A DSP-based blind deconvolution algorithm for motion image restoration
Sign Up to like & getrecommendations! Published in 2018 at "Cluster Computing"
DOI: 10.1007/s10586-018-1881-0
Abstract: In the process of image shooting, image stabilization is an inevitable problem. Therefore, this paper finds an efficient and simple image stabilization algorithm in image stabilization. Using a new image regularization method to reduce the… read more here.
Keywords: image; image stabilization; based blind; dsp based ... See more keywords
Sparsity maximization nonlinear blind deconvolution and its application in identification of satellite microvibration sources
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Mechanical Science and Technology"
DOI: 10.1007/s12206-019-1206-0
Abstract: In this study, sparsity maximization nonlinear blind deconvolution (NBD) is proposed to identify the vibration sources of satellite systems from mixed vibration signals. The proposed algorithm decomposes NBD into two independent stages, namely, nonlinear compensation… read more here.
Keywords: sparsity maximization; maximization nonlinear; blind deconvolution; deconvolution ... See more keywords
Blind deconvolution based equalizer for underwater acoustic communications
Sign Up to like & getrecommendations! Published in 2019 at "Applied Acoustics"
DOI: 10.1016/j.apacoust.2019.01.022
Abstract: Abstract Reliable and efficient underwater acoustic communications are challenging problems because of complex underwater channel properties. With the recent advancements in underwater technologies, there is a need for a robust underwater communication system which can… read more here.
Keywords: acoustic communications; underwater acoustic; blind deconvolution; deconvolution based ... See more keywords
Adaptive blind deconvolution using generalized cross-validation with generalized lp/lq norm regularization
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.02.091
Abstract: Abstract Blind image deconvolution is a typically ill-conditioned inverse problem that requires additional information to constrain the solution space. The purpose of this paper is to investigate the characteristics of generalized lp/lq norm on the… read more here.
Keywords: adaptive blind; deconvolution using; deconvolution; generalized norm ... See more keywords
Learning to do multiframe wavefront sensing unsupervised: Applications to blind deconvolution
Sign Up to like & getrecommendations! Published in 2020 at "Astronomy and Astrophysics"
DOI: 10.1051/0004-6361/202038552
Abstract: Observations from ground based telescopes are affected by the presence of the Earth atmosphere, which severely perturbs them. The use of adaptive optics techniques has allowed us to partly beat this limitation. However, image selection… read more here.
Keywords: multiframe wavefront; image; learning multiframe; deconvolution ... See more keywords
Multi-task neural network blind deconvolution and its application to bearing fault feature extraction
Sign Up to like & getrecommendations! Published in 2023 at "Measurement Science and Technology"
DOI: 10.1088/1361-6501/accbdb
Abstract: Blind deconvolution (BD) is an effective method to extract fault-related characteristics from vibration signals. Previous researches focused on two primary approaches to improve the robustness and effectiveness of BD methods: developing new optimization functions or… read more here.
Keywords: neural network; blind deconvolution; task; fault ... See more keywords
Non-blind deconvolution with an alternating direction method of multipliers (ADMM) after noise reduction in nondestructive testing
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Instrumentation"
DOI: 10.1088/1748-0221/14/11/p11032
Abstract: To ensure the quality of material, nondestructive testing is necessary, and radiography testing is the nondestructive technique most commonly used today. For inspection, the quality of a radiographic image is critical, and there are many… read more here.
Keywords: non blind; noise reduction; method; nondestructive testing ... See more keywords
Sparse Blind Deconvolution Method for Wall Parameters Estimation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3029082
Abstract: The information of wall parameters is very important for the imaging performance of through-the-wall radar imaging (TWRI). The existing estimation methods usually require the calibration procedure to ensure the accuracy of the estimated wall parameters.… read more here.
Keywords: blind deconvolution; wall; sparse blind; wall parameters ... See more keywords
Photon-Limited Blind Deconvolution Using Unsupervised Iterative Kernel Estimation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2022.3226947
Abstract: Blind deconvolution is a challenging problem, but in low-light it is even more difficult. Existing algorithms, both classical and deep-learning based, are not designed for this condition. When the photon shot noise is strong, conventional… read more here.
Keywords: blind deconvolution; deconvolution; limited blind; estimation ... See more keywords
Algorithms for Sparse Multichannel Blind Deconvolution
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3253387
Abstract: In this article, we present two algorithms for sparse multichannel blind deconvolution (SMBD). The first algorithm is based on a cascade of a forward and a backward prediction error filter (C-PEF). The second consists in… read more here.
Keywords: blind deconvolution; smbd; multichannel blind; algorithms sparse ... See more keywords
Fast Multi-Modulus Blind Deconvolution Algorithms
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Wireless Communications"
DOI: 10.1109/twc.2022.3178480
Abstract: A novel class of fast Multi-Modulus algorithms (fastMMA) for Blind Source Separation (BSS) and deconvolution are presented in this work. These are obtained through a fast fixed-point optimization rule used to minimize the Multi-Modulus (MM)… read more here.
Keywords: deconvolution algorithms; blind deconvolution; modulus blind; multi modulus ... See more keywords