LDCT Image Enhancement Algorithm Based on Modified SSR

doi:10.3969/j.issn.1000-3428.2011.04.086

Abstract

Abstract: In order to improve the intensity and contrast qualities of CT images and reduce the image noise in clinic application, this paper proposes a modified Low-Dose CT(LDCT) images contrast enhancement algorithm based on Single-Scale Retinex(SSR). Different from the classical Retinex methods estimate the illumination image in a complex way, the proposed algorithm estimates the illumination image approximately, and does the reflectance image in a nonlinear way to amplify and emphasize these details. Experimental results show that the proposed method avoids more complex implementations and yields better performance of LDCT image enhancement over the conventional histogram equalization, the Frankle-McCann Retinex algorithm and McCann99 Retinex algorithm.

Key words: contrast enhancement, Low-Dose CT(LDCT), Retinex theory, SSR model, illumination image, reflectance image

摘要： 针对低剂量CT扫描(LDCT)的灰度动态范围宽、对比度差以及图像噪声增加问题，提出一种改进的LDCT影像增强算法。在对经典单尺度Retinex进行研究的基础上，论述该算法的原理和实现方法，并通过实验与改进的直方图均衡化算法以及Frackle-McCann Retinex算法、McCann99 Retinex算法进行比较。实验分析结果表明，该算法对于LDCT影像对比度增强较一般的图像增强算法具有更好的处理效果，能够满足医生临床诊断的要求。

关键词: 对比度增强, LDCT影像, Retinex理论, SSR模型, 亮度图像, 反射图像

CLC Number:

TN391

JIE Zhi-Bin, YA Pei-Yu. LDCT Image Enhancement Algorithm Based on Modified SSR[J]. Computer Engineering, 2011, 37(4): 238-240.

解志斌, 颜培玉. 基于改进SSR的LDCT影像增强算法[J]. 计算机工程, 2011, 37(4): 238-240.

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URL:

https://www.ecice06.com/EN/Y2011/V37/I4/238

References

[1] 马银平, 江伟. 基于局部均值和标准差的图像增强算法[J]. 计算机工程, 2009, 35(22): 205-206. [2] Land E H. The Retinex Theory of Color Vision[J]. Scientific American, 1977, 237(6): 108-128. [3] Rahman Z, Woodell G A, Jobson D J. Retinex Image Enhancement: Applications to Medical Images[C]//Proc. of NASA Medical Imaging Conference. Greenbelt, Maryland, USA: [s. n.], 2001: 1-24. [4] Iqbal N. Automatic Enhancement of Chest Radiography Using Retinex Processing[C]//Proc. of the International Multi Topic Conference. [S. l.]: IEEE Press, 2002: 27-31. [5] Rahman Z, Woodell G A, Jobson D J. Retinex Processing for Automatic Image Enhancement[J]. Journal of Electronic Imaging, 2004, 13(1): 100-110. [6] Jobson D J, Rahman Z, Woodell G A. Properties and Performance of the Center/Surround Retinex[J]. IEEE Trans. on Image Processing, 1997, 6(3): 451-462. [7] Jobson D J, Rahman Z, Woodell G A. A Multiscale Retinex for Bridging the Gap Between Color Images and the Human Observation of Scenes[J]. IEEE Trans. on Image Processing, 1997, 6(7): 965-976. [8] Li Tao, Asari V. Modified Luminance Based MSR for Fast and Efficient Image Enhancement[C]//Proc. of the 32nd Applied Imagery Pattern Recognition Workshop. [S. l.]: IEEE Press, 2003: 174-179. [9] Choi D H, Jang I H, Kim M H, et al. Color Image Enhancement Based on Single-scale Retinex with a JND-based Nonlinear Filter[C]//Proc. of International Symposium on Circuits and Systems. [S. l.]: IEEE Press, 2007: 3948-3951. [10] Yu Zeyun, Bajaj C. A Fast and Adaptive Method for Image Contrast Enhancement[C]//Proc. of International Conference on Image Processing. Singapore: [s. n.], 2004: 1001-1004. [11] Funt B, Ciuera F, McCann J. Retinex in Matlab[J]. Journal of Electronic Imaging, 2004, 13(1): 48-57.

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