Micro-scale searching algorithm for high-resolution image matting
Natural image matting based on pixel pair optimization is commonly employed during image post-processing. However, obtaining high-quality alpha mattes for high-resolution images via existing image matting methods is challenging as it typically requires considerable computational resources. In this p...
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Veröffentlicht in: | Multimedia tools and applications 2024-04, Vol.83 (13), p.38931-38947 |
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creator | Feng, Fujian Gou, Hongshan Liang, Yihui Feng, Le Tan, Mian Huang, Han Wang, Lin |
description | Natural image matting based on pixel pair optimization is commonly employed during image post-processing. However, obtaining high-quality alpha mattes for high-resolution images via existing image matting methods is challenging as it typically requires considerable computational resources. In this paper, we design a novel optimization information transmission strategy that can be applied to images of different resolutions to improve the quality of the transmitted information required for evolutionary optimization. In addition, we propose a micro-scale searching matting algorithm, which allows us to obtain high-quality matting for high-resolution images with limited computational resources. To verify the applicability of the proposed algorithm for high-resolution images, experiments were conducted on the alpha matting benchmark dataset. Experimental results show that the proposed micro-scale searching matting algorithm can estimate high-quality alpha mattes without incurring excessive computational resources. Moreover, the proposed algorithm outperforms the state-of-the-art optimized matting algorithms when applied to high-resolution images. |
doi_str_mv | 10.1007/s11042-023-17157-0 |
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However, obtaining high-quality alpha mattes for high-resolution images via existing image matting methods is challenging as it typically requires considerable computational resources. In this paper, we design a novel optimization information transmission strategy that can be applied to images of different resolutions to improve the quality of the transmitted information required for evolutionary optimization. In addition, we propose a micro-scale searching matting algorithm, which allows us to obtain high-quality matting for high-resolution images with limited computational resources. To verify the applicability of the proposed algorithm for high-resolution images, experiments were conducted on the alpha matting benchmark dataset. Experimental results show that the proposed micro-scale searching matting algorithm can estimate high-quality alpha mattes without incurring excessive computational resources. 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subjects | Algorithms Computer Communication Networks Computer Science Data Structures and Information Theory Design optimization Editing High resolution Image quality Image resolution Mattes Methods Multimedia Multimedia Information Systems Optimization Propagation Search algorithms Software Special Purpose and Application-Based Systems |
title | Micro-scale searching algorithm for high-resolution image matting |
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