Color Image Enhancement In the Framework of Logarithmic Models

TL;DR

This paper introduces a novel logarithmic mathematical model for color image processing, transforming color spaces into a Euclidean space to improve image enhancement techniques with experimental validation.

Contribution

It develops a new logarithmic vector space model for color images, enabling enhanced processing and analysis compared to traditional methods.

Findings

The model effectively enhances color images.

Experimental results demonstrate improved image quality.

The logarithmic approach offers a new perspective for color processing.

Abstract

In this paper, we propose a mathematical model for color image processing. It is a logarithmical one. We consider the cube (-1,1)x(-1,1)x(-1,1) as the set of values for the color space. We define two operations: addition <+> and real scalar multiplication <x>. With these operations the space of colors becomes a real vector space. Then, defining the scalar product (.|.) and the norm || . ||, we obtain a (logarithmic) Euclidean space. We show how we can use this model for color image enhancement and we present some experimental results.