基于Curve Let变换的X射线图像增强算法
Study of the X-Ray Image Enhancement Algorithm Based on Curve Let Transform
摘 要
为了提高了X射线图像的对比度和细节显示的清晰度, 应用基于Curve let变换的图像增强算法, 对原图像进行增强。试验结果表明, 该算法与直方图均衡化、同态滤波等算法相比, 有效地增强了对比度、抑制了背景噪声。相比之下, Curve let变换更具有优势。
X射线图像
图像增强
Curve let transform
Radiographic image
Image enhancement
Abstract
In order to improve the contrast and clarity of details of the radiographic images, the image enhancement algorithm based on Curve Let transform was applied to deal with the original images. The experimental results showed that this algorithm could effectively enhance contrast and control the background noise compared with other algorithms, such as homomorphism filter and histogram equalize. In contrast, Curve Let transform had more advantages.
中图分类号 TP391 TG115.28
所属栏目 科研成果与学术交流
基金项目
收稿日期 2009/7/6
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备注刘艳华(1985-), 女, 硕士研究生, 研究方向为数字图像处理及X射线实时成像。
引用该论文: LIU Yan-Hua,CHENG Yao-Yu,ZHANG Xiang-Bing. Study of the X-Ray Image Enhancement Algorithm Based on Curve Let Transform[J]. Nondestructive Testing, 2010, 32(4): 253～255
刘艳华,程耀瑜,张向兵. 基于Curve Let变换的X射线图像增强算法[J]. 无损检测, 2010, 32(4): 253～255
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参考文献
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【3】Chan H P, Vyborny C J. Digital mammography: ROC studies of the effects of pixel size and unsharp mask filtering on the detection of subtle microcalfications[J]. Invest Radiol, 1987, 22(7): 581-589.
【4】Candes E J, Donoho D L. Curve let: a surprisingly effective nonadaptive representation of objects with edges[EB/OL]. Nashville: Vanderbilt University Press, 1999. http: // www.stat stanford edu/~candes/papers/curvelet-SMStyle.pr2f.
【5】Candes E J, Donoho D L. Continuous Curve let transform: ⅡDiscretization into frames[J]. Appl Comput Harmon Anal, 2003(19): 198-222.
【6】Candes E J, Donoho D L. Continuous Curve let transform: ⅠResolution of the wave front set[J]. Appl Comput Harmon Anal, 2003(19): 162-197.
【7】Grossman A, Morlet J. Decomposition of hardy functions into square integrable wavelets of constant shape[J]. SIAM J Appl, 1984(15): 723-737.
【2】Hummel R. Image enhancement by histogram transformation[J]. Computer Graphics and Image Processing, 1977(6): 184-195.
【3】Chan H P, Vyborny C J. Digital mammography: ROC studies of the effects of pixel size and unsharp mask filtering on the detection of subtle microcalfications[J]. Invest Radiol, 1987, 22(7): 581-589.
【4】Candes E J, Donoho D L. Curve let: a surprisingly effective nonadaptive representation of objects with edges[EB/OL]. Nashville: Vanderbilt University Press, 1999. http: // www.stat stanford edu/~candes/papers/curvelet-SMStyle.pr2f.
【5】Candes E J, Donoho D L. Continuous Curve let transform: ⅡDiscretization into frames[J]. Appl Comput Harmon Anal, 2003(19): 198-222.
【6】Candes E J, Donoho D L. Continuous Curve let transform: ⅠResolution of the wave front set[J]. Appl Comput Harmon Anal, 2003(19): 162-197.
【7】Grossman A, Morlet J. Decomposition of hardy functions into square integrable wavelets of constant shape[J]. SIAM J Appl, 1984(15): 723-737.
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