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A blind approach to evaluate the perceptual sharpness present in a naturalimage is proposed. Though the literature demonstrates a set of variegatedvisual cues to detect or evaluate the absence or presence of sharpness, weemphasize in the current work that high frequency content and local standarddeviation can form strong features to compute perceived sharpness in anynatural 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 ofsharp changes between regions. Sharp region transitions in an image are causedby the presence of spatial high frequency content. Therefore, in the proposedapproach, we hypothesize that using the high frequency content as the principalstimulus, the perceived sharpness can be quantified in an image. When an imageis convolved with a high pass filter, higher values at any pixel locationsignify the presence of high frequency content at those locations. Consideringthese values as the stimulus, the exponent of the stimulus is weighted by localstandard deviation to impart the contribution of the local contrast within theformation of the sharpness map. The sharpness map highlights the relativelysharper regions in the image and is used to calculate the perceived sharpnessscore of the image. The advantages of the proposed method lie in its use ofsimple visual cues of high frequency content and local contrast to arrive atthe perceptual score, and requiring no training with the images. The promise ofthe proposed method is demonstrated by its ability to compute perceivedsharpness for within image and across image sharpness changes and for blindevaluation of perceptual degradation resulting due to presence of blur.Experiments conducted on several databases demonstrate improved performance ofthe proposed method over that of the state-of-the-art techniques.

High Frequency Content based Stimulus for Perceptual Sharpness Assessment in Natural Images