Article
Engineering, Electrical & Electronic
Seung-Hun Nam, Wonhyuk Ahn, In-Jae Yu, Myung-Joon Kwon, Minseok Son, Heung-Kyu Lee
Summary: This paper proposes a CNN-based approach for classifying seam-carving forgery, with specialized network blocks designed to capture local artifacts caused by seam carving. Experimental results demonstrate that the method has good classification performance and robustness.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Kun Zeng, Jiangchuan Hu, Yongyi Gong, Kanoksak Wattanachote, Runpeng Yu, Xiaonan Luo
Summary: Two seam coupling strategies, real mapping and virtual mapping, were proposed for vertical retargeting to address the problems of multiple assignments and missing assignments. Experimental results demonstrated that the method overcomes the limitations of vertical retargeting and effectively preserves geometric consistency.
ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Cui Jia, Song Lei, Lu Hongju, Tang Mingxi, Qi Meng
Summary: Image retargeting technologies aim to preserve important information and reduce edge distortion. The JND algorithm is proposed to detect and pass distortion information to reduce retargeting distortions, offering promising results compared to other approaches at 'Retarget Me' database.
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
(2021)
Article
Computer Science, Software Engineering
Ankit Garg, Anuj Kumar Singh
Summary: This paper presents an improved technique for image retargeting, which uses the gradient energy map generation method to safeguard the prominent regions of the image. The efficiency of the technique is validated through objective and subjective image quality assessment.
Article
Computer Science, Software Engineering
Sean Flynn, David Hart, Bryan Morse, Seth Holladay, Parris Egbert
Summary: This paper introduces a novel method for intelligently resizing a wide range of volumetric data, including fluids, allowing for more versatile post-processing. Additionally, a faster seam computation method is presented to improve production workflow viability.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Information Systems
Hai Su, Zigui Ye, Yaping Liu, SongSen Yu
Summary: Seam carving algorithm is widely used for content-based image scaling. We propose a dynamic energy regulation method to improve the effect of seam carving by simulating the energy change in each carving. Our method adjusts the energy value of each pixel after each carving to simulate the extra energy introduced by carving.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Yuzhen Niu, Shuai Zhang, Zhishan Wu, Tiesong Zhao, Weiling Chen
Summary: In this paper, a new IRQA framework based on RCM and NBP is proposed, integrating registration confidence measurement, noticeability-based pooling, and visual attention fusion to evaluate the quality of retargeted images. Experimental results demonstrate that this metric outperforms the state-of-the-art approaches in assessing image retargeting quality.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Automation & Control Systems
Feng Shao, Zhenqi Fu, Qiuping Jiang, Gangyi Jiang, Yo-Sung Ho
Summary: This paper proposes a new method for assessing the quality of image retargeting by measuring geometric distortion and content loss to determine the retargeting quality. Experimental results show that the proposed method performs better on two databases.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Zehra Karapinar Senturk, Devrim Akgun
Summary: The paper introduces a new blind detection method based on seam carving for identifying retargeted images, which shows improved accuracies compared to traditional solutions through experiments.
ELEKTRONIKA IR ELEKTROTECHNIKA
(2021)
Article
Computer Science, Information Systems
Ankit Garg, Anand Nayyar, Anuj Kumar Singh
Summary: This paper proposes an improved seam carving technique to overcome the limitations of traditional techniques by restricting the intersection of optimal seam points on line structures. Through subjective and objective evaluations, the effectiveness and high similarity of the proposed technique have been demonstrated.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Jila Ayubi, Mehdi Chehel Amirani, Morteza Valizadeh
Summary: This paper introduces a new method based on information entropy to extract the importance map and proposes a new method for selecting the most optimal seam based on the calculation of the Lyapunov exponents. Through simulation on the MSRA and RetargetMe datasets, it is demonstrated that the proposed algorithm performs better than the classical seam-carving and generalized seam-carving algorithms.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Xuejin Wang, Feng Shao, Qiuping Jiang, Zhenqi Fu, Xiangchao Meng, Ke Gu, Yo-Sung Ho
Summary: This paper presents a new objective quality assessment method for retargeted stereopairs by combining image quality and depth perception measures. Experimental results demonstrate the superiority of this method.
