Modeling Image Tone Dichotomy with the Power Function
This work addresses image analysis and processing challenges related to tone, lightness, and color perception, particularly in cases of poor contrast, but appears incremental as it builds on existing power function properties.
The paper tackled the problem of modeling image illumination dichotomy using a power function, proposing a new mathematical model that abstracts this dichotomy and showing its value through comparisons with state-of-the-art image enhancement methods.
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.