通过距离加权区域能量和结构张量在NSCT域中的多焦图像融合
Ming Lv1, Liangliang Li2, Qingxin Jin3
1College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
这项研究引入了一个新的多焦图像融合算法,使用距离加权区域能量和结构张量. 这种新的方法提高了融合多焦图像中的图像清晰度和信息内容.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
背景情况:
- 多焦图像融合旨在将不同焦平面的图像结合在一起.
- 现有的方法可能难以保存细节并实现高质量的融合.
研究的目的:
- 开发一个先进的多焦图像融合算法.
- 为了提高融合图像的清晰度和信息内容.
主要方法:
- 使用非子样本的轮变换域用于融合.
- 用于低频组件的使用距离加权区域能源.
- 应用于高频组件融合的结构张量.
- 集成的融合子频段使用反向非子样本的轮变换.
主要成果:
- 拟议的算法比现有的先进方法具有显著的优势.
- 在Lytro数据集上的实验结果显示出卓越的性能.
- 生成的融合图像表现出更高的清晰度和更丰富的信息.
结论:
- 开发的算法有效地融合了多焦图像.
- 该方法为高质量的图像融合应用提供了一个有前途的方法.
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