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Sharpness Measure: Towards Automatic Image Enhancement

Shaked, Doron; Tastl, Ingeborg


Keyword(s): image enhancement; image analysis; image sharpening; feature extraction

Abstract: We propose a measure for image sharpness, which facilitates automatic image sharpness enhancement. This way blurry images will be sharpened more whereas sufficiently sharp images will not be sharpened at all. The measure employs localized frequency content analysis in a feature-based context. Thereby it avoids many of the pitfalls of alternative methods: Frequency domain methods provide excellent sharpness measures for images of similar scenes, however they fail when the scene changes. Feature-based methods concentrate on features, however assumptions required for good performance are too restrictive for general purposes. The proposed sharpness measure correlates well with perceived sharpness, and is to a large degree invariant to image content. Furthermore, we show that the proposed image sharpness measure can be used to drive an enhancement algorithm, which will sharpen an input image to a nominal measure. Last but not least, the proposed sharpness measure is computationally efficient, and requires fewer computations than a 3x3 convolution. Notes: To be presented at the IEEE International Conference on Image Processing, 11-14 September 2005, Genoa, Italy

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