Sharpness estimation for document and scene images

Images of document pages have different characteristics than images of natural scenes, and so the sharpness measures developed for natural scene images do not necessarily extend to document images primarily composed of text. We present an efficient and simple method for effectively estimating the sharp-ness/blurriness of document images that also performs well on natural scenes. Our method can be used to predict the sharpness in scenarios where images are blurred due to camera-motion (or hand-shake), defocus, or inherent properties of the imaging system. The proposed method outperforms the perceptually-based, no-reference sharpness work of [1] and [4], which was shown to perform better than 14 other no-reference sharpness measures on the LIVE dataset.

[1]  Lina J. Karam,et al.  A No-Reference Image Blur Metric Based on the Cumulative Probability of Blur Detection (CPBD) , 2011, IEEE Transactions on Image Processing.

[2]  Patrenahalli M. Narendra,et al.  A Separable Median Filter for Image Noise Smoothing , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Xiang Zhu,et al.  Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content , 2010, IEEE Transactions on Image Processing.

[5]  Stefan Winkler,et al.  A no-reference perceptual blur metric , 2002, Proceedings. International Conference on Image Processing.

[6]  Eric C. Larson,et al.  Most apparent distortion: full-reference image quality assessment and the role of strategy , 2010, J. Electronic Imaging.

[7]  Lina J. Karam,et al.  A no-reference perceptual image sharpness metric based on a cumulative probability of blur detection , 2009, 2009 International Workshop on Quality of Multimedia Experience.

[8]  Sei-Wang Chen,et al.  A non-parametric blur measure based on edge analysis for image processing applications , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[9]  Xiang Zhu,et al.  A no-reference sharpness metric sensitive to blur and noise , 2009, 2009 International Workshop on Quality of Multimedia Experience.

[10]  Lina J. Karam,et al.  A No-Reference Objective Image Sharpness Metric Based on the Notion of Just Noticeable Blur (JNB) , 2009, IEEE Transactions on Image Processing.

[11]  Weisi Lin,et al.  A no-reference quality metric for measuring image blur , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..