31 citations · 38 across the 9 of their papers we have counts for
9 papers
Sampling Method for Generalized Graph Signals With Pre-Selected Vertices via DC Optimization
Keitaro Yamashita, Kazuki Naganuma, Shunsuke Ono
This paper proposes a method for vertex-wise aggregation sampling of a broad class of graph signals, designed to attain the best possible recovery based on the generalized sampling…
Robust Foreground-Background Separation for Severely-Degraded Videos Using Convolutional Sparse Representation Modeling
Kazuki Naganuma, Shunsuke Ono
This paper proposes a foreground-background separation (FBS) method with a novel foreground model based on convolutional sparse representation (CSR). In order to analyze the dynami…
Spatio-Spectral Structure Tensor Total Variation for Hyperspectral Image Denoising and Destriping
Shingo Takemoto, Kazuki Naganuma, Shunsuke Ono
This paper proposes a novel regularization method, named Spatio-Spectral Structure Tensor Total Variation (S3TTV), for denoising and destriping of hyperspectral (HS) images. HS ima…
Robust Spatiotemporal Fusion of Satellite Images: A Constrained Convex Optimization Approach
Ryosuke Isono, Kazuki Naganuma, Shunsuke Ono
This paper proposes a novel spatiotemporal (ST) fusion framework for satellite images, named Robust Optimization-based Spatiotemporal Fusion (ROSTF). ST fusion is a promising appro…
Generalized Graph Signal Sampling by Difference-of-Convex Optimization
Keitaro Yamashita, Kazuki Naganuma, Shunsuke Ono
We propose a comprehensive framework for the generalized sampling and recovery of graph signals by leveraging difference-of-convex (DC) optimization. A fundamental challenge in gra…
Towards Robust Hyperspectral Unmixing: Mixed Noise Modeling and Image-Domain Regularization
Kazuki Naganuma, Shunsuke Ono
Hyperspectral (HS) unmixing is the process of decomposing an HS image into material-specific spectra (endmembers) and their spatial distributions (abundance maps). Existing unmixin…
Variable-Wise Diagonal Preconditioning for Primal-Dual Splitting: Design and Applications
Kazuki Naganuma, Shunsuke Ono
This paper proposes a method for designing diagonal preconditioners for a preconditioned primal-dual splitting method (P-PDS), an efficient algorithm that solves nonsmooth convex o…
Robust Time-Varying Graph Signal Recovery for Dynamic Physical Sensor Network Data
Eisuke Yamagata, Kazuki Naganuma, Shunsuke Ono
We propose a time-varying graph signal recovery method for estimating the true time-varying graph signal from corrupted observations by leveraging dynamic graphs. Most of the conve…
A General Destriping Framework for Remote Sensing Images Using Flatness Constraint
Kazuki Naganuma, Shunsuke Ono
Removing stripe noise, i.e., destriping, from remote sensing images is an essential task in terms of visual quality and subsequent processing. Most existing destriping methods are…