Color Image Enhancement In the Framework of Logarithmic Models
This work addresses color image processing for applications like photography or computer vision, but it appears incremental as it builds on existing logarithmic models without claiming major breakthroughs.
The authors tackled the problem of color image enhancement by proposing a logarithmic mathematical model that transforms the color space into a Euclidean vector space, and they presented experimental results demonstrating its application.
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.