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基于卷积的图像轻度处理的优化
D Andrew Rowlands1, Graham D Finlayson1
1Colour & Imaging Lab, School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK.
Journal of imaging
|August 28, 2024
概括
对卷积视网膜的新统计方法客观地减轻了使用自相关统计数据的图像阴影. 这种方法优化了封闭形式的过器,改善了图像处理,没有主观增强.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 统计建模 统计建模
背景情况:
- 卷积视网膜方法使用中心/周围运算符来减少阴影和动态范围.
- 现有的方法经常调整视觉吸引力的参数,并包括增强功能,如对数映射.
研究的目的:
- 介绍和详细介绍基于自相关统计的卷积视网膜的统计方法.
- 在没有主观图像增强组件的情况下客观地减轻阴影.
主要方法:
- 模拟图像白度和阴影的自相关矩阵.
- 解决线性回归以获得封闭形式的最佳过器.
- 分析自相关性矩阵形状对最佳波器形状的影响.
主要成果:
- 统计方法产生了一个客观最优的过器.
- 在从文本文档中删除阴影的证明有效性.
- 在具有挑战性的图像数据集上验证了性能.
结论:
- 统计卷积视网膜方法提供了一个客观的方法来缓解阴影.
- 自相关统计对于确定最佳波器特性至关重要.
- 该方法对包括文档分析在内的各种图像处理应用具有前景.
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