一个2D图像的3D重建函数自适应性消噪算法
Feng Wang1, Weichuan Ni1, Shaojiang Liu1
1Guangzhou Xinhua University, Dongguan, Guangdong, China.
PeerJ. Computer science
|October 9, 2023
概括
本研究引入了适应性无色化算法用于3D重建,保存图像细节通常在传统方法中丢失. 这种新的方法提高了对2D图像的噪声免疫力和3D模型保真度.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 三维重建的3D重建
背景情况:
- 图像消除算法经常在降噪过程中模糊关键细节.
- 从二维图像进行3D重建面临着噪音和细节保存方面的挑战.
研究的目的:
- 开发一种适应性无色化算法,用于二维图像的3D重建.
- 为了保存通常被常规无色化方法所损害的精细图像细节.
- 为了提高3D模型的噪声免疫力和真实性,这些模型是从杂的2D图像中获得的.
主要方法:
- 基于区域值的图像细分.
- 为背景地区表示的门.
- 针对目标地区的对抗性生成网络处理.
- 从处理的2D目标图像中生成3D模型.
主要成果:
- 实现了超过95%的平均降噪.
- 从原始图像中成功保留了重要的特征信息.
- 在实验测试中证明了图像细节的稳定保存.
- 评估了重建保真度和降噪效果.
结论:
- 拟议的自适应性消噪算法在3D重建过程中有效地保存图像细节.
- 这种方法为2D到3D图像转换中的降噪挑战提供了有希望的解决方案.
- 提高最终3D模型中的图像质量和目标信息保真度.
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