A blind approach to evaluate the perceptual sharpness present in a natural image is proposed. Though the existing literature demonstrates a set of variegated visual cues to detect or evaluate the absence or presence of sharpness, we emphasize in the current work that high frequency content and local standard deviation can form strong features to compute perceived sharpness in any natural image, and can be considered an able alternative for the existing cues. Unsharp areas in a natural image happen to exhibit uniform intensity or lack of sharp changes between regions. Sharp region transitions in an image are caused by the presence of spatial high frequency content. Therefore, in the proposed framework, we hypothesize that using the high frequency content as the principal stimulus, the perceived sharpness can be quantified in an image. Using extensive experiments, the performance of the proposed framework is demonstrated in terms of different filters and varying pooling strategies. The experiments conducted on four publicly available databases demonstrate improved performance of the proposed framework over that of the state-of-the-art techniques for blind evaluation of perceptual degradation resulting due to the presence of blur.