs. Firstly, spatial attention deformable convolution is introduced for computation of multi-head self-attention in the Transformer block, particularly in addressing complex haze scenarios encountered in RSIs. Subsequently, a multi-scale attention feature enhancement (MAFE) block is designed, tailored to capture local and multi-level detailed information features using multi-receptive field convolution operations, thereby accommodating non-uniform haze. Finally, a multi-level feature complementary fusion (MFCF) block is proposed, leveraging both shallow and deep features acquired from all encoding layers to augment each level of reconstructed image. The dehazing performance is evaluated on 6 open-source datasets, and quantitative and qualitative experimental results demonstrate the advancements of the proposed method in both metrical scores and visual quality. The source code is available at <span><span>https://github.com/ningjin00/MABDT</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109768"},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A new method for judging thermal image quality with applications 判断热图像质量的新方法及其应用

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-07 DOI: 10.1016/j.sigpro.2024.109769

Sos Agaian , Hrach Ayunts , Thaweesak Trongtirakul , Sargis Hovhannisyan

{"title":"A new method for judging thermal image quality with applications","authors":"Sos Agaian , Hrach Ayunts , Thaweesak Trongtirakul , Sargis Hovhannisyan","doi":"10.1016/j.sigpro.2024.109769","DOIUrl":"10.1016/j.sigpro.2024.109769","url":null,"abstract":"<div><div>Infrared thermal imaging, a non-destructive testing technology, measures the surface temperature of objects. Assessing thermal image quality is crucial for image monitoring, system design, algorithm optimization, and benchmarking. However, developing objective metrics that align with human perception is challenging due to the distinct structure of thermal images, which often feature high background temperatures and minimal variance between objects and the background. Existing methods typically target specific local features or overall image contrast, but new measures are needed to bridge the gap between objective performance and the unique characteristics of thermal images.</div><div>We propose a novel image quality assessment (IQA) method inspired by the human vision system, specifically designed for thermal images, harmonizing local and global data. The primary contributions include (1) innovative local, global, and hybrid thermal quality assessment methods that deliver precise image quality predictions without needing reference images, (2) an experimental analysis evaluating the developed blind thermal IQA measure’s applicability to various thermal images, and (3) a comprehensive analysis of traditional IQA measure-based methods applied to publicly accessible thermal databases. Extensive simulations demonstrate our method’s competitive performance and strong alignment with human perception of image quality.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109769"},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning feature-weighted regularization discriminative correlation filters for real-time UAV tracking 学习用于无人飞行器实时跟踪的特征加权正则化判别相关滤波器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-07 DOI: 10.1016/j.sigpro.2024.109765

Xiumin Wang , Feng Ma , Xuming Wang , Chen Chen

{"title":"Learning feature-weighted regularization discriminative correlation filters for real-time UAV tracking","authors":"Xiumin Wang , Feng Ma , Xuming Wang , Chen Chen","doi":"10.1016/j.sigpro.2024.109765","DOIUrl":"10.1016/j.sigpro.2024.109765","url":null,"abstract":"<div><div>Traditional discriminative correlation filters used for tracking unmanned aerial vehicle objects are often disrupted by concealed noise, resulting in unstable tracking results. Various methods have been developed to search for optimal feature combinations and construct feature weight pools. However, these methods often overlook the significance of different feature channels in tracking frames. Irrespective of the availability of the effective target information, a tracker regards all feature channels similarly. This makes it challenging for the tracker to avoid learning the background noise from such feature combinations. This study proposes a channel-level feature-weighting method called learning feature-weighted regularization discriminative correlation filters (FWRDCF). By introducing feature-weighted regularization (FWR) that automatically adjusts the weights of the feature channels into each frame, the FWRDCF tracker can significantly suppress background noise. Furthermore, the alternating direction method of multipliers is used to obtain the closed-form solution of the model, thereby establishing a robust correlation filter-tracking architecture. Experiments on UAV123@10fps, UAV123, DTB70, and UAVDT demonstrated that the FWRDCF tracker achieved better tracking performance than 15 other state-of-the-art trackers. An integration study of three baselines (AutoTrack, STRCF, and BACF) reveals that the proposed FWR can be integrated with trackers with multi-channel features.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109765"},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recursive-RARE-based three-dimensional parameter estimation of near-field source considering amplitude attenuation 考虑振幅衰减的基于递归-RARE 的近场源三维参数估计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-06 DOI: 10.1016/j.sigpro.2024.109766

