Quality Evaluation of Decimated Images Using Visual Difference Predictor

Ryo MATSUOKA; Takao JINNO; Masahiro OKUDA

doi:10.1587/transfun.E96.A.1824

Quality Evaluation of Decimated Images Using Visual Difference Predictor

Ryo MATSUOKA, Takao JINNO, Masahiro OKUDA

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This paper proposes a method for evaluating visual differences caused by decimation. In many applications it is important to evaluate visual differences of two different images. There exist many image assessment methods that utilize the model of the human visual system (HVS), such as the visual difference predictor (VDP) and the Sarnoff visual discrimination model. In this paper, we extend and elaborate on the conventional image assessment method for the purpose of evaluating the visual difference caused by the image decimation. Our method matches actual human evaluation more and requires less computational complexity than the conventional method.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E96-A No.8 pp.1824-1827

Publication Date: 2013/08/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E96.A.1824

Type of Manuscript: LETTER

Category: Image

Authors

Ryo MATSUOKA
  University of Kitakyushu
Takao JINNO
  Toyohashi University of Technology
Masahiro OKUDA
  University of Kitakyushu

Keyword

quantitative evaluation, decimation, interpolation, visual difference predictor

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Ryo MATSUOKA, Takao JINNO, Masahiro OKUDA, "Quality Evaluation of Decimated Images Using Visual Difference Predictor" in IEICE TRANSACTIONS on Fundamentals, vol. E96-A, no. 8, pp. 1824-1827, August 2013, doi: 10.1587/transfun.E96.A.1824.
Abstract: This paper proposes a method for evaluating visual differences caused by decimation. In many applications it is important to evaluate visual differences of two different images. There exist many image assessment methods that utilize the model of the human visual system (HVS), such as the visual difference predictor (VDP) and the Sarnoff visual discrimination model. In this paper, we extend and elaborate on the conventional image assessment method for the purpose of evaluating the visual difference caused by the image decimation. Our method matches actual human evaluation more and requires less computational complexity than the conventional method.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E96.A.1824/_p

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@ARTICLE{e96-a_8_1824,
author={Ryo MATSUOKA, Takao JINNO, Masahiro OKUDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Quality Evaluation of Decimated Images Using Visual Difference Predictor},
year={2013},
volume={E96-A},
number={8},
pages={1824-1827},
abstract={This paper proposes a method for evaluating visual differences caused by decimation. In many applications it is important to evaluate visual differences of two different images. There exist many image assessment methods that utilize the model of the human visual system (HVS), such as the visual difference predictor (VDP) and the Sarnoff visual discrimination model. In this paper, we extend and elaborate on the conventional image assessment method for the purpose of evaluating the visual difference caused by the image decimation. Our method matches actual human evaluation more and requires less computational complexity than the conventional method.},
keywords={},
doi={10.1587/transfun.E96.A.1824},
ISSN={1745-1337},
month={August},}

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TY - JOUR
TI - Quality Evaluation of Decimated Images Using Visual Difference Predictor
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1824
EP - 1827
AU - Ryo MATSUOKA
AU - Takao JINNO
AU - Masahiro OKUDA
PY - 2013
DO - 10.1587/transfun.E96.A.1824
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E96-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2013
AB - This paper proposes a method for evaluating visual differences caused by decimation. In many applications it is important to evaluate visual differences of two different images. There exist many image assessment methods that utilize the model of the human visual system (HVS), such as the visual difference predictor (VDP) and the Sarnoff visual discrimination model. In this paper, we extend and elaborate on the conventional image assessment method for the purpose of evaluating the visual difference caused by the image decimation. Our method matches actual human evaluation more and requires less computational complexity than the conventional method.
ER -