Academic Journal of Computing & Information Science, 2024, 7(2); doi: 10.25236/AJCIS.2024.070203.
Zhang Huajian, Mu Dazhong
Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment, Beijing Institution of Graphic Communication, Beijing, China
In this paper, we present a halftone method based on invertible neural network (INN). We use the spectral features that halftone image dithering should have as constraints during training to allow the network to learn how to generate satisfactory halftone images. We use the original grayscale image as input during training, and use the halftone image generated through traditional error diffusion methods as the reference target. Our method outputs halftone images that preserve textual information that was not preserved in the error diffusion halftone method, enhancing the direct readability of the textual content that appears in the halftone images.
Halftone, Dithering, Invertible Neural Network, Deep Learning
Zhang Huajian, Mu Dazhong. A scene-text feature enhanced halftone method based on invertible neural network. Academic Journal of Computing & Information Science (2024), Vol. 7, Issue 2: 19-25. https://doi.org/10.25236/AJCIS.2024.070203.
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