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Hauptverfasser: Martinez, Axel, Olague, Gustavo, Hernandez, Emilio
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2409.06764
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author Martinez, Axel
Olague, Gustavo
Hernandez, Emilio
author_facet Martinez, Axel
Olague, Gustavo
Hernandez, Emilio
contents The primary purpose of this paper is to present the concept of dichotomy in image illumination modeling based on the power function. In particular, we review several mathematical properties of the power function to identify the limitations and propose a new mathematical model capable of abstracting illumination dichotomy. The simplicity of the equation opens new avenues for classical and modern image analysis and processing. The article provides practical and illustrative image examples to explain how the new model manages dichotomy in image perception. The article shows dichotomy image space as a viable way to extract rich information from images despite poor contrast linked to tone, lightness, and color perception. Moreover, a comparison with state-of-the-art methods in image enhancement provides evidence of the method's value.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06764
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Modeling Image Tone Dichotomy with the Power Function
Martinez, Axel
Olague, Gustavo
Hernandez, Emilio
Computer Vision and Pattern Recognition
Artificial Intelligence
Robotics
The primary purpose of this paper is to present the concept of dichotomy in image illumination modeling based on the power function. In particular, we review several mathematical properties of the power function to identify the limitations and propose a new mathematical model capable of abstracting illumination dichotomy. The simplicity of the equation opens new avenues for classical and modern image analysis and processing. The article provides practical and illustrative image examples to explain how the new model manages dichotomy in image perception. The article shows dichotomy image space as a viable way to extract rich information from images despite poor contrast linked to tone, lightness, and color perception. Moreover, a comparison with state-of-the-art methods in image enhancement provides evidence of the method's value.
title Modeling Image Tone Dichotomy with the Power Function
topic Computer Vision and Pattern Recognition
Artificial Intelligence
Robotics
url https://arxiv.org/abs/2409.06764