Premium
Pseudopassive two‐dimensional recursive digital filters for image processing
Author(s) -
Domanski Marek,
Fettweis Alfred
Publication year - 1989
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.4490170110
Subject(s) - digital filter , gaussian , mathematics , algorithm , stability (learning theory) , filter (signal processing) , norm (philosophy) , network synthesis filters , prototype filter , control theory (sociology) , computer science , filter design , artificial intelligence , computer vision , electronic engineering , engineering , physics , control (management) , quantum mechanics , machine learning , political science , law
This paper describes the theory of two‐dimensional digital filters that are pseudopassive with respect to the l p ‐norm of the state vector. As the classical pseudopassive digital filters are a subclass of these filters, the respective theorems referred to stability are also generalized. It is shown that this theory is useful for the two‐dimensional filters that answer with non‐negative‐valued responses to non‐negative‐valued excitations. Such systems are especially suitable for image processing. the synthesis of the l 1 ‐pseudolossless systems is proposed as a tool to guarantee stability of such filters. A technique to obtain local state‐space models for such two‐dimensional l 1 ‐pseudolossless recursive filters with prescribed spatial responses is given. A ‘Gaussian filter’ design illustrates the technique and shows that the proposed two‐dimensional l 1 ‐pseudolossless filters are able to match useful spatial responses.