3 papers
eess.SP2025
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 flexible sampling of a broad class of graph signals, designed to attain the best possible recovery based on the generalized sampling th…
cs.CV2025
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…
eess.SP2024
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…