IEEE TRANSACTIONS ON MULTIMEDIA
(2022)
Article
Engineering, Electrical & Electronic
Wanli Xue, Weilun Xie, Yao Zhang, Shengyong Chen
Summary: Parallax tolerance is a challenging issue in image stitching, and addressing spatial variations, seam cutting, and consistency of homographies is crucial. To tackle these challenges, a stable image stitching framework is proposed in this study, involving a uniform linear structure model and a stable hybrid actor-critic algorithm to reduce ghosting and preserve structure.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Ankit Garg, Anuj Kumar Singh
Summary: This paper introduces the seam diversion-based image retargeting (SDIR) algorithm and analyzes its performance through two experiments. Experiment 1 analyzes the impact of different edge detection operators on the algorithm, while Experiment 2 evaluates the performance based on the visual quality and quality of importance maps. The results show that the SDIR algorithm performs well in minimizing structural deformations on prominent objects.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Ya Zhou, Zhibo Chen, Weiping Li
Summary: This paper proposes a Hierarchical Visual Comfort Assessment (Hi-VCA) scheme for SIR, which considers hybrid distortions and incorporates valid Local-SSIM and Dual Natural Scene Statistics (D-NSS) features to measure structural distortion and information loss. Extensive experiments show that Hi-VCA outperforms state-of-the-art schemes in handling hybrid distortions.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2021)
Article
Engineering, Electrical & Electronic
Alam Abbas Syed, Hassan Foroosh
Summary: This paper presents effective methods using spherical polar Fourier transform data for two different applications: 3D volumetric registration and machine learning classification network. The proposed method for registration offers unique and effective techniques, handling arbitrary large rotation angles and showing robustness. The modified classification network achieves robust classification results in processing spherical data.
Article
Engineering, Electrical & Electronic
Ruibo Fan, Mingli Jing, Jingang Shi, Lan Li, Zizhao Wang
Summary: In this study, a new low-rank sparse decomposition algorithm named TVRPCA+ is proposed for foreground-background separation. The algorithm combines spectral norm, structured sparse norm, and total variation regularization to suppress noise and obtain cleaner foregrounds. Experimental results demonstrate that TVRPCA+ achieves high performance in complex backgrounds and noise scenarios.
Article
Engineering, Electrical & Electronic
Omair Aldimashki, Ahmet Serbes
Summary: This paper proposes a coarse-to-fine FrFT-based algorithm for chirp-rate estimation of multi-component LFM signals, which achieves improved performance and a reduced signal-to-noise breakdown threshold by utilizing mathematical models for coarse estimation and a refined estimate-and-subtract strategy. Extensive simulation results demonstrate that the proposed algorithm performs very close to the Cramer-Rao lower bound, with the advantages of eliminating leakage effect, avoiding error propagation, and maintaining acceptable computational cost compared to other state-of-the-art methods.
Article
Engineering, Electrical & Electronic
Xinlei Shi, Xiaofei Zhang, Yuxin Sun, Yang Qian, Jinke Cao
Summary: In this paper, a low-complexity localization approach for multiple sources using two-dimensional discrete Fourier transform (2D-DFT) is proposed. The method computes the cross-covariance and utilizes phase offset method and total least square solution to obtain accurate position estimates.
Article
Engineering, Electrical & Electronic
Prabhanjan Mannari, Ratnasingham Tharmarasa, Thiagalingam Kirubarajan
Summary: This paper discusses the problem of extended target tracking for a single 2D extended target with a known convex polytope shape and dynamics. It proposes a framework based on the existing point multitarget tracking framework to address the challenges of uncertainty in shape and kinematics, as well as self-occlusion. The algorithm developed using this framework is capable of dynamically changing the number of parameters used to describe the shape and estimating the whole target shape even when different parts of the target are visible at different frames.
Article
Engineering, Electrical & Electronic
Yongsong Li, Zhengzhou Li, Jie Li, Junchao Yang, Abubakar Siddique
Summary: This paper proposes a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The WARTH method effectively measures local and global feature information using an adaptive ring-shaped structural element and a target awareness indicator, resulting in accurate detection of small targets with minimized false alarms.
