Image quality is a vital criterion that guides the technical development of digital cameras. Traditionally, the image\r\nquality of digital cameras has been measured using test-targets and/or subjective tests. Subjective tests should be\r\nperformed using natural images. It is difficult to establish the relationship between the results of artificial test\r\ntargets and subjective data, however, because of the different test image types. We propose a framework for\r\nobjective image quality metrics applied to natural images captured by digital cameras. The framework uses\r\nreference images captured by a high-quality reference camera to find image areas with appropriate structural\r\nenergy for the quality attribute. In this study, the framework was set to measure sharpness. Based on the results,\r\nthe mean performance for predicting subjective sharpness was clearly higher than that of the state-of-the-art\r\nalgorithm and test-target sharpness metrics.
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