Article
Computer Science, Artificial Intelligence
Ugur Kadak
Summary: The paper introduced a novel family of multivariate fuzzy neural network interpolation operators activated by sigmoidal functions belonging to the new class of multivariate sigmoidal functions. An alternative method to the well-known shortcomings of the Hukuhara difference was presented by using a proper function defined on a set of fuzzy-cell numbers. Various special examples for the class of multivariate sigmoidal functions were presented, along with illustrative examples demonstrating the approximation performances of all operators. Additionally, a novel interpolation algorithm involving a multidimensional fuzzy inference system with applications in color image resizing and inpainting was proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Sadegh Fadaei, Abdolreza Rashno
Summary: This paper presents a hexagonal platform based on interpolation to address challenges in hexagonal image processing, achieving the best performance in synthetic images and outperforming existing hexagonal lattice methods in real images.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Construction & Building Technology
Min-Yuan Cheng, Riqi Radian Khasani, Kent Setiono
Summary: This study proposes a novel HybridGAN that combines ESRGAN and DeblurGANv2 to improve the resolution and blurriness of dynamically acquired railway inspection images. Experimental results show that HybridGAN consistently improves mAP scores across multiple resolution levels and performs significantly better on low-quality dataset.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Muhammad Ismail, Changjing Shang, Jing Yang, Qiang Shen
Summary: This article proposes a sparse data-based approach for image super-resolution using ANFIS interpolation. By splitting the training dataset into sufficient and sparse subsets, different techniques are applied accordingly. The experimental evaluation shows positive results for the proposed method.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Wang Shen, Ming Cheng, Guo Lu, Guangtao Zhai, Li Chen, M. Salman Asif, Zhiyong Gao
Summary: This paper discusses the challenges of high-speed video acquisition under poor illumination conditions and proposes a camera system using alternating exposures. The system reconstructs high-quality frames using restoration and interpolation modules, and improves imaging quality through optimization of spatial and temporal enhancement methods. Experimental results demonstrate the excellent performance of this method on both synthetic and real-world data.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Materials Science, Multidisciplinary
Sung In Cho, Suk-Ju Kang
Summary: This paper introduces a new dictionary-based interpolation technique to enhance text quality when increasing image resolution. By analyzing and extracting text shapes, encoding and decoding text patterns, and utilizing a pre-trained code dictionary, the proposed method significantly improves text sharpness. Experimental results show that the algorithm outperformed benchmark methods for all test images, reducing the blur index by up to 0.112.
JOURNAL OF INFORMATION DISPLAY
(2021)
Article
Computer Science, Information Systems
Sedighe Mirbolouk, Morteza Valizadeh, Mehdi Chehel Amirani, Mohammad Amin Choukali
Summary: The paper introduces an efficient contrast enhancement approach based on a histogram weighting method using a fuzzy system. It is capable of enhancing image contrast while preserving details by dividing the original image histogram into sub-histograms through fuzzy clustering and weighting them with a Mamdani fuzzy inference system.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yang Zhao, Yanbo Ma, Yuan Chen, Wei Jia, Ronggang Wang, Xiaoping Liu
Summary: This paper proposes a multiframe deinterlacing network joint enhancement network for early interlaced videos. The proposed method effectively removes artifacts in early videos and achieves high-quality reconstruction.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Multidisciplinary Sciences
Abdelsalam Hamdi, Yee Kit Chan, Voon Chet Koo
Summary: License Plate Recognition (LPR) is an important application of Artificial Intelligence (AI) and deep learning. A new deep learning architecture called D_GAN_ESR is proposed to enhance license plate images and improve LPR accuracy.
Article
Computer Science, Artificial Intelligence
Linh Anh Nguyen, Dat Xuan Tran
Summary: This article presents an efficient algorithm for computing the greatest fuzzy bisimulation between two finite fuzzy interpretations in fuzzy description logic fALC, with a complexity of O((m+n)n) under Godel semantics. The algorithm has been adapted to deal with fuzzy finite automata and other fuzzy description logics, reducing the complexity from O(n^5) to O((m+n)n) and improving efficiency.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jorg Sander, Bob D. de Vos, Ivana Isgum
Summary: This paper proposes an unsupervised deep learning semantic interpolation approach for synthesizing high-resolution medical images from low-resolution examples. The method utilizes the latent space generated by autoencoders and employs convex combination to achieve semantically smooth interpolation. Evaluation on multiple medical image datasets shows that the proposed method outperforms traditional methods in terms of structural similarity and peak signal-to-noise ratio.
MEDICAL IMAGE ANALYSIS
(2022)
Article
Computer Science, Artificial Intelligence
Kejie Lyu, Sicheng Pan, Yingming Li, Zhongfei Zhang
Summary: In this paper, a new Joint Image Super-resolution and Enhancement Network (JSENet) is proposed, which is the first end-to-end method based on deep learning for joint SR and IE. JSENet seamlessly integrates the two tasks together using a bilateral learning framework, and two lightweight modules are designed for restoring details and generating color transformation coefficients respectively, improving the algorithm's deployability in real-world applications.
Article
Engineering, Electrical & Electronic
Zheng Fang, Changshuo Liang, Shuwan Xu, Qing Bai, Yu Wang, Hongjuan Zhang, Baoquan Jin
Summary: In this study, a phase-domain-interpolation-based resampling method is proposed to address the problem of degraded spatial resolution in the optical frequency domain reflectometry (OFDR) system caused by nonlinearity in the lightwave-frequency sweep. The method utilizes coordinate transformation and phase interpolation to enhance the spatial resolution by compensating for nonlinearity. Experimental results demonstrate a significant improvement in spatial resolution using the proposed method.
IEEE SENSORS JOURNAL
(2022)
Article
Computer Science, Information Systems
Amanjot Singh, Jagroop Singh
Summary: This paper presents a new method for image upscaling and de-blocking of compressed images. The proposed technique in the spatial domain is practical and realistic, showing promising results in comparison to other interpolation methods.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Yanming Ye, Mengxiong Zhou, Zhanyu Wang, Xingfa Shen
Summary: This paper proposes a divide-and-conquer strategy to synthesize a high-resolution depth image from a low-resolution range image under the guidance of a registered high-resolution color image. Different interpolation methods are used for planar areas and edge regions, and the upsampling results are refined using a Depth CNN. Experimental results demonstrate that our method achieves the best quality with fewer artifacts compared to classical super-resolution algorithms, and our depth CNN outperforms state-of-the-art methods in qualitative and quantitative evaluations.
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.