Xinkai Wu , Lu Wang , Hua Chen, Ye Tian, Minghong Zhu, Gang Wang

{"title":"Recursive-RARE-based three-dimensional parameter estimation of near-field source considering amplitude attenuation","authors":"Xinkai Wu , Lu Wang , Hua Chen, Ye Tian, Minghong Zhu, Gang Wang","doi":"10.1016/j.sigpro.2024.109766","DOIUrl":"10.1016/j.sigpro.2024.109766","url":null,"abstract":"<div><div>This paper addresses the issue for near-field (NF) localization considering amplitude attenuation, proposing a recursive rank-reduction (RARE) method for three-dimensional (3-D) parameter estimation of NF sources incident on a symmetrical cross array. The proposed method constructs several one-dimensional (1-D) spectral peak search estimators to obtain two-dimensional angle and range parameters. Initially, using the received data from symmetrical array elements in one axis, a 1-D spectral peak search estimator is constructed. The origins of two types of pseudo peaks within this estimator are analyzed, and then, corresponding pseudo peaks removal methods, namely the initial screening method and the recursive RARE method, are presented to obtain the estimate of the first angle parameter. Subsequently, the estimated results are fed into another 1-D spectral peak search estimator constructed from the original received data to obtain the range parameter. Finally, the same process is applied to the other axis to obtain the second angle and range parameters, followed by a parameter matching operation for 3-D parameters. Compared to existing NF source localization methods, the proposed method more effectively eliminates pseudo peaks, and demonstrates superior parameter estimation performance under conditions of small number of snapshots and low signal-to-noise ratio, as validated by several simulation results.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109766"},"PeriodicalIF":3.4,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing jamming and spoofing impacts on GNSS receivers: Automatic gain control (AGC) 评估干扰和欺骗对全球导航卫星系统接收器的影响：自动增益控制（AGC）

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-05 DOI: 10.1016/j.sigpro.2024.109762

Emile Ghizzo, El-Mehdi Djelloul, Julien Lesouple, Carl Milner, Christophe Macabiau

{"title":"Assessing jamming and spoofing impacts on GNSS receivers: Automatic gain control (AGC)","authors":"Emile Ghizzo, El-Mehdi Djelloul, Julien Lesouple, Carl Milner, Christophe Macabiau","doi":"10.1016/j.sigpro.2024.109762","DOIUrl":"10.1016/j.sigpro.2024.109762","url":null,"abstract":"<div><div>In modern GNSS receivers, the Automatic Gain Control (AGC) monitors the received signal level to optimize quantization and mitigate interference. This paper characterizes the jamming and spoofing impact on AGC and received signal. It first expresses the AGC gain as a function of the received signal level. Under nominal conditions, the AGC leverages the ergodic properties of the received signal to estimate its level over time. Two physical quantities, namely time-based power and signal distribution, are typically considered. However, in the presence of interference, these ergodic properties are no longer guaranteed, posing challenges in modeling the behavior of these quantities. This paper proposes a probabilistic framework for interpreting temporal estimation and computing time-based power and distribution in order to characterize AGC gain under jamming and spoofing. First, this study models the spoofing impact for both unique and multiple emitted spoofing signals as a function of the re-radiated noise power and the spoofing signals’ characteristics (e.g., number of emitted signals, amplitudes, modulation). Furthermore, it reveals the non-uniformity of the jamming chirp phase, which introduces distortions in power and signal distribution, consequently affecting AGC gain and demonstrates the convergence of the jamming signal toward a continuous wave signal at high frequencies.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109762"},"PeriodicalIF":3.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On compressive self-calibration with structural constraints via alternating minimization 通过交替最小化实现具有结构约束的压缩自校准

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-04 DOI: 10.1016/j.sigpro.2024.109757

