再生过器:增强马赛克算法用于近盐和胡降低噪声
Ratko M Ivković1, Ivana M Milošević2, Zoran N Milivojević3
1Department of Software Engineering, Faculty of Economics and Engineering Management in Novi Sad, Cvecarska 2, 21000 Novi Sad, Serbia.
Sensors (Basel, Switzerland)
|January 11, 2025
概括
这项研究引入了一种新的再生过器,有效地从图像中去除盐和胡 (nS&P) 附近的噪音. 过器保留图像细节,即使在97%的噪音密度下也保持质量.
科学领域:
- 图像处理 图像处理
- 计算机视觉 计算机视觉 计算机视觉
- 数字信号处理是数字信号处理.
背景情况:
- 数字图像通常会受到噪音的破坏,例如近盐和胡 (nS&P) 噪音,这降低了视觉质量并阻碍了分析.
- 传统的降噪过器可能会模糊图像细节或无法有效消除高密度噪声.
- 现有的方法通常依赖于中位数或其他复杂的过技术,需要采用替代方法.
研究的目的:
- 开发和展示一种新的再生过器,以有效和选择性地从数字图像中去除nS&P噪声.
- 为了证明过器在降噪过程中保持图像结构细节的能力.
- 提供一种强大的图像消噪方法,其性能优于传统技术,特别是在高噪声条件下.
主要方法:
- 提出了一个新的再生过器,重点是通过局部上下文分析恢复受噪声影响的像素.
- 过器采用代处理方法,旨在避免随着代的增加而导致图像质量下降.
- 性能评估是使用标准图像质量评估指标和实验性比较进行的.
主要成果:
- 再生过器有效地减少了nS&P噪声,同时保持了基本的图像结构.
- 过器表现出强度和一致的高质量结果,即使噪声密度高达97%.
- 代处理不会对图像质量产生负面影响,即使在高噪音水平下也是如此.
结论:
- 拟议的再生过器为数字图像中的nS&P降噪提供了一种卓越的方法.
- 过器能够保存细节并处理极端噪音水平的能力使其成为图像处理中的一个有价值的工具.
- 公开存储库中的代码和数据可用性确保了透明度并促进了进一步的研究.
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