Adaptive multiscale processing for contrast enhancement

Andrew F. Laine; Shuwu Song; Jian Fan; Walter Huda; Janice C. Honeyman; Barbara G. Steinbach

doi:10.1117/12.148666

29 July 1993 Adaptive multiscale processing for contrast enhancement

Andrew F. Laine, Shuwu Song, Jian Fan, Walter Huda, Janice C. Honeyman, Barbara G. Steinbach

Proceedings Volume 1905, Biomedical Image Processing and Biomedical Visualization; (1993) https://doi.org/10.1117/12.148666
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

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.

Citation Download Citation

Andrew F. Laine, Shuwu Song, Jian Fan, Walter Huda, Janice C. Honeyman, and Barbara G. Steinbach "Adaptive multiscale processing for contrast enhancement", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); https://doi.org/10.1117/12.148666

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