Human vision and perception are the ultimate determinants of display quality, however, human judgment is variable, making it difficult to define and apply quantitatively in research or production environments.

Traditional methods for automated defect detection do not replicate human perception, which is an issue particularly in identifying just-noticeable differences.

Accurately correlating human perceptions of defects with the information that can be gathered using imaging colorimeters offers an opportunity for objective and repeatable defect detection and quantification.

By applying algorithms for just-noticeable differences (JND) image analysis, a means of automated, repeatable display analysis directly correlated with human perception can be achieved.

Initial application of JND analysis provides data that allows a quantitative grading of display image quality for illuminated displays, supplementing other defect detection techniques. Radiant Vision Systems presents the typical results of the implementation of this technique in this white paper.

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