Premium
P‐26: A Mura Metric Based on Human Vision Models
Author(s) -
Wang ShengBo,
Jhang ZihJian,
Wen ChaoHua
Publication year - 2006
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1889/1.2433481
Subject(s) - mura , metric (unit) , contrast (vision) , computer science , artificial intelligence , human visual system model , computer vision , noise (video) , machine vision , pattern recognition (psychology) , engineering , image (mathematics) , operations management , liquid crystal display , operating system
This paper describes a model of human spatial vision and a corresponding procedure for using the model to define a quality metric and Mura defects for flat‐panel‐displays. Together the proposed model and human contrast thresholds constitute a Mura quality metric which is responsive to noise generating both characteristics of a display system and a machine vision system. Predictions of the contrast perception performance of the model is presented and compared with human performance data. Results revealed that very small errors between predictions made by the model and the subjective test data. The results of the validation studies conducted so far suggest that the proposed method for Mura defect quantification is feasible and warrants critical examination.