Signal Processing最新文献

Focus-aware compression and image quality metric for 3D displays 三维显示器的焦点感知压缩和图像质量度量

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-22 DOI: 10.1016/j.sigpro.2025.110091

T. Chlubna , M. Vlnas , D. Bařina , T. Milet , P. Zemčík

{"title":"Focus-aware compression and image quality metric for 3D displays","authors":"T. Chlubna , M. Vlnas , D. Bařina , T. Milet , P. Zemčík","doi":"10.1016/j.sigpro.2025.110091","DOIUrl":"10.1016/j.sigpro.2025.110091","url":null,"abstract":"<div><div>3D displays are capable of immersive 3D content presentation without glasses and headsets. The displays project different views depending on the user’s viewing angle. Multiple views are visible to the user at once to simulate the 3D perception. The visual blending of the simultaneously projected views creates out-of-focus areas in the scene. The scene can be displayed with only one focusing distance, where the objects appear sharp. This paper utilizes this effect in data compression. First, several metrics are proposed for automatic visual quality assessment of the results on the 3D display. Then, automatic detection of the focusing distance in the scene, based on the input views, is proposed. Based on this detection, the high spatial frequencies in out-of-focus areas can be eliminated using the depth-of-field effect, or such areas can be compressed with higher compression ratio, depending on the use case. The paper compares the proposals. A user study is conducted to obtain human evaluation of the results. The results obtained identified the optimal visual quality metric for the 3D display. The proposed compression proved to be beneficial for 3D displays and capable of reaching a higher compression ratio than standard methods without a perceivable quality loss.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110091"},"PeriodicalIF":3.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131058","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

Few-shot jamming recognition based on NMF combined with multi-dimensional fusion network 基于NMF与多维融合网络相结合的小弹干扰识别

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-21 DOI: 10.1016/j.sigpro.2025.110089

Jiachen Li , Jiaxian Hao , Yukai Kong , Xianxiang Yu , Zhaoyin Xiang , Guolong Cui , Wenmin Wang

引用次数: 0

Optimized sparse 2D antenna array design via beampattern matching 基于波束匹配的二维稀疏天线阵优化设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-21 DOI: 10.1016/j.sigpro.2025.110086

Saeid Sedighi , Nazila Karimian-Sichani , Bhavani Shankar M.R. , Maria S. Greco , Fulvio Gini , Björn Ottersten

{"title":"Optimized sparse 2D antenna array design via beampattern matching","authors":"Saeid Sedighi , Nazila Karimian-Sichani , Bhavani Shankar M.R. , Maria S. Greco , Fulvio Gini , Björn Ottersten","doi":"10.1016/j.sigpro.2025.110086","DOIUrl":"10.1016/j.sigpro.2025.110086","url":null,"abstract":"<div><div>Emerging millimeter-wave (mmWave) MIMO radars combine the benefits of large bandwidth available at mmWave frequencies with the spatial diversity provided by MIMO architectures, significantly enhancing radar capabilities for automotive, surveillance, and imaging applications. However, deploying large numbers of antennas and transceivers at these high frequencies substantially increases chip complexity and hardware costs. In this paper, we address the design of sparse two-dimensional (2D) antenna arrays that retain the desirable beampattern characteristics of fully populated arrays – namely, narrow mainlobes and low sidelobes – while significantly reducing the required number of antenna elements. We formulate the sparse array design problem as a beampattern matching optimization, which selects optimal subsets of transmit and receive antenna positions from an initial dense grid. To efficiently solve this challenging nonconvex optimization problem, we introduce an iterative algorithm combining Majorization–Minimization (MM) and Alternating Optimization (AO) techniques. We provide theoretical guarantees for convergence to at least a local optimum. Additionally, we propose a weighting vector optimization step to further enhance sidelobe suppression. Numerical simulations confirm that the proposed method maintains angular resolution and Sidelobe Levels (SLLs) comparable to those of full arrays, while substantially reducing hardware complexity and cost. Performance comparisons against existing methods demonstrate notable improvements in sidelobe suppression and computational efficiency without compromising processing gain.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110086"},"PeriodicalIF":3.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131057","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

