Abstract
Two comprehensive evaluation metrics, image perceptual quality based on
target detectability (PQTD) and perceptual quality based on scene understanding
(PQSU), are proposed to measure image quality for visible and infrared color fusion
images of typical scenes. A psychophysical experiment is performed to explore the
relationship between conventional quality attributes and the proposed evaluation
metrics. The prediction models for PQTD and PQSU are derived by multiple linear
regression statistical analyses. Results show that the variation of PQTD can be
predicted by sharpness and perceptual contrast between the target and background,
and that color harmony and sharpness can predict PQSU. The proposed evaluation
metrics and their prediction models provide a foundation for further developing
objective quality evaluation of color fusion images.
© 2012 Chinese Optics Letters
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