Signal Processing最新文献_第10页

Extraction of patterns from images using a model of combined frequency localization spaces 使用组合频率定位空间模型从图像中提取模式

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-26 DOI: 10.1016/j.sigpro.2024.109810

Djordje Stanković , Cornel Ioana , Irena Orović

{"title":"Extraction of patterns from images using a model of combined frequency localization spaces","authors":"Djordje Stanković , Cornel Ioana , Irena Orović","doi":"10.1016/j.sigpro.2024.109810","DOIUrl":"10.1016/j.sigpro.2024.109810","url":null,"abstract":"<div><div>An algorithm for image decomposition and separation of superposed stationary contributions is proposed. It is based on the concept of sparse-to-sparse domain representation achieved through a relationship between block-based and full-size discrete cosine transform. The L-statistics is adapted to discard nonstationary components from the frequency domain vectors, leaving just a few coefficients associated with stationary pattern. These fewer stationary components are then used under the compressive sensing framework to reconstruct the stationary pattern. The original image is observed as a nonstationary component, acting as a non-desired part at this stage of the procedure, while the stationary pattern is observed as a “desired part” that should be extracted through the reconstruction process. The problem of interest is formulated as underdetermined system of equations resulting from a relationship between the two considered transformation spaces. Once the stationary pattern is reconstructed, it can be removed entirely from the image. Furthermore, it will be shown that the efficiency of pattern extraction cannot be affected, even when image contains additional nonstationary disturbance (here, the noisy image is observed as nonstationary undesired part). The proposed approach is motivated by challenges in removing Moiré-like patterns from images, enabling some interesting applications, including extraction of hidden sinusoidal signatures.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109810"},"PeriodicalIF":3.4,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758834","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

Last-seen time is critical: Revisiting RSSI-based WiFi indoor localization

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-26 DOI: 10.1016/j.sigpro.2024.109756

Shixiong Wan , Chaojie Gu , Yuanchao Shu , Zhiguo Shi

引用次数: 0

Game-theory-based complexity allocation for 360-degree video coding 基于博弈论的360度视频编码复杂度分配

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-23 DOI: 10.1016/j.sigpro.2024.109807

Jielian Lin , Kaiying Xing , Yiwen Xu

{"title":"Game-theory-based complexity allocation for 360-degree video coding","authors":"Jielian Lin , Kaiying Xing , Yiwen Xu","doi":"10.1016/j.sigpro.2024.109807","DOIUrl":"10.1016/j.sigpro.2024.109807","url":null,"abstract":"<div><div>360-degree video applications with immersive experiences have been well spread in our daily life. However, 360-degree video with high resolution (e.g., 8192<span><math><mrow><mspace></mspace><mo>×</mo><mspace></mspace><mn>4096</mn><mo>,</mo><mn>6144</mn><mspace></mspace><mo>×</mo></mrow></math></span> 3072, and 3840 × 1920) leads to high coding computational complexity. To further optimize the complexity allocation and obtain the optimal coding performance, this paper proposes a game-theory-based complexity allocation algorithm for 360-degree video coding. The proposed method first constructs the latitude-level complexity allocation model by introducing game theory. Second, the optimal Lagrange coefficient <span><math><msup><mrow><mi>λ</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span> value is obtained by the Newton method, and then, the complexity of the latitude can be further obtained. Finally, the overall complexity allocation algorithm is also designed. Experimental results indicate our method obtains Time Saving (TS) with 18.44%<span><math><mo>∼</mo></math></span>67.08% and BDBR performance with 0.10%<span><math><mo>∼</mo></math></span>3.11%. The proposed method also achieves the optimal Coding Gain (CG) values for the most global target complexity.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109807"},"PeriodicalIF":3.4,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744535","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

FTAN: Feature Transform and Alignment Network for cross-domain specific emitter identification 跨域特定发射极识别的特征变换与对准网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109800

Zhiling Xiao, Xiang Zhang, Guomin Sun, Huaizong Shao

引用次数: 0

RIS-assisted differential transmitted spatial modulation design ris辅助差分传输空间调制设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109767