Optimal transport-guided multivariable model for point set matching problems 点集匹配问题的最优运输导向多变量模型

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-21 DOI: 10.1016/j.sigpro.2025.110090

Litao Ma, Xu Wang, Jiqiang Chen

{"title":"Optimal transport-guided multivariable model for point set matching problems","authors":"Litao Ma, Xu Wang, Jiqiang Chen","doi":"10.1016/j.sigpro.2025.110090","DOIUrl":"10.1016/j.sigpro.2025.110090","url":null,"abstract":"<div><div>With the rapid development of computer vision, the demand for point set matching in complex environments is increasing, especially in cases with large-scale deformation and high noise. However, existing algorithms often exhibit low accuracy or high computational costs. To enhance algorithmic efficiency while maintaining precision, we propose a new point sets matching method named multivariable entropic-regularized optimal transport model (MeROT), which handles the point sets more flexibly. Compared with the traditional optimal transport model, the proposed model introduces an orthogonal transformation matrix and a stretching transformation matrix, which can better handle the rotation and stretch transformation of the point set. In addition, an entropic-regularization term is incorporated to enhance the model’s robustness against noise and to decrease the computational expense. Subsequently, an alternate iteration algorithm is proposed. Thanks to the special properties of the two matrices and the entropy regularization term, each subproblem within the algorithm can be resolved either through a closed-form solution or by employing an efficient computational method. Therefore, MeROT offers both high matching accuracy and computational efficiency, making it well-suited for point cloud matching problems in the current complex environment. Finally, several experiments on 3D point sets are designed to show the efficiency of the proposed model.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110090"},"PeriodicalIF":3.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147343","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 decorrelation method in asynchronous arithmetic average fusion of GM-PHD filters GM-PHD滤波器异步算术平均融合中的去相关方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-20 DOI: 10.1016/j.sigpro.2025.110119

Xue Yu, Feng Xi-an

引用次数: 0

Adaptive GLMB filter with IoU-based birth modeling for UAV visual multi-object tracking 基于iou出生建模的自适应GLMB滤波器用于无人机视觉多目标跟踪

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-17 DOI: 10.1016/j.sigpro.2025.110087

Haiyi Tong, Dekang Zhu, Hongbo Guo, Zhou Zhang

{"title":"Adaptive GLMB filter with IoU-based birth modeling for UAV visual multi-object tracking","authors":"Haiyi Tong, Dekang Zhu, Hongbo Guo, Zhou Zhang","doi":"10.1016/j.sigpro.2025.110087","DOIUrl":"10.1016/j.sigpro.2025.110087","url":null,"abstract":"<div><div>This paper proposes an Intersection-over-Union-based Adaptive Birth Generalized Labeled Multi-Bernoulli (IoU-AB-GLMB) filter for UAV-based multi-object tracking (MOT), specifically designed to address challenges posed by small objects with indistinct appearance features and time-varying object numbers. The proposed method introduces an IoU-based adaptive birth probability estimation model, where detected bounding boxes are clustered using IoU metrics to analyze spatial relationships, allowing the identification of unassociated or weakly associated measurements as birth targets. Additionally, we also enhance the Gibbs sampling truncation strategy by incorporating hypothesis weights and target count constraints, enabling adaptive truncation to improve computational efficiency while maintaining critical track hypotheses. Built on the GLMB framework, our proposed filter provides a unified probabilistic model that handles detection uncertainty, target survival, birth, and disappearance through Bayesian recursion, eliminating the need for manually defined rules. Furthermore, instead of committing to a single optimal association, the GLMB filter retains multiple association hypotheses at each iteration, allowing for a more robust treatment of uncertainty. Experimental results show that IoU-AB-GLMB achieves MOT accuracy 41.29% and 39.07% on VisDrone and UAVDT. Despite not relying on appearance cues, our method performs comparably to state-of-the-art appearance-based trackers StrongSORT (43.06% on VisDrone; 27.93% on UAVDT). These results underscore the effectiveness of our algorithm in UAV tracking scenarios.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110087"},"PeriodicalIF":3.4,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089887","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

