Optimal unsharp mask for image sharpening and noise removal

Sang Ho Kim; Jan P. Allebach

doi:10.1117/12.538366

21 May 2004 Optimal unsharp mask for image sharpening and noise removal

Sang Ho Kim, Jan P. Allebach

Proceedings Volume 5299, Computational Imaging II; (2004) https://doi.org/10.1117/12.538366
Event: Electronic Imaging 2004, 2004, San Jose, California, United States

Abstract

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.

Citation Download Citation

Sang Ho Kim and Jan P. Allebach "Optimal unsharp mask for image sharpening and noise removal", Proc. SPIE 5299, Computational Imaging II, (21 May 2004); https://doi.org/10.1117/12.538366

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