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Optimal unsharp mask for image sharpening and noise removal

[+] Author Affiliations
Sang Ho Kim

Digital Printing Division, Samsung Elec. Co. Ltd., Suwon, Korea E-mail: sangho1.kim@samsung.com

Jan P. Allebach

School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907-1285 E-mail: allebach@ecn.purdue.edu

J. Electron. Imaging. 14(2), 023005 (May 24, 2005). doi:10.1117/1.1924510
History: Received Oct. 21, 2003; Revised Nov. 17, 2004; Accepted Nov. 29, 2004; May 24, 2005; Online May 24, 2005
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We consider the problem of restoring a noisy blurred image using an adaptive unsharp mask filter. Starting with a set of very high quality images, we use models for both the blur and the noise to generate a set of degraded images. With these image pairs, we optimally train the strength parameter of the unsharp mask to smooth flat areas of the image and to sharpen areas with detail. We characterize the blur and the noise for a specific hybrid analog/digital imaging system in which the original image is captured on film with a low-cost analog camera. A silver-halide print is made from this negative; and this is scanned to obtain a digital image. Our experimental results for this imaging system demonstrate the superiority of our optimal unsharp mask compared to a conventional unsharp mask with fixed strength. © 2005 SPIE and IS&T.

© 2005 SPIE and IS&T

Citation

Sang Ho Kim and Jan P. Allebach
"Optimal unsharp mask for image sharpening and noise removal", J. Electron. Imaging. 14(2), 023005 (May 24, 2005). ; http://dx.doi.org/10.1117/1.1924510


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