New version of Gram-Schmidt Process with inverse for Signal and Image Processing

TL;DR

This paper presents an improved Gram-Schmidt Process with an inverse, tailored for digital signal and image processing, offering enhanced orthogonalization capabilities.

Contribution

The paper introduces an enhanced Gram-Schmidt Process with an inverse, specifically designed for improved performance in digital signal and image processing applications.

Findings

Enhanced process with inverse for better orthogonalization

Applicable to digital signal and image processing tasks

Potential for improved computational efficiency

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.