Chaorong Zhang, Yuyan Liu, Benjamin K. Ng, Chan-Tong Lam

{"title":"RIS-assisted differential transmitted spatial modulation design","authors":"Chaorong Zhang, Yuyan Liu, Benjamin K. Ng, Chan-Tong Lam","doi":"10.1016/j.sigpro.2024.109767","DOIUrl":"10.1016/j.sigpro.2024.109767","url":null,"abstract":"<div><div>In this paper, we propose a novel reconfigurable intelligent surface (RIS)-assisted wireless communication design called the RIS-assisted differential transmitted spatial modulation (DTSM) scheme. The encoding process of the differential spatial modulation (DSM) is integrated into the DTSM scheme, where only one transmit antenna is activated per time slot to transmit the <span><math><mi>M</mi></math></span>-ary phase shift keying (PSK) modulation symbol through the RIS. Due to the detection characteristics of DSM, the bit error rate (BER) performance remains satisfactory without requiring channel state information estimation, thereby enhancing robustness. The RIS application in the proposed scheme mitigates the effects of shadow area fading by adjusting the phase of the reflected signals to improve the signal-to-noise ratio at the receiver. In simulation results by comparing to other RIS-assisted spatial modulation schemes, we can find that the proposed DTSM scheme demonstrates good BER performance across various scenarios, including Nakagami-<span><math><mi>m</mi></math></span> fading, which also indicates its potential for practical applications.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109767"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744533","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

Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems 机载PLC中脉冲噪声的抑制：介绍MIMO OFDM系统中的S-SAMP-PV算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109798

Ruowen Yan, Qiao Li, Huagang Xiong

{"title":"Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems","authors":"Ruowen Yan, Qiao Li, Huagang Xiong","doi":"10.1016/j.sigpro.2024.109798","DOIUrl":"10.1016/j.sigpro.2024.109798","url":null,"abstract":"<div><div>Power Line Communication (PLC) offers an efficient solution for data transmission over electrical power lines, presenting a promising avenue for in-flight communication in More Electrical Aircraft (MEA). A significant challenge in airborne PLC is Impulsive Noise (IN), which hampers transmission reliability. Existing noise mitigation methods, while valuable, face limitations in airborne settings due to computational intensiveness and sub-optimal sparse recovery performance. This paper introduces the Structured Sparsity Adaptive Matching Pursuit with Preliminary partial support estimation and Variable step-size (S-SAMP-PV) algorithm, devised for Multiple-Input-Multiple-Output (MIMO) systems. It uniquely pre-estimates partial support of sparse IN signals, enabling adaptive convergence without prior sparsity knowledge. This methodology substantially reduces computational demands, satisfying stringent real-time requirements of airborne applications. In simulation, the S-SAMP-PV algorithm exhibits marked advantages over traditional algorithms such as Orthogonal Matching Pursuit (OMP). Specifically, it realizes an approximate 81.3<span><math><mtext>%</mtext></math></span> reduction in Normalized Mean Square Error (NMSE) and demonstrates around 37<span><math><mtext>%</mtext></math></span> improvement in computational efficiency relative to OMP. Moreover, its Bit Error Rate (BER) performance at high Signal to Noise Ratio (SNR) approaches the ideal scenario where IN is assumed to be perfectly eliminated. These results emphasize the promise of S-SAMP-PV in elevating the performance of airborne PLC systems by efficient IN mitigation.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109798"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756675","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

Tensor singular value decomposition and low-rank representation for hyperspectral image unmixing 高光谱图像解混的张量奇异值分解与低秩表示

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109799

Zi-Yue Zhu , Ting-Zhu Huang , Jie Huang , Ling Wu

{"title":"Tensor singular value decomposition and low-rank representation for hyperspectral image unmixing","authors":"Zi-Yue Zhu , Ting-Zhu Huang , Jie Huang , Ling Wu","doi":"10.1016/j.sigpro.2024.109799","DOIUrl":"10.1016/j.sigpro.2024.109799","url":null,"abstract":"<div><div>Hyperspectral unmixing (HU) finds pure spectra (endmembers) and their proportions (abundances) in hyperspectral images (HSIs). The matrix–vector non-negative tensor factorization (MV-NTF) describes the HSI as the sum of the outer products of the endmembers and their corresponding abundance maps. Concatenating these abundance maps in the third dimension is precisely the abundance tensor. Many subsequent studies have focused on exploiting different priors to improve the accuracy of MV-NTF. Most of them, however, explore the properties of abundance matrices or abundance maps, which is hard to fully utilize the structural similarity in abundance tensors corresponding to HSIs containing mixed materials. In this paper, we use the tensor singular value decomposition (T-SVD) to directly exploit the structural information in the abundance tensor. For this purpose, we propose a new low-rank representation by dividing the abundance tensor into a main feature tensor and a disturbance term. We characterize the low-rank property of the feature tensor after performing T-SVD and characterize the sparsity of the disturbance term. In this vein, we establish a model named abundance low-rank structure based on T-SVD (ALRSTD) and propose the solution algorithm. Experiments show that ALRSTD has better unmixing effect compared with several state-of-the-art methods, especially in the abundance estimation and the computation speed.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109799"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744530","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

PIPO-Net: A Penalty-based Independent Parameters Optimization deep unfolding Network PIPO-Net：基于惩罚的独立参数优化深度展开网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109796

