New version of Gram-Schmidt Process with inverse for Signal and Image Processing
Computer Vision and Pattern Recognition
2016-07-19 v1
Abstract
The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors, matrices, etc) into an orthonormal basis (a set of orthogonal, unit-length vectors, bi or tri dimensional matrices). The process consists of taking each array and then subtracting the projections in common with the previous arrays. This paper introduces an enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for Digital Signal and Image Processing, among others applications.
Keywords
Cite
@article{arxiv.1607.04759,
title = {New version of Gram-Schmidt Process with inverse for Signal and Image Processing},
author = {Mario Mastriani},
journal= {arXiv preprint arXiv:1607.04759},
year = {2016}
}
Comments
12 pages, 4 figures, 2 tables