59 citations · 258 across the 20 of their papers we have counts for
9 papers · 1 filter
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…
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 generalized graph signals by leveraging difference-of-convex (DC) optimization. A fundamental chal…
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…
Data-Driven Sensor Selection Method Based on Proximal Optimization for High-Dimensional Data With Correlated Measurement Noise
Takayuki Nagata, Keigo Yamada, Taku Nonomura +3
The present paper proposes a data-driven sensor selection method for a high-dimensional nondynamical system with strongly correlated measurement noise. The proposed method is based…
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…
On The Synergy Between Nonconvex Extensions of The Tensor Nuclear Norm for Tensor Recovery
Kaito Hosono, Shunsuke Ono, Takamichi Miyata
Low-rank tensor recovery has attracted much attention among various tensor recovery approaches. A tensor rank has several definitions, unlike the matrix rank--e.g. the CP rank and…
Epigraphical Relaxation for Minimizing Layered Mixed Norms
Seisuke Kyochi, Shunsuke Ono, Ivan Selesnick
This paper proposes an epigraphical relaxation (ERx) technique for non-proximable mixed norm minimization. Mixed norm regularization methods play a central role in signal reconstru…
A Constrained Convex Optimization Approach to Hyperspectral Image Restoration with Hybrid Spatio-Spectral Regularization
Saori Takeyama, Shunsuke Ono, Itsuo Kumazawa
We propose a new constrained optimization approach to hyperspectral (HS) image restoration. Most existing methods restore a desirable HS image by solving some optimization problem,…
Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to River State Estimation
Yuhei Kaneko, Shogo Muramatsu, Hiroyasu Yasuda +4
This work proposes convolutional-sparse-coded dynamic mode decomposition (CSC-DMD) by unifying extended dynamic mode decomposition (EDMD) and convolutional sparse coding. EDMD is a…