Journal ArticleDOI
Universal analytical forms for modeling image probabilities
TLDR
Using L/sup 2/-metric on the set of Bessel K forms, a pseudometric on the image space for quantifying image similarities/differences is proposed and some applications, including clutter classification and pruning of hypotheses for target recognition, are presented.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, 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 L/sup 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.read more
Citations
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Journal ArticleDOI
Fields of Experts
Stefan Roth,Michael J. Black +1 more
TL;DR: The approach provides a practical method for learning high-order Markov random field models with potential functions that extend over large pixel neighborhoods with non-linear functions of many linear filter responses.
Journal ArticleDOI
On Advances in Statistical Modeling of Natural Images
TL;DR: Some recent results in statistical modeling of natural images that attempt to explain patterns of non-Gaussian behavior of image statistics, i.e. high kurtosis, heavy tails, and sharp central cusps are reviewed.
Proceedings ArticleDOI
Reduced-reference image quality assessment using a wavelet-domain natural image statistic model
Zhou Wang,Eero P. Simoncelli +1 more
TL;DR: This paper proposes an RR image quality assessment method based on a natural image statistic model in the wavelet transform domain that uses the Kullback-Leibler distance between the marginal probability distributions of wavelet coefficients of the reference and distorted images as a measure of image distortion.
Journal ArticleDOI
Texture classification using spectral histograms
Xiuwen Liu,DeLiang Wang +1 more
TL;DR: A filter selection algorithm is proposed to maximize classification performance of a given dataset and the spectral histogram representation provides a robust feature statistic for textures and generalizes well.
BookDOI
Applied Bayesian modeling and causal inference from incomplete-data perspectives : an essential journey with Donald Rubin's statistical family
Andrew Gelman,Xiao-Li Meng +1 more
TL;DR: Applied Bayesian modeling and causal inference from incomplete-data perspectives as discussed by the authors, applied Bayesian modelling and causality from incomplete data perspectives, Applied Bayesian model and inference in incomplete data perspective.
References
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Book
Table of Integrals, Series, and Products
TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
Journal ArticleDOI
Nonlinear dimensionality reduction by locally linear embedding.
Sam T. Roweis,Lawrence K. Saul +1 more
TL;DR: Locally linear embedding (LLE) is introduced, an unsupervised learning algorithm that computes low-dimensional, neighborhood-preserving embeddings of high-dimensional inputs that learns the global structure of nonlinear manifolds.
Journal ArticleDOI
Eigenfaces vs. Fisherfaces: recognition using class specific linear projection
TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
Journal ArticleDOI
Independent component analysis, a new concept?
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).
Book
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
TL;DR: Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field of visual perception as discussed by the authors, where the process of vision constructs a set of representations, starting from a description of the input image and culminating with three-dimensional objects in the surrounding environment, a central theme and one that has had farreaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis.