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基于ACE-GPM的低亮度雾噪声图像消除方法
Wuyi Li1, Guanglu Zhou1, Xingjian Wang1
1College of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
PloS one
|May 7, 2024
概括
本研究介绍了ACE-GPM,这是一个先进的图像消噪算法,可以增强对比度并有效地消除噪声. 它比现有方法更好地保留图像细节和纹理,提供更好的质量,更低的计算成本.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 信号处理 信号处理
背景情况:
- 佩罗纳-马利克 (P-M) 模型在图像无声化中存在噪声放大和渐变问题.
- 现有的方法在噪音,低光图像中的对比度增强和细节保存方面扎.
研究的目的:
- 开发一个改进的图像消除算法,解决PM模型的局限性.
- 为了增强对比度,去除噪音,并保留细节在退化图像.
主要方法:
- 集成自动色彩均等 (ACE) 进行对比增强.
- 应用Otsu方法用于精确的图像细分.
- 使用梯度调整的P-M模型与梯度下降,以消除噪音.
- 使用增强功能来突出前景和背景细节.
主要成果:
- 与其他方法相比,ACE-GPM算法显著改善了对比度和降噪.
- 图像细节和纹理信息的保存,信息的0.42增加表明.
- 降低了计算资源支出,同时保持了高图像质量.
结论:
- 在图像消除,对比度增强和细节保存方面,ACE-GPM提供了卓越的性能.
- 该算法为处理噪音和低光图像提供了高效的解决方案.
- 这种方法有效地克服了传统的PM模型的缺陷.
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