Results 41 to 50 of about 28,366 (229)
Blind Deconvolution Using Modulated Inputs [PDF]
IEEE Transactions on Signal Processing, 2020 This paper considers the blind deconvolution of multiple modulated signals, and an arbitrary filter. Multiple inputs $\boldsymbol{s}_1, \boldsymbol{s}_2, \ldots, \boldsymbol{s}_N =: [\boldsymbol{s}_n]$ are modulated (pointwise multiplied) with random sign sequences $\boldsymbol{r}_1, \boldsymbol{r}_2, \ldots, \boldsymbol{r}_N =: [\boldsymbol{r}_n ...
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Blind deconvolution of video sequences [PDF]
2008 15th IEEE International Conference on Image Processing, 2008 We present a new blind deconvolution method for video sequence. It is derived following an inverse problem approach in a Bayesian framework. This method exploits the temporal continuity of both object and PSF Combined with edge-preserving spatial regularization, a temporal regularization constrains the blind deconvolution problem, improving its ...
Soulez, Ferréol +4 more
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Advanced Materials, EarlyView.Electrochemical CO2RR is a key technology for converting CO2 into chemicals, but there remains a gap between “laboratory science” and “engineering practice” in current research. This review establishes a multi‐scale research framework, encompassing atomic‐level characterization, microenvironment regulation, external field‐assisted optimization, and AI ...
Ping Hong +3 more
wiley +1 more source
, 2019 We present a semi-blind, spatially-variant deconvolution technique aimed at optical microscopy that combines a local estimation step of the point spread function (PSF) and deconvolution using a spatially variant, regularized Richardson-Lucy algorithm. To
Liebling, Michael, Shajkofci, Adrian
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Subsampled Blind Deconvolution via Nuclear Norm Minimization [PDF]
, 2020 Many phenomena can be modeled as systems that preform convolution, including negative effects on data like translation/motion blurs. Blind Deconvolution (BD) is a process used to reverse the negative effects of a system by effectively undoing the ...
Thieken, Alexander
core
Advanced Science, EarlyView.This study employs longitudinal fluorescence imaging in transgenic mice to map post‐craniotomy cortical recovery. We identify distinct neuroimmune recovery phases: microglial structural inflammation peaks at ∼10 days, neuronal structural intensity peaks at ∼14 days and correlates with microglial activity, and functional network modularity is most ...
Guihua Xiao +13 more
wiley +1 more source
Applied aspects of modern non-blind image deconvolution methods
Компьютерная оптикаThe focus of this paper is the study of modern non-blind image deconvolution methods and their application to practical tasks. The aim of the study is to determine the current state-of-the-art in non-blind image deconvolution and to identify the ...
O.B. Chaganova +3 more
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Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring
Sensors, 2017 Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process.
Naixue Xiong +5 more
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Real-time multiframe blind deconvolution of solar images
, 2018 The quality of images of the Sun obtained from the ground are severely limited by the perturbing effect of the turbulent Earth's atmosphere. The post-facto correction of the images to compensate for the presence of the atmosphere require the combination ...
Ramos, A. Asensio +2 more
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Advanced Science, EarlyView.Grancalcin (GCA), a myeloid‐derived protein, is enriched in gingival tissues of periodontitis patients and mouse models. Through interactions with CD44 and activation of MYH9, GCA promotes NF‐κB signaling and exacerbates periodontal inflammation and bone loss.
Min Zhou +6 more
wiley +1 more source