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Takayuki Hasegawa

Researcher at Chiba University

Publications -  31
Citations -  434

Takayuki Hasegawa is an academic researcher from Chiba University. The author has contributed to research in topics: Image conversion & Quality (business). The author has an hindex of 8, co-authored 29 publications receiving 413 citations.

Papers
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Journal ArticleDOI

System design for accurately estimating the spectral reflectance of art paintings

TL;DR: A system that incorporates both spectral characteristics and estimation software to estimate spectral reflectance of art paintings from low-dimensional multichannel images is designed and developed on the basis of the minimum-mean-square error criterion.
Patent

Differential pumping system and exposure apparatus

TL;DR: A differential pumping system as discussed by the authors includes a first chamber for storing a light source that emits pulsed light, a first exhaust unit for exhausting said first chamber, a second chamber being connectible to the first chamber to receive the pulsed energy, and a second exhaust unit to exhaust the second chamber.
Journal ArticleDOI

Limitation of Color Samples for Spectral Estimation from Sensor Responses in Fine Art Painting

TL;DR: In this paper, a new technique is proposed to improve the way of selecting samples used to estimate spectral reflectance from sensor responses in multi-band images, which limits the samples of reflectance spectra based on the spectral reflectances estimated by the conventional estimation method, and estimates it again using the limited samples.
Patent

Method of cooling optical component, cooling device, exposure apparatus, and method of manufacturing device

TL;DR: In this article, the authors proposed a cooling method for cooling a reflecting mirror that is irradiated by an EUV light, where circuit patterns are precisely exposed and transferred onto a wafer, resulting in reduction of the fraction defective of the wafers.
Journal ArticleDOI

Photometric approach to surface reconstruction of artist paintings

TL;DR: A robust and computationally less expensive nonlinear optimization algorithm is proposed that optimizes the small number of parameters to simultaneously determine all of the specular BRDF, diffuse albedo, and surface normal.