The fusion of a low-spatial-and-high-spectral resolution hyperspectral image (HSI) with a
high-spatial-and-low-spectral resolution multispectral image (MSI) allows synthesizing a …

We propose a new regularization function, named Spatio-Spectral Structure Tensor Total
Variation (S 3 TTV), for hyperspectral image (HSI) denoising. Spatio-Spectral Total Variation …

This paper proposes a novel regularization method, named Spatio-Spectral Structure
Tensor Total Variation (S3TTV), for denoising and destriping of hyperspectral (HS) images …

Supervised learning with a convolutional neural network is recognized as a powerful means
of image restoration. However, most such methods have been designed for application to …

We propose a method for DNN-based hyperspectral image denoising. In recent years, many
methods have been proposed for applying deep learning to the problems of restoring …

Hyperspectral image (HSI) has been widely used in target detection and classification.
However, various kinds of noise in HSIs affect the applications of HSIs. In this paper, we …

Compressive sensing is a technique of restoring original signals from a small number of
observation data by utilizing the sparseness of signals. By applying this technique to MRI …

This paper proposes multiscale structure-tensor total variation (MSTV) for image recovery.
Gradient vectors in local patches usually have similar directions, and thus each local …

In this paper, we propose a sharpening method for medical images combining weights on
each pixel and Total Variation regularization. When weighting properly on each pixel in …

ハイパースペクトル画像 (HSI: Hyperspectral Image) は, 通常の RGB 画像と比較してより細密な
スペクトル情報を持つ 3 次元データである. HSI はそのスペクトル帯域の狭さ故に …