Presentation 2021-08-23
[Invited Talk (Young Researcher)] Hyperspectral image restoration based on convex optimization
Saori Takeyama,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Hyperspectral (HS) images have high-resolution spectral information including invisible light, so they can visible the intrinsic characteristics of the scene object. Thanks to the property, the images are expected to be in various fields. However, HS images are easily affected by multiple types of noises because of less amount of incident light and have a tradeoff between spatial and spectral resolution. In this talk, we introduce about HS image restoration approach based on convex optimization.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) hyperspectral image restoration / convex optimization
Paper # SIP2021-31
Date of Issue 2021-08-16 (SIP)

Conference Information
Committee SIP
Conference Date 2021/8/23(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Yukihiro Bandou(NTT)
Vice Chair Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) / Takayuki Nakachi(Ryukyu Univ.)
Secretary Toshihisa Tanaka(Xiaomi) / Takayuki Nakachi(Takushoku Univ.)
Assistant Taichi Yoshida(UEC) / Seisuke Kyochi(Univ. of Kitakyushu)

Paper Information
Registration To Technical Committee on Signal Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) [Invited Talk (Young Researcher)] Hyperspectral image restoration based on convex optimization
Sub Title (in English)
Keyword(1) hyperspectral image restoration
Keyword(2) convex optimization
1st Author's Name Saori Takeyama
1st Author's Affiliation Tokyo Institute of Technology(Tokyo Tech)
Date 2021-08-23
Paper # SIP2021-31
Volume (vol) vol.121
Number (no) SIP-144
Page pp.pp.18-18(SIP),
#Pages 1
Date of Issue 2021-08-16 (SIP)