Ranking in Rp and its use in multivariate image estimation

Russell C. Hardie; Gonzalo R. Arce

doi:10.1117/12.19593

1 July 1990 Ranking in R^p and its use in multivariate image estimation

Russell C. Hardie, Gonzalo R. Arce

Proceedings Volume 1247, Nonlinear Image Processing; (1990) https://doi.org/10.1117/12.19593
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

In this paper, we consider the extension of ranking a set of elements in R to ranking a set of vectors in a p'th dimensional space R^p. In the approach presented here vector ranking reduces to ordering vectors according to a sorted list of vector distances. A statistical analysis of this vector ranking is presented, and these vector ranking concepts are then used to develop ranked-order type estimators for multivariate image fields. We develop a class of vector filters which are efficient smoothers in additive noise and can be designed to have detail-preserving characteristics. A statistical analysis is developed for the class of filters and a number of simulations were performed in order to quantitatively evaluate their performance. These simulations involve the estimation of both stationary multivariate random signals and color images in additive noise.

Citation Download Citation

Russell C. Hardie and Gonzalo R. Arce "Ranking in R^p and its use in multivariate image estimation", Proc. SPIE 1247, Nonlinear Image Processing, (1 July 1990); https://doi.org/10.1117/12.19593

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