A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Database Support for Knowledge-Based Image Evaluation
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
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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.