Introduction: Measurement of the sharpness or blurriness of an image is important to several image and video processing applications, such as image restoration, enhancement, deblurring, super-resolution, and biomedical applications. In particular, when combined with other factors, blurriness can be used to ascertain the overall quality of an image. Blurred images are generally due to the attenuation of high frequencies within the image, which are commonly caused by image compression algorithms, out-of-focusing, or motion blurring. Objective sharpness assessment methods have been classified into full-reference, reduced-reference, and no-reference assessments. The full-reference metrics use the original image as a reference. The reduced-reference metrics use partial information from the original image such as edge information and features of artifacts. The no-reference metrics require no information about the original image. The demand for no-reference assessments has increased since no reference image is available in many practical applications.