Spectrally compatible waveform design with low correlation sidelobe for MIMO radar under time-varying spectral environment 时变频谱环境下MIMO雷达低相关旁瓣频谱兼容波形设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-15 DOI: 10.1016/j.sigpro.2025.110109

Zhaobo Jia , Lei Yu , Yinsheng Wei

{"title":"Spectrally compatible waveform design with low correlation sidelobe for MIMO radar under time-varying spectral environment","authors":"Zhaobo Jia , Lei Yu , Yinsheng Wei","doi":"10.1016/j.sigpro.2025.110109","DOIUrl":"10.1016/j.sigpro.2025.110109","url":null,"abstract":"<div><div>Modern radar operates in a spectral environment with intense and time-varying interference, which significantly affects the radar performance. To address this problem, we adopt the pulse group diversity pulse intra-coding waveform and propose the average autocorrelation integrated sidelobe level (AISL) to measure the comprehensive autocorrelation performance within a coherent processing interval. Furthermore, the weighted objective function of AISL and cross-integrated sidelobe level is established. Additionally, the spectral and constant modulus constraints are utilized to formulate the optimization problem. To solve this NP-hard problem, we transform the original problem into several easy-to-solve sub-problems based on the alternating direction method of multipliers framework. Then we use the conjugate gradient method to solve the sub-problems. We also provide a weighted value selection approach tailored to different radar performance requirements. Simulation experiments are provided to demonstrate that the proposed algorithm can accurately select appropriate weighted values under diverse conditions. Moreover, the proposed algorithm outperforms the existing algorithms in terms of sidelobe performance and execution efficiency.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110109"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147342","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

SSPWave: Integrated signal subspace projection wavelet-inspired network for HRRP denoising and recognition 基于集成信号子空间投影小波的HRRP去噪与识别

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-15 DOI: 10.1016/j.sigpro.2025.110110

Ting Chen, Shuai Guo, Penghui Wang, Yinghua Wang, Junkun Yan, Hongwei Liu

{"title":"SSPWave: Integrated signal subspace projection wavelet-inspired network for HRRP denoising and recognition","authors":"Ting Chen, Shuai Guo, Penghui Wang, Yinghua Wang, Junkun Yan, Hongwei Liu","doi":"10.1016/j.sigpro.2025.110110","DOIUrl":"10.1016/j.sigpro.2025.110110","url":null,"abstract":"<div><div>Identifying non-cooperative targets based on HRRP is a critical and challenging task. To enhance HRRP recognition performance in harsh environments characterized by low signal-to-noise ratios (SNR), we innovatively proposed a noise-robust model that combines domain knowledge and time-frequency multi-resolution analysis, namely integrated signal subspace projection wavelet-inspired network (SSPWave). It cascades a fine-grained deep denoising model and a general recognition model. First, we attempt to integrate discrete wavelet transform (DWT) into the deep denoising model, systematically removing the high-frequency components corresponding to the noise layer by layer, while retaining the low-frequency components containing the main structure of the target on down-sampling process. Second, to reconstruct the high-frequency details required during up-sampling, we propose a signal subspace projection (SSP) module. Notably, SSP introduces the estimated SNR as prior, and facilitates waveform preservation through adaptive subspace projection. SSPWave achieves a balance between noise suppression and detail preservation with SNR-guided, demonstrating the flexibility and effectiveness in addressing various noise levels of HRRPs. We evaluated the model on two measured HRRP datasets, which exhibited advanced recognition robustness on several evaluation metrics. Most importantly, domain knowledge assistance and time-frequency multi-resolution analysis are validated as effective strategies for HRRP denoising and recognition tasks.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"238 ","pages":"Article 110110"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131059","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

WaveGRU-Net: Robust non-contact ECG reconstruction via MIMO millimeter-wave radar and multi-scale semantic analysis WaveGRU-Net：基于MIMO毫米波雷达和多尺度语义分析的鲁棒非接触心电重建

