一个新的混合图像消噪算法,使用自适应和修改的基于决策的过器,以提高图像质量
Faiz Ullah1, Kamlesh Kumar2, Tariq Rahim3
1School of Computing, Gachon University, Seongnam, 13120, Republic of Korea.
Scientific reports
|March 16, 2025
概括
本研究介绍了一种使用自适应中位过器 (AMF) 和修改决策基中位过器 (MDBMF) 的混合图像消除算法. 这种新的方法有效地减少噪音,同时保持图像边缘,优于现有的技术.
科学领域:
- 数字图像处理 数字图像处理
- 计算机视觉 计算机视觉
- 信号处理 信号处理
背景情况:
- 传统的图像消除方法与计算复杂性,过度平滑和保存边缘等关键细节作斗争.
- 有效的降噪对于恢复数字图像的视觉质量和结构完整性至关重要.
研究的目的:
- 引入一种混合无声算法,该算法结合了自适应中间波器 (AMF) 和修改的基于决策的中间波器 (MDBMF).
- 通过保护边缘和有效减少噪音来解决传统方法的局限性.
主要方法:
- 一个混合无噪点算法,集成AMF用于动态窗口调整和MDBMF用于选择性像素恢复.
- 在9个基准图像上进行测试,包括标准和医疗数据集 (胸部,肝脏),噪声密度不同 (10-90%).
主要成果:
- 混合方法在主观和客观分析中明显优于最先进的方法.
- 量化指标显示有所改善:PSNR高达2.34dB,IEF高达20%,MSE高达15%,SSIM高达0.07dB.
- FOM和VIF指标分别达到0.68和0.61,显示出卓越的表现.
结论:
- 拟议的混合消噪算法在降噪方面提供了卓越的性能,同时保留了图像细节,特别是边缘.
- 这种方法在标准和医疗成像应用中比现有无色化技术提供了显著的进步.
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