Ziyi Wang, Heng Qiao

{"title":"On compressive self-calibration with structural constraints via alternating minimization","authors":"Ziyi Wang, Heng Qiao","doi":"10.1016/j.sigpro.2024.109757","DOIUrl":"10.1016/j.sigpro.2024.109757","url":null,"abstract":"<div><div>This paper considers the compressive bilinear self-calibration problem with explicit low-dimensional structural constraints. The celebrated proximal alternating linearized minimization (PALM) framework is adapted to simultaneously allow general sub-sampling schemes and structure-promoting regularizers. For the first time in literature, we refine the conditional convergence guarantees of PALM and show that the parameter commonly adopted to remove the scaling ambiguity as well as the structural penalties can ensure the unconditional convergence independent of strict assumptions on the statistical properties of the measurements, subspaces, number of snapshots, or initial iterates. In particular, we impose sparse and small total variation structures on the target signals and provide detailed numerical procedures for efficient computations. The extension to the complex-valued case is also made, and extensive numerical experiments are carried out to corroborate the theoretical claims. Different choices of sub-sampling schemes and compression rates are simulated to support the effectiveness of the proposed algorithm under various settings. We also make comparisons with the state-of-art competing methods, and the superiority of our proposed algorithm is empirically verified.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109757"},"PeriodicalIF":3.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancements and challenges in coverless image steganography: A survey 无掩码图像隐写术的进步与挑战：调查

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-04 DOI: 10.1016/j.sigpro.2024.109761

Xuyu Xiang, Yang Tan, Jiaohua Qin, Yun Tan

{"title":"Advancements and challenges in coverless image steganography: A survey","authors":"Xuyu Xiang, Yang Tan, Jiaohua Qin, Yun Tan","doi":"10.1016/j.sigpro.2024.109761","DOIUrl":"10.1016/j.sigpro.2024.109761","url":null,"abstract":"<div><div>Coverless image steganography has emerged as a significant research direction in the field of steganography in recent years. Unlike traditional image steganography, it does not require modifying the cover image to achieve information hiding. This review aims to systematically summarize the research progress and challenges in coverless image steganography. Firstly, the paper introduces the basic principles and classification methods of coverless image steganography, including embedding methods based on low-level image features and those combining advanced semantic features from deep learning. Secondly, it discusses key research achievements in this field, such as novel embedding algorithms, efficient extraction methods, and robustness enhancement techniques against various attacks. Additionally, the review highlights major challenges faced by current coverless image steganography, including difficulties in secret information extraction, capacity limitations, and practicality issues, and explores potential solutions and future research directions. Through comprehensive analysis of existing literature, the review aims to provide researchers with a holistic perspective, fostering further development and application of coverless image steganography. The paper includes 124 key contributions, offering a comprehensive overview of coverless image steganography, covering its fundamental principles, research progress, challenges, and solutions.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109761"},"PeriodicalIF":3.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-image reversible data hiding based on pixel value parity and multiple embedding strategy 基于像素值奇偶校验和多重嵌入策略的双图像可逆数据隐藏

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-04 DOI: 10.1016/j.sigpro.2024.109764

Hua Zhang , Zhenghong Peng , Fanli Meng

{"title":"Dual-image reversible data hiding based on pixel value parity and multiple embedding strategy","authors":"Hua Zhang , Zhenghong Peng , Fanli Meng","doi":"10.1016/j.sigpro.2024.109764","DOIUrl":"10.1016/j.sigpro.2024.109764","url":null,"abstract":"<div><div>Dual-image reversible data hiding (DI-RDH) has attracted a lot of attention for its excellent embedding capability. However, the stego image after data embedding is degraded, which limits its practical application. This paper proposes an innovative DI-RDH method based on pixel value parity (PVP), which prevents influences from the image texture features and ensures that the pixel value deviation between the temporary stego image and the original image is −1, 0, or 1, as it can partially offset the difference introduced when generating the cover image. Such characteristics enable us to establish a multiple embedding strategy (MES), which applies the difference image to embed the secret message, decreasing the number of invalid shifting pixels in the difference histogram to enhance embedding capacity and image quality. The average maximum embedding rate of our method combining PVP and two phases of MES is determined to be 1.37 bpp, corresponding to the theoretical results. The average peak signal-to-noise ratio of our method on the UCID database is increased by at least 2.19 dB for a given ER of 0.5 bpp compared with several state-of-the-art methods.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"228 ","pages":"Article 109764"},"PeriodicalIF":3.4,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved analytical solution with optimization constraints using TDOA and FDOA measurements for USV/AUV collaborative localization 利用 TDOA 和 FDOA 测量改进分析解决方案，为 USV/AUV 协同定位提供优化约束条件

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-03 DOI: 10.1016/j.sigpro.2024.109760

Huaxia Zhang , Huigang Wang , Juan Lei , Weina Zhao

引用次数: 0