Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
EA, SIP, SP, IPSJ-SLP [detail] |
2025-03-03 11:20 |
Okinawa |
|
[Poster Presentation]
Low-Dose DECT Image Reconstruction Using Edge Sparsity and Similarity Akira Egashira, Daichi Kitahara (Keio Univ.) EA2024-112 SIP2024-147 SP2024-53 |
Dual-energy computed tomography (DECT) enables diagnosis using not only X-ray attenuation coefficients but also more det... [more] |
EA2024-112 SIP2024-147 SP2024-53 pp.221-226 |
ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] |
2024-02-20 12:45 |
Hokkaido |
Hokkaido Univ. |
3D CG Coded Image Noise Removal and Quality Assessment Based on Optimal Design of Total Variation Regularization Norifumi Kawabata (Kanazawa Gakuin Univ.) ITS2023-67 IE2023-56 |
Sparse coding techniques, which reproduce and represent images with as few combinations as possible from a small amount ... [more] |
ITS2023-67 IE2023-56 pp.112-117 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-16 13:10 |
Okinawa |
Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
[Special Talk]
Group Sparse/Low-rank Modeling for Multidimensional Signal Recovery Seisuke Kyochi (Kogakuin Univ.) IMQ2022-52 CQ2022-93 IE2022-129 MVE2022-82 |
Group sparse/low-rank modeling based on the ℓ1 norm and nuclear norm has been successfully applied
to signal processing... [more] |
IMQ2022-52 CQ2022-93 IE2022-129 MVE2022-82 pp.156-161(IMQ), pp.64-69(CQ), pp.156-161(IE), pp.156-161(MVE) |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2022-06-27 17:25 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Additive Cumulative Link Model with Total Variation Regularization for Ordinal Regression Hiroya Iyori, Shin Matsushima (Univ. of Tokyo) NC2022-8 IBISML2022-8 |
In many fields such as medical research and social science, data on an ordinal scale are often obtained.
Problems in wh... [more] |
NC2022-8 IBISML2022-8 pp.69-75 |
EA, SIP, SP, IPSJ-SLP [detail] |
2022-03-01 09:20 |
Okinawa |
(Primary: On-site, Secondary: Online) |
[Poster Presentation]
Hyperspectral Image Denoising by Graph Spatio-Spectral Total Variation Minimization Shingo Takemoto, Kazuki Naganuma, Shunsuke Ono (Tokyo Tech) EA2021-70 SIP2021-97 SP2021-55 |
We propose a novel denoising method for hyperspectral images (HSI) based on the Graph Spatio-Spectral Total Variation (G... [more] |
EA2021-70 SIP2021-97 SP2021-55 pp.38-43 |
MI |
2022-01-27 14:30 |
Online |
Online |
Reducing the number of projections in 3-D Compton Camera using EM-TV based image reconstruction Tomohiro Ono (Hirosaki Univ.), Yuto Nagao, Mitsutaka Yamaguchi, Naoki Kawachi (QST), Tsutomu Zeniya (Hirosaki Univ.) MI2021-80 |
It is desired to develop a Compton camera, which has been used for gamma ray detection in space and the environment, as ... [more] |
MI2021-80 pp.150-155 |
SIS, ITE-BCT |
2020-10-01 13:40 |
Online |
Online |
Image Regularization with Morphological Gradient Priors Using Optimization of Multiple Structuring Elements for Each Pixel Hirotaka Oka, Mistuji Muneyasu, Soh Yoshida (Kansai Univ.), Makoto Nakashizuka (CIT) SIS2020-15 |
In image regularization, a method for restoring an image has been proposed in which a morphological gradient is used as ... [more] |
SIS2020-15 pp.29-34 |
ITE-BCT, SIS |
2019-10-24 15:30 |
Fukui |
Fukui International Activities Plaza |
Image Regularization with Total Variation and Morphological Gradient Priors Using Optimization of Structuring Element for Each Pixel Shoya Oohara, Hirotaka Oka, Mistuji Muneyasu, Soh Yoshida (Kansai Univ.), Makoto Nakashizuka (CIT) SIS2019-17 |
As an image prior for image restoration, a method using the sum of morphological gradients has been proposed. Optimizati... [more] |
SIS2019-17 pp.47-52 |
IMQ, IE, MVE, CQ (Joint) [detail] |
2019-03-14 14:20 |
Kagoshima |
Kagoshima University |
Implementation and Evaluation of Total Variation Regularization Decomposition for Super Resolution using an Inexpensive Single Board Computer Hiromasa Takeda, Taiki Kondo, Hiroto Kizuna, Hiroyuki Sato, Eiji Sugino (Iwate Pref. Univ.) IMQ2018-39 IE2018-123 MVE2018-70 |
With the advent of large and high resolution displays in recent years, large screen electronic signage such as digital s... [more] |
IMQ2018-39 IE2018-123 MVE2018-70 pp.97-102 |
CAS, SIP, MSS, VLD |
2018-06-14 14:10 |
Hokkaido |
Hokkaido Univ. (Frontier Research in Applied Sciences Build.) |
A Study on Reflection Removal Using Depth Map Toshihiro Shibata, Yuji Akai, Ryo Matsuoka (Kagawa Univ.) CAS2018-8 VLD2018-11 SIP2018-28 MSS2018-8 |
In this paper, we propose a novel reflection removal method for RGB-D images that achieves reflection removal and depth ... [more] |
CAS2018-8 VLD2018-11 SIP2018-28 MSS2018-8 pp.39-43 |
MI |
2017-01-18 10:41 |
Okinawa |
Tenbusu Naha |
[Short Paper]
Super Resolution of MR images via Optimization in Fourier Domain with Low Rank and Smoothness of Image Space Naoki Kawamura, Tatsuya Yokota, Hidekata Hontani (NITech) MI2016-74 |
We use MR images of the same object measured with different magnetic gradient directions in order to construct a MR imag... [more] |
MI2016-74 pp.19-20 |
MI |
2015-03-03 10:46 |
Okinawa |
Hotel Miyahira |
Row-Action-Type Method for Total-Variation Regularization and its Application to CT Image Reconstruction Fukashi Yamazaki, Takuya Nemoto, Keita Takaki, Hiroyuki Kudo (Tsukuba Univ.) MI2014-95 |
This paper proposes an exact row-action-type total variation(TV) minimization algorithm which is faster than conventiona... [more] |
MI2014-95 pp.199-204 |
MI |
2015-03-03 10:58 |
Okinawa |
Hotel Miyahira |
Total variation regularization of diffusion weighted images for reducing noise of diffusional kurtosis MRI Yuuki Nakamura, Hirokuni Okada, Masahito Aoyama, Yoshitaka Masutani (Hiroshima City Univ.) MI2014-96 |
Diffusional kurtosis imaging (DKI) is an MR imaging method for quantifying non-Gaussianity of water molecule based on a ... [more] |
MI2014-96 pp.205-208 |