Article
Engineering, Electrical & Electronic
Yu Wang, Zhen Qin, Jun Tao, Yili Xia
Summary: In this paper, an enhanced sparsity-aware recursive least squares (RLS) algorithm is proposed, which combines the proportionate updating (PU) and zero-attracting (ZA) mechanisms, and introduces a general convex regularization (CR) function and variable step-size (VSS) technique to improve performance.
Article
Engineering, Electrical & Electronic
Neil J. Bershad, Jose C. M. Bermudez
Summary: This paper analyzes the impact of processing delay on the Least Mean Squares (LMS) algorithm in system identification, highlighting bias issues in the resulting weight vector.
Article
Engineering, Electrical & Electronic
Kanghui Jiang, Defu Jiang, Mingxing Fu, Yan Han, Song Wang, Chao Zhang, Jingyu Shi
Summary: In this paper, a novel method for velocity estimation using multicarrier signals in a single dwell is proposed, which effectively addresses the issue of Doppler ambiguity in pulse Doppler radars.
Article
Engineering, Electrical & Electronic
Xiao-Jun Zhang, Peng-Lang Shui, Yu-Fan Xue
Summary: This paper proposes a method for low-velocity small target detection in maritime surveillance radars. It models sea clutter sequences using the spherical invariant random vector (SIRV) model with block tridiagonal speckle covariance matrix and inverse Gamma distributed texture. The proposed detector, which is a long-time adaptive generalized likelihood ratio test with linear threshold detector (GLRT-LTD), shows competitive detection performance in experiments.
Article
Engineering, Electrical & Electronic
Aiyi Zhang, Fulai Liu, Ruiyan Du
Summary: This paper proposes an adaptive weighted robust data recovery method with total variation regularization for hyperspectral image. The method models the HSI recovery problem as a tensor robust principal component analysis optimization problem, decomposing the data into low-rank HSI data, outliers, and noise component. An adaptive weighted strategy is then defined to impose on the tensor nuclear norm and outliers, using the priori information of singular values and strengthening the sparsity of outliers.
Article
Engineering, Electrical & Electronic
Hamid Asadi, Babak Seyfe
Summary: This paper presents a novel approach for estimating the model order in the presence of observation errors. The proposed method is based on correntropy estimation of eigenvalues in the observation space, which is further enhanced by resampling the observations using the bootstrap method. The algorithm partitions the observation space into signal and noise subspaces using the covariance matrix of mixtures, and determines the model order based on a correntropy estimator with kernel functions. Theoretical analysis and comparative evaluations demonstrate the superiority of this information-theoretic approach.
Article
Engineering, Electrical & Electronic
Buket colak Guvenc, Engin Cemal Menguc
Summary: In this paper, a novel family of online censoring based complex-valued least mean kurtosis (CLMK) algorithms is proposed. The algorithms censor less informative complex-valued data streams and reduce the costs of data processing without affecting accuracy. Robust algorithms are also developed to handle outliers. The simulation results confirm the attractive features of the proposed algorithms in large-scale system identification and regression scenarios.
Article
Engineering, Electrical & Electronic
Yun Su, Weixian Tan, Yifan Dong, Wei Xu, Pingping Huang, Jianxin Zhang, Diankun Zhang
Summary: In this study, a novel method for detecting low-resolution and small targets in millimeter wave radar images is proposed. The Wavelet-Conv structure and Wavelet-Attention mechanism are introduced to overcome the limitations of existing detectors. Experimental results demonstrate that the proposed method improves recall and mean average precision while maintaining competitive inference speed.
Article
Engineering, Electrical & Electronic
Xin Wang, Xingxing Jiang, Qiuyu Song, Jie Liu, Jianfeng Guo, Zhongkui Zhu
Summary: This study proposes a variational mode extraction (VME) method for extracting specific modes from complicated signals. By exploring the convergence property of VME, strategies for identifying ICF and determining the balance parameter are designed, and a bandwidth estimation strategy is constructed. The effectiveness of the proposed method for bearings fault diagnosis is verified and compared with other methods.