Nonlinear Filter Design Using Envelopes

Authors:
Marcel Brun;Roberto Hirata, Jr.;Junior Barrera;Edward R. Dougherty
Affiliations:
Departamento de Ciência da Computação, Instituto de Matemática e Estatística—USP Rua do Matão, 1010 - 05508-900, São Paulo, SP, Brazil;SENAC College of Computer Science and Technology, Department of Electrical Engineering, Texas A & M University;Departamento de Ciência da Computação, Instituto de Matemática e Estatística—USP Rua do Matão, 1010 - 05508-900, São Paulo, SP, Brazil;Department of Electrical Engineering, Texas A & M University
Venue:
Journal of Mathematical Imaging and Vision
Year:
2004

Citing 13
Cited 0

Precision of morphological-representation estimators for translation-invariant binary filters: increasing and nonincreasing

Signal Processing
Optimal stack filters under rank selection and structural constraints

Signal Processing
Neural networks for pattern recognition

Neural networks for pattern recognition
Automatic programming of morphological machines by PAC learning

Fundamenta Informaticae - Special issue on mathematical morphology
Aperture filters

Signal Processing
Hybrid human-machine binary morphological operator design: an independent constraint approach

Signal Processing
Multiresolution Analysis for Optimal Binary Filters

Journal of Mathematical Imaging and Vision
A Tutorial on Support Vector Machines for Pattern Recognition

Data Mining and Knowledge Discovery
Pattern Recognition Theory in Nonlinear Signal Processing

Journal of Mathematical Imaging and Vision
Design of Statistically Optimal Stack Filters

SIBGRAPI '99 Proceedings of the XII Brazilian Symposium on Computer Graphics and Image Processing
Envelope-constrained filters: adaptive algorithms

IEEE Transactions on Signal Processing
Robust design of envelope-constrained filters in the presence ofinput uncertainty

IEEE Transactions on Signal Processing
A training framework for stack and Boolean filtering-fast optimal design procedures and robustness case study

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Machine design of a signal or image operator involves estimating the optimal filter from sample data. The optimal filter is the best filter, relative to the error measure used; however, owing to design error, the designed filter might not perform well. In general it is suboptimal. The envelope constraint involves using two humanly designed filters that form a lower and upper bound for the designed operator. The method has been employed for binary operators. This paper considers envelope design for gray-scale filters, in particular, aperture filters. Some basic theoretical properties are stated, including optimality of the design method relative to the constraint imposed by the envelope. Examples are given for noise reduction and de-blurring.