Cornsweet surfaces for selective contrast enhancement
Autor: | Tania Pouli, Erik Reinhard, Jiri Kosinka, Neil A. Dodgson, Henrik Lieng |
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Přispěvatelé: | Lieng, H [0000-0001-6969-0108], Apollo - University of Cambridge Repository |
Rok vydání: | 2021 |
Předmět: |
Contrast enhancement
business.industry media_common.quotation_subject General Engineering Computer Graphics and Computer-Aided Design Luminance Human-Computer Interaction Computational photography Relative luminance Dimension (vector space) Robustness (computer science) Surface modelling Contrast (vision) Computer vision Artificial intelligence business Unsharp masking Mathematics media_common |
Popis: | A typical goal when enhancing the contrast of images is to increase the perceived contrast without altering the original feel of the image. Such contrast enhancement can be achieved by modelling Cornsweet profiles into the image. We demonstrate that previous methods aiming to model Cornsweet profiles for contrast enhancement, often employing the unsharp mask operator, are not robust to image content. To achieve robustness, we propose a fundamentally different vector-centric approach with Cornsweet surfaces. Cornsweet surfaces are parametrised 3D surfaces (2D in space, 1D in luminance enhancement) that are extruded or depressed in the luminance dimension to create countershading that respects image structure. In contrast to previous methods, our method is robust against the topology of the edges to be enhanced and the relative luminance across those edges. In user trials, our solution was significantly preferred over the most related contrast enhancement method. © 2014 Elsevier Ltd. |
Databáze: | OpenAIRE |
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