Dynamic Orthonormalization of Color Spaces

Dynamic Orthonormalization of Color Spaces: A Matrix Algebra Approach for Enhanced Signal Separation Douglas C. Youvan doug@ March 23, 2024 In the domain of digital imaging and analysis, the challenge of distinguishing between closely overlapping signals—whether they arise from natural scenes, biological specimens, or artistic endeavors—remains a pivotal concern. “Dynamic Orthonormalization of Color Spaces: A Matrix Algebra Approach for Enhanced Signal Separation“ introduces a sophisticated technique grounded in matrix algebra, designed to transform color spaces dynamically, thus enabling the separation and clarification of such overlapping signals. By leveraging the principles of orthonormalization, this method not only promises to refine signal analysis across various applications but also to revolutionize image processing by offering an adaptable, precise tool for enhancing signal distinction. This paper explores the theoretical underpinnings of the technique, details its practical implementation, and underscores its broad applicability through a range of examples, inviting further exploration and innovation in this promising field.