Xiumei Li , Zhijie Zhang , Huang Bai , Ljubiša Stanković , Junpeng Hao , Junmei Sun

{"title":"PIPO-Net: A Penalty-based Independent Parameters Optimization deep unfolding Network","authors":"Xiumei Li , Zhijie Zhang , Huang Bai , Ljubiša Stanković , Junpeng Hao , Junmei Sun","doi":"10.1016/j.sigpro.2024.109796","DOIUrl":"10.1016/j.sigpro.2024.109796","url":null,"abstract":"<div><div>Compressive sensing (CS) has been widely applied in signal and image processing fields. Traditional CS reconstruction algorithms have a complete theoretical foundation but suffer from the high computational complexity, while fashionable deep network-based methods can achieve high-accuracy reconstruction of CS but are short of interpretability. These facts motivate us to develop a deep unfolding network named the penalty-based independent parameters optimization network (PIPO-Net) to combine the merits of the above mentioned two kinds of CS methods. Each module of PIPO-Net can be viewed separately as an optimization problem with respective penalty function. The main characteristic of PIPO-Net is that, in each round of training, the learnable parameters in one module are updated independently from those of other modules. This makes the network more flexible to find the optimal solutions of the corresponding problems. Moreover, the mean-subtraction sampling and the high-frequency complementary blocks are developed to improve the performance of PIPO-Net. Experiments on reconstructing CS images demonstrate the effectiveness of the proposed PIPO-Net.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109796"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706978","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

Proximal gradient algorithm with dual momentum for robust compressive sensing MRI 鲁棒压缩感知MRI的双动量近端梯度算法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109817

Zhonghua Xie , Lingjun Liu , Zehong Chen , Cheng Wang

{"title":"Proximal gradient algorithm with dual momentum for robust compressive sensing MRI","authors":"Zhonghua Xie , Lingjun Liu , Zehong Chen , Cheng Wang","doi":"10.1016/j.sigpro.2024.109817","DOIUrl":"10.1016/j.sigpro.2024.109817","url":null,"abstract":"<div><div>Adopting the new signal acquisition technology Compressive Sensing (CS) to Magnetic Resonance Imaging (MRI) reconstruction has been proved to be an effective scheme for reconstruction of high-resolution images with only a small fraction of data, thus making it the key to design a reconstruction algorithm with excellent performance. To achieve accelerated and robust CS-MRI reconstruction, a novel combination of Proximal Gradient (PG) and two types of momentum is developed. Firstly, to accelerate convergence of the PG iteration, we introduce the classical momentum method to solve the data-fitting subproblem for fast gradient search. Secondly, inspired by accelerated gradient strategies for convex optimizations, we further modify the obtained PG algorithm with the Nesterov's momentum technique to solve the prior subproblem, boosting its performance. We demonstrate the effectiveness and flexibility of the proposed method by combining it with two categories of prior models including a weighted nuclear norm regularization and a deep CNN (Convolutional Neural Network) prior model. As such, we obtain a dual momentum-based PG method, which can be equipped with any denoising engine. It is shown that the momentum-based PG method is closely related to the well-known Approximate Message Passing (AMP) algorithm. Experiments validate the effectiveness of leveraging dual momentum to accelerate the algorithm and demonstrate the superior performance of the proposed method both quantitatively and visually as compared with the existing methods.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109817"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758832","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

An interference power allocation method against multi-objective radars based on optimized proximal policy optimization 基于优化近端策略的多目标雷达干扰功率分配方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-21 DOI: 10.1016/j.sigpro.2024.109785

Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu

{"title":"An interference power allocation method against multi-objective radars based on optimized proximal policy optimization","authors":"Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu","doi":"10.1016/j.sigpro.2024.109785","DOIUrl":"10.1016/j.sigpro.2024.109785","url":null,"abstract":"<div><div>Aiming at the problem of interference resource scheduling in cognitive electronic warfare, a multi-objective interference power allocation method based on the proximal policy optimization (PPO) framework is proposed in this paper. Firstly, the confrontation between jammers and multi-objective radar networks is mapped as the interaction between the agent and the environment, and the radar target detection model under suppression interference is established. On this basis, an interference power allocation model against multi-objective radars based on PPO framework is constructed. Moreover, a reward normalization mechanism is introduced to optimize the reward setting, and an interference power allocation method based on optimized PPO is proposed. Meanwhile, this paper constructs a confrontation scenario in which the jammer covers the target aircraft to break through the multi-objective radar network. Simulation experiments are conducted based on this scenario to verify the effectiveness of the method proposed in this paper. The interference power allocation method proposed in this paper can intelligently adjust the power allocation scheme of the jammer according to the electromagnetic situation on the battlefield, optimize the resource utilization of the jammer, and occupy the initiative on the battlefield.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109785"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697674","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