Abstract
This paper presents an efficient blind method for image quality measurement. The key idea is to characterize image quality in terms of image sharpness while the sharpness is considered as blurring. The blur parameter is estimated using sharp edges in the underlying image. To improve the system efficiency, a criterion for edge sharpness is proposed and only the sharpest edges are selected for extraction of line spread function (LSF). The effect of nearby edges on LSF is analyzed, and two constrains are presented to select appropriate LSFs. The experimental results demonstrate that the performance of the proposed method is comparable to the method in, but the speed is much fast. This paradigm can be served as blind image quality evaluation for automatic vision-based applications.
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