Universal Analytical Forms for Modeling Image Probabilities (2002)
| Venue: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Citations: | 31 - 8 self |
BibTeX
@ARTICLE{Srivastava02universalanalytical,
author = {Anuj Srivastava and Xiuwen Liu and Ulf Grenander},
title = {Universal Analytical Forms for Modeling Image Probabilities},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2002},
volume = {24},
pages = {1200--1214}
}
OpenURL
Abstract
Seeking probability models for images, we employ a spectral approach where the images are decomposed using bandpass filters and probability models are imposed on the filter outputs (also called spectral components). We employ a (two-parameter) family of probability densities, introduced in [11] and called Bessel K forms, for modeling the marginal densities of the spectral components, and demonstrate their fit to the observed histograms for video, infrared, and range images. Motivated by object-based models for image analysis, a relationship between the Bessel parameters and the imaged objects is established. Using 2-metric on the set of Bessel K forms, we propose a pseudometric on the image space for quantifying image similarities/differences. Some applications, including clutter classification and pruning of hypotheses for target recognition, are presented.







