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Originally published In Press as doi:10.1167/iovs.08-3079 on April 15, 2009
 (Investigative Ophthalmology and Visual Science. 2009;50:4502-4508.)
© 2009 by The Association for Research in Vision and Ophthalmology, Inc.
doi:10.1167/iovs.08-3079
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Quantitative Assessment of Perceived Visibility Enhancement with Image Processing for Single Face Images: A Preliminary Study

Ming Mei1 and Susan J. Leat2

1From the Center for Vision Research, York University, Toronto, Ontario, Canada; and the 2School of Optometry, University of Waterloo, Waterloo, Ontario, Canada.

PURPOSE. To develop a method to quantitatively assess the visibility enhancement of single face images gained with digital filters for people with maculopathy. To apply this method to obtaining preliminary results of visibility enhancement with subjectively preferred filters for people with maculopathy.

METHODS. Six subjects with normal vision and two with maculopathy were required to recognize seven facial expressions of single face images with different display durations of 2 seconds, 1 second, and 0.73 second. As a result, four facial expressions (anger, disgust, fear, and sadness) and a display duration of 0.73 second were chosen to measure single face image visibility enhancement with subjectively preferred digital filters. Finally, nine subjects with maculopathy viewed 30 images with four facial expressions that were either unfiltered or filtered with subjectively preferred digital filters. Each subject was required to identify the facial expression in a four-alternative, forced-choice paradigm. The errors with original and filtered images were calculated.

RESULTS. The method with four facial expressions and display duration of 0.73 second prevented a ceiling effect. The nine subjects with maculopathy made significantly fewer errors with the filtered images than with the original ones images (P = 0.004).

CONCLUSIONS. The developed method was effective in objective (quantitative) measurement of the enhancement in image visibility with digital filtering for people with maculopathy. There is a measurable improvement in facial expression recognition with subjectively preferred filters. The facial expression recognition task developed and validated in the present study is recommended as a method to be used in future studies of enhancement of face images.






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