Fast algorithms for histogram matching: application to texture synthesis

Jannick P. Rolland; V. Vo; B. Bloss; Craig K. Abbey

doi:10.1117/1.482725

1 January 2000 Fast algorithms for histogram matching: application to texture synthesis

Jannick P. Rolland, V. Vo, B. Bloss, Craig K. Abbey

Journal of Electronic Imaging, Vol. 9, Issue 1, (January 2000). https://doi.org/10.1117/1.482725

Texture synthesis is the ability to create ensembles of images of similar structures from sample textures that have been photographed. The method we employ for texture synthesis is based on histogram matching of images at multiple scales and orientations. This paper reports two fast and in one case simple algorithms for histogram matching. We show that the sort-matching and the optimal cumulative distribution function (CDF)-matching (OCM) algorithms provide high computational speed compared to that provided by the conventional approach. The sort-matching algorithm also provides exact histogram matching. Results of texture synthesis using either method show no subjective perceptual differences. The sort-matching algorithm is attractive because of its simplicity and speed, however as the size of the image increases, the OCM algorithm may be preferred for optimal computational speed.

Citation Download Citation

Jannick P. Rolland, V. Vo, B. Bloss, and Craig K. Abbey "Fast algorithms for histogram matching: application to texture synthesis," Journal of Electronic Imaging 9(1), (1 January 2000). https://doi.org/10.1117/1.482725

Published: 1 January 2000

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available