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Efficient restoration and enhancement of super-resolved X-ray images

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Robinson, MD; Farsiu, S; Lo, JY; Toth, CA
December 1, 2008

Our previous work demonstrates the ability to reconstruct a single higher resolution image from fusing a collection of multiple extremely low-dosage aliased X-ray images. While this computationally efficient method eliminates aliasing artifacts associated with undersampling, it does not address the problem of deblurring the reconstructed image. In this paper, we present a fast nonlinear deblurring algorithm, specifically designed to address the nonstationary noise associated with multiframe reconstructed images. The algorithm uses a combination of Fourier sharpening and wavelet denoising similar to the ForWarD algorithm. Experimental results on enhancing digital mammogram images attest to the effectiveness of the presented method. © 2008 IEEE.

Duke Scholars

DOI

ISBN

9781424417643

Publication Date

December 1, 2008

Start / End Page

629 / 632
 

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Robinson, M. D., Farsiu, S., Lo, J. Y., & Toth, C. A. (2008). Efficient restoration and enhancement of super-resolved X-ray images (pp. 629–632). https://doi.org/10.1109/ICIP.2008.4711833
Robinson, M. D., S. Farsiu, J. Y. Lo, and C. A. Toth. “Efficient restoration and enhancement of super-resolved X-ray images,” 629–32, 2008. https://doi.org/10.1109/ICIP.2008.4711833.
Robinson MD, Farsiu S, Lo JY, Toth CA. Efficient restoration and enhancement of super-resolved X-ray images. In 2008. p. 629–32.
Robinson, M. D., et al. Efficient restoration and enhancement of super-resolved X-ray images. 2008, pp. 629–32. Scopus, doi:10.1109/ICIP.2008.4711833.
Robinson MD, Farsiu S, Lo JY, Toth CA. Efficient restoration and enhancement of super-resolved X-ray images. 2008. p. 629–632.

DOI

ISBN

9781424417643

Publication Date

December 1, 2008

Start / End Page

629 / 632