2D静止波形变形和2D双树DWT用于MRI脱
Mourad Talbi1, Brahim Nasraoui2, Arij Alfaidi2
1Center of Biotechnogy of Borj Cédria, Laboratory LMEEVED, Hammam-Lif, Tunisia.
Current medical imaging
|July 8, 2025
概括
本研究介绍了一种使用静止波段变换 (SWT 2-D) 和双树离散波段变换 (DWT) 的新型图像无色化方法. 拟议的方法有效地去除图像中的噪声,包括MRI,在关键指标上表现优于现有技术.
科学领域:
- 数字图像处理 数字图像处理
- 医疗成像医学成像
- 信号处理 信号处理
背景情况:
- 图像噪声是获取,传输和处理过程中不可避免的工件.
- 有效的降噪对于随后的图像分析和解释至关重要,特别是在磁共振图像 (MRI) 中.
- 现有的消噪方法在消除噪音和保存细节方面存在局限性.
研究的目的:
- 为噪音图像,包括MRI,提出和评估一种新的图像消噪方法.
- 通过有效地消除噪音,同时保持重要的图像特征来提高图像质量.
- 为了比较拟议方法的性能与已建立的除技术.
主要方法:
- 该方法使用静止波段变换 (SWT 2-D) 和2D双树离散波段变换 (DWT) 的组合.
- 噪音图像首先使用2D双树DWT转换,以获得波形系数.
- 然后使用基于SWT的2D技术来表示这些系数,然后用反向的2D双树DWT来重建被表示的图像.
主要成果:
- 与其他四种除技术相比,拟议的方法显示出更高的性能.
- 使用峰值信号与噪声比率 (PSNR),结构相似性 (SSIM),规范平均平方误差 (NMSE) 和特征相似性 (FSIM) 的定量评估证实了它的有效性.
- 该方法实现了更高的PSNR,SSIM和FSIM值,以及更低的NMSE值,表明更好的降噪和图像质量.
结论:
- 拟议的基于SWT的2D和2D双树DWT图像消除方法显著优于现有方法.
- 它有效地消除了灰度图像和MRI的噪音,图像细节的扭曲最小,特别是在中等噪音水平 (σ = 10,20).
- 虽然噪声降低在较高的噪声水平 (σ = 30,40) 上是显著的,但可能会出现一些轻微的扭曲,突出了消除噪声和保存细节之间的权衡.
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