An image segmentation scheme based on multiresolutional, successive approximations of the image histogram is proposed. The algorithm begins with a coarse, initial segmentation of the image obtained by selecting thresholds from a coarse sampling of a low-pass filtered version of the image histograms. This segmentation is refined by selecting thresholds from increasingly better approximations of the histogram. The algorithm is linear in the size of the input image and handles images with multimodal histograms. Preliminary results indicate that the approach shows promise as a simple, computationally efficient algorithm for hierarchical image segmentation. The algorithm may easily be embedded in the `split' phase of any of the well known split-and-merge type segmentation algorithms.
Kidiyo KpalmaVéronique Haese-CoatJoseph Ronsin
Jing ZhouXiang FangBijoy K. Ghosh
Philippe SalembierLaurent Jaquenoud