Open AccessHilbert space filling curve using scilab
Author(s) -
Sushma T.V,
M. K. Roopa
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.9.9748
Subject(s) - hilbert curve , space (punctuation) , computer science , hilbert space , property (philosophy) , image compression , image (mathematics) , image processing , algorithm , compression (physics) , line (geometry) , locality , code (set theory) , data compression , mathematics , mathematical analysis , geometry , computer vision , physics , philosophy , linguistics , set (abstract data type) , epistemology , thermodynamics , programming language , operating system
Space filling curve is used widely for linear mapping of multi-dimensional space. This provides a new line of thinking for various applications in image processing, Image compression being the most widely used. The paper highlights the locality preserving property of Hilbert Space filling curve which is essential in numerous applications such asin image compression, numerical analysis of a large aray of data, parallel processing and so on. A simplistic approach forusingHilbert Space filling curve using Scilab code has been presented.