Nonlinear Multi-Scale Contrast Enhancement for X-Ray Chest Radiography

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Nonlinear Multi-Scale Contrast Enhancement for X-Ray Chest Radiography

更新时间：2025-07-09

- Nonlinear Multi-Scale Contrast Enhancement for X-Ray Chest Radiography
- Vol. 44, Issue 6, Pages: 83-87(2010)
- 作者机构：
  
  西安交通大学图像处理与模式识别研究所,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.73
- Online First：10 June 2010，
  
  Published：2010
- 稿件说明：
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Nonlinear Multi-Scale Contrast Enhancement for X-Ray Chest Radiography[J]. 2010, 44(6): 83-87.
DOI：

Nonlinear Multi-Scale Contrast Enhancement for X-Ray Chest Radiography[J]. 2010, 44(6): 83-87. DOI：

摘要

针对医学X射线胸片增强的同时会在大尺度边缘产生伪影从而影响医学诊断的问题

提出了一种基于边缘的非线性X射线胸片增强算法(MSCE).该算法先将图像进行多尺度分解

然后结合人眼视觉对对比度敏感的感知特性

计算图像基于边缘的局部对比度

通过结合其局部对比度信息控制各尺度信号增强系数

最后重建得到增强后的图像.MSCE算法能在保证小信号增强能力的同时

较大限度地抑止大尺度信号边缘伪影.实验结果表明

与Vuylsteke以及Stahl的非线性增强算法相比

在保证同样细节增强能力的同时

其大尺度边缘区的平均局部方差分别下降了约36.78%和29.64%

实验验证了MSCE算法具有优越的整体视觉质量.

Abstract

An algorithm for multi-scale nonlinear X-ray chest radiography contrast enhancement based on edge(MSCE)is presented to overcome the drawback of introducing visible artifacts in conventional methods. Images are decomposed within the multi-scale decomposition architecture

and then local contrast of images is obtained based on edge information. The enhancement coefficient is calculated from image's local contrast information

and the enhanced image is then obtained. The MSCE algorithm can provide a smooth enhancement of large structures to avoid these visible artifacts

and to maintain the same detail enhancement ability. Experimental results show that the average local variance in the edge region(ALVE)decreases about 36.78% and 29.64% with almost the same detail enhancement ability comparing with the Vuylsteke and Stahl's methods

and that the proposed method can achieve better perceptual quality.

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references

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人眼视觉特性与粗糙集结合的X射线图像增强算法.西安交通大学学报, 2009, 43(6): 48-51.

基于小波变换的扩散滤波模型数值解的收敛性.西安交通大学学报, 2009, 43(4): 121-124.

一种医学X射线图像动态范围扩展方法.西安交通大学学报, 2008, 42(12): 1468-1471.

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