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.
© 2015 IEEE
PDF Article
More Like This
Cited By
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription