A Novel Quality Assessment Method for Flat Panel Display Defects

Hoon Kim, Heon Gu, Young Hyun Kim, Kang A. Choi, Sung-Jea Ko

Research output: Contribution to journalArticle

Abstract

This paper presents a novel quality assessment method for flat panel display (FPD) defects, often called Muras, that employs the characteristics of the human visual system (HVS). Given a Mura image, the brightness difference between the Mura and its surrounding region is first adjusted to reflect the HVS's property of background-adaptive perception. Then, the resulting adjusted Mura image is further processed using multiscale defect saliency acquisition (MDSA) to obtain a final Mura image with human perception characteristics. In the experiments, the quality scores of Mura test images are measured using the conventional and proposed methods. The results demonstrate that the quality of Mura evaluated by the proposed method correlates with the subjective quality to a much higher degree compared with the conventional methods.

Original languageEnglish
Article number7368869
Pages (from-to)500-505
Number of pages6
JournalIEEE/OSA Journal of Display Technology
Volume12
Issue number5
DOIs
Publication statusPublished - 2016 May 1

Fingerprint

Flat panel displays
flat panel displays
Defects
defects
Luminance
acquisition
brightness
Experiments

Keywords

  • Human visual system (HVS)
  • Mura
  • perceptual defect assessment
  • Visual saliency

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

A Novel Quality Assessment Method for Flat Panel Display Defects. / Kim, Hoon; Gu, Heon; Kim, Young Hyun; Choi, Kang A.; Ko, Sung-Jea.

In: IEEE/OSA Journal of Display Technology, Vol. 12, No. 5, 7368869, 01.05.2016, p. 500-505.

Research output: Contribution to journalArticle

Kim, Hoon ; Gu, Heon ; Kim, Young Hyun ; Choi, Kang A. ; Ko, Sung-Jea. / A Novel Quality Assessment Method for Flat Panel Display Defects. In: IEEE/OSA Journal of Display Technology. 2016 ; Vol. 12, No. 5. pp. 500-505.
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