Image evaluation and quality measurements are fundamental components in all image processing applications and
techniques. Recently, a no-reference perceptual blur metrics (PBM) was suggested for numerical evaluation of blur
effects. The method is based on computing the intensity variations between neighboring pixels of the input image
before and after low-pass filtering. The method was proved to demonstrate a very good correlation between the
quantitative measure it provides and visual evaluation of perceptual image quality. However, this quantitative image
blurriness measure has no intuitive meaning and has no association with conventionally accepted imaging system design
parameters such as, for instance, image bandwidth.
In this paper, we suggest an extended modification of this PBM-method that provides such a direct association and
allows evaluation image in terms of the image efficient bandwidth. To this end we apply the PBM-method to a series of
test pseudo-random images with uniform spectrum of different spread within the image base-band defined by the image
sampling rate and map the image blur measurement results obtained for this set of test images to corresponding
measures of their bandwidths. In this way we obtain a new image feature, which provides evaluation of image in terms
of the image effective bandwidth measured in fractions, from 0 to 1, of the image base-band. In addition, we also show
that the effective bandwidth measure provides a good estimation for the potential JPEG encoder compression rate,
which allows one to choose the best compression quality for a requested compressed image size.