Results 31 to 40 of about 17,556,704 (381)
Variational Destriping in Remote Sensing Imagery: Total Variation with L1 Fidelity
Remote Sensing, 2018 This paper introduces a variational method for destriping data acquired by pushbroom-type satellite imaging systems. The model leverages sparsity in signals and is based on current research in sparse optimization and compressed sensing.
Igor Yanovsky, Konstantin Dragomiretskiy
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Dead-Time Compensation for the First-Order Dead-Time Processes: Towards a Broader Overview
Mathematics, 2021 The article reviews the results of a number of recent papers dealing with the revision of the simplest approaches to the control of first-order time-delayed systems.
Mikulas Huba +3 more
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Sign variation, the Grassmannian, and total positivity [PDF]
, 2015 The totally nonnegative Grassmannian is the set of k-dimensional subspaces V of R^n whose nonzero Pluecker coordinates all have the same sign. Gantmakher and Krein (1950) and Schoenberg and Whitney (1951) independently showed that V is totally ...
Karp, Steven N.
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Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion
Remote Sensing, 2018 Millimeter-wave interferometric synthetic aperture radiometer (InSAR) can provide high-resolution observations for many applications by using small antennas to achieve very large synthetic aperture.
Yilong Zhang +4 more
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Poisson image denoising based on fractional-order total variation
Inverse Problems and Imaging, 2020 Poisson noise is an important type of electronic noise that is present in a variety of photon-limited imaging systems. Different from the Gaussian noise, Poisson noise depends on the image intensity, which makes image restoration very challenging ...
M. R. Chowdhury +3 more
semanticscholar +1 more source
Compressive Hyperspectral Imaging Using Progressive Total Variation [PDF]
, 2014 Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowing to simplify the architecture of the onboard sensors. Solutions proposed
Barducci, Alessandro +4 more
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A Variational Model for Wrapped Phase Denoising
Mathematics, 2023 This paper presents a variational model for the denoising of wrapped phase images. By enforcing the required Pythagorean trigonometric identity between the real and imaginary components of the signal, this model improves the signal-to-noise ratio of the ...
Ivan May-Cen +2 more
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Optimizing parametric total variation models [PDF]
2009 IEEE 12th International Conference on Computer Vision, 2009 One of the key factors for the success of recent energy minimization methods is that they seek to compute global solutions. Even for non-convex energy functionals, optimization methods such as graph cuts have proven to produce high-quality solutions by iterative minimization based on large neighborhoods, making them less vulnerable to local minima. Our
Strandmark, Petter +2 more
openaire +3 more sources
A Characterization of the Domain of Beta-Divergence and Its Connection to Bregman Variational Model
Entropy, 2017 In image and signal processing, the beta-divergence is well known as a similarity measure between two positive objects. However, it is unclear whether or not the distance-like structure of beta-divergence is preserved, if we extend the domain of the beta-
Hyenkyun Woo
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Remote Sensing, 2021 The fusion of the hyperspectral image (HSI) and the light detecting and ranging (LiDAR) data has a wide range of applications. This paper proposes a novel feature fusion method for urban area classification, namely the relative total variation structure ...
Yinghui Quan +6 more
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