Abstract

A multiresolution-analysis-based local contrast transform is proposed to enhance local structures in x-ray images. The local contrast is defined as a ratio of the local intensity variation to the local mean. With wavelet multiresolution decomposition, the detail coefficients and approximation coefficients are interpreted, respectively, as local variations and local averages in virtue of the localization property of wavelet transform. Based on the local contrast transform, an algorithm is developed to modify coefficients before wavelet synthesis. An across-scale local contrast is obtained when the scale associated with the local variation is different from that of the local mean. The nonlinearity and local adaptiveness properties of local contrast transform result in structural enhancement in local dark regions in the reconstructed images. We applied this technique to deboned poultry inspection using x-ray images. Because of its high x-ray absorption, a foreign inclusion appears as a low-intensity object in an x-ray image, thus resulting in contrast enhancement in the reconstructed multiresolution images.

© 2001 Optical Society of America

Full Article  |  PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (8)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (36)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription