Modeling Image Tone Dichotomy with the Power Function
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 47 references that are in the map. First posted on arXiv 10 Sep 2024.
Builds on
8 of 47 references.
References · 8
- 2020Pre-Trained Image Processing Transformercited by 893
- 2018Deep Retinex Decomposition for Low-Light Enhancementcited by 723
- 2019EnlightenGAN: Deep Light Enhancement without Paired Supervisioncited by 466
- 2020Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancementcited by 303
- 2022Highly Accurate Dichotomous Image Segmentationcited by 110
- 2020DeepLPF: Deep Local Parametric Filters for Image Enhancementcited by 107
- 2023Low-Light Image Enhancement with Illumination-Aware Gamma Correction and Complete Image Modelling Networkcited by 33
- 2023Adversarial Attacks Assessment of Salient Object Detection via Symbolic Learningcited by 1
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Citing papers per year: 2024: 1.
1 paper.