We describe a method for objective and quantitative evaluation of image quality. The method represents a novel use of image enhancement concepts. It employs three new measures that evaluate the definition of contours, uniform intensity distribution, and noise rate in determining the image quality. Because the three measures have clear physical meanings, they can be selectively applied according to the viewer's evaluation criteria. The three measures are relatively inexpensive to compute, making them suitable for automated ranking of image quality in personal digital imaging devices, such as digital cameras. However, the method is equally adept at evaluating other digital images such as those on the Internet. Experiments with the method show good correlation with visual quality assessment for various image subject types. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Yao, H., Huseh, M. Y., Yao, G., & Liu, Y. (2005). Image evaluation factors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3656 LNCS, pp. 255–262). Springer Verlag. https://doi.org/10.1007/11559573_32
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