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-15 DOI: 10.1016/j.sigpro.2025.110108

Dan Xu , Yiming Xu , Kaijie Xu , Ze Hu , Mengdao Xing , Fulvio Gini , Maria Sabrina Greco

{"title":"WaveGRU-Net: Robust non-contact ECG reconstruction via MIMO millimeter-wave radar and multi-scale semantic analysis","authors":"Dan Xu , Yiming Xu , Kaijie Xu , Ze Hu , Mengdao Xing , Fulvio Gini , Maria Sabrina Greco","doi":"10.1016/j.sigpro.2025.110108","DOIUrl":"10.1016/j.sigpro.2025.110108","url":null,"abstract":"<div><div>With the rising demand for telemedicine, non-contact heart beating monitoring has attracted significant interest due to its non-invasive and patient-friendly attributes. However, conventional approaches are typically limited to detecting the peaks of the Electrocardiogram (ECG), making the accurate extraction of ECG intervals challenging. This paper proposed a novel method for non-contact ECG signal reconstruction utilizing multiple-input-multiple-output millimeter-wave radar, enabling precise reconstruction of comprehensive ECG features and capturing nuanced variations in cardiac activity. First, Two-Dimensional beamforming is employed to enhance the radar signal of interest. The echo inevitably contains interference from random body movements and chest displacements caused by respiration. The interference from random body movements can be effectively suppressed by using a cumulative energy spectrum analysis. Next, the phase information representing the combined respiratory and cardiac micro-movements is extracted. Then, the phase is inputted into the WaveGRU-Net model, which is an advanced neural network based on the Convolutional Neural Network-Long Short-Term Memory architecture, to reconstruct heartbeat signals and ECG waveforms. The proposed method successfully separates respiratory and cardiac signals in the time-frequency domain, yielding a refined ECG reconstruction enriched with detailed semantic features that encapsulate subtle cardiac dynamics. Experimental results demonstrate the proposed method has strong semantic representation capabilities.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110108"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099520","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

OMLK-Net: An Online Multi-scale Large Separable Kernel Distillation Network for efficient image super-resolution OMLK-Net：一种用于图像超分辨率的在线多尺度大可分离核蒸馏网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2025-05-14 DOI: 10.1016/j.sigpro.2025.110078

Hanjia Wei, Weiwei Wang, Xixi Jia, Xiangchu Feng, Chuan Chen

{"title":"OMLK-Net: An Online Multi-scale Large Separable Kernel Distillation Network for efficient image super-resolution","authors":"Hanjia Wei, Weiwei Wang, Xixi Jia, Xiangchu Feng, Chuan Chen","doi":"10.1016/j.sigpro.2025.110078","DOIUrl":"10.1016/j.sigpro.2025.110078","url":null,"abstract":"<div><div>Single-image super-resolution (SISR) has seen remarkable progress in recent years, driven by the powerful learning capabilities of large-scale neural networks, such as deep CNNs and Transformers. However, these advances come at the expense of substantial computational costs. Striking a delicate balance between effectiveness and efficiency remains a key challenge in neural network design. This paper proposes OMLK-Net, a novel lightweight architecture for SISR, offering the dual advantages of computational efficiency and high effectiveness. OMLK-Net adopts a divide-and-conquer strategy to separately optimize local and nonlocal feature learning, enabling a lightweight architecture without compromising feature representation effectiveness. Specifically, our OMLK-Net comprises two key modules: an Online Multiscale Distillation Block (OMDB) and Large Separable Shifting Kernel Attention (L2SKA) blocks. The OMDB module aims to explore multiscale local contextual information with a customized lightweight network block; while the L2SKA aims to harness nonlocal features by using computationally efficient large separable shifting kernels. By virtue of its carefully designed local and nonlocal feature extraction operators, OMLK-Net effectively addresses SISR challenges while maintaining low computational complexity. Extensive experimental results on benchmark datasets demonstrate that OMLK-Net achieves a better trade-off against state-of-the-art methods in terms of performance and model complexity. Codes will be available soon.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"237 ","pages":"Article 110078"},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069101","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