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Proceedings Paper

Adaptive multiscale processing for contrast enhancement
Author(s): Andrew F. Laine; Shuwu Song; Jian Fan; Walter Huda; Janice C. Honeyman; Barbara G. Steinbach
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Paper Abstract

This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

Paper Details

Date Published: 29 July 1993
PDF: 12 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148666
Show Author Affiliations
Andrew F. Laine, Univ. of Florida (United States)
Shuwu Song, Univ. of Florida (United States)
Jian Fan, Univ. of Florida (United States)
Walter Huda, Univ. of Florida (United States)
Janice C. Honeyman, Univ. of Florida (United States)
Barbara G. Steinbach, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 1905:
Biomedical Image Processing and Biomedical Visualization
Raj S. Acharya; Dmitry B. Goldgof, Editor(s)

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