An Enhancement Method for X-Ray Image Using Rough Sets and Human Visual System

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An Enhancement Method for X-Ray Image Using Rough Sets and Human Visual System

更新时间：2025-05-08

- An Enhancement Method for X-Ray Image Using Rough Sets and Human Visual System
- Vol. 43, Issue 6, Pages: 48-51+56(2009)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 June 2009，
  
  Published：2009
- 稿件说明：
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An Enhancement Method for X-Ray Image Using Rough Sets and Human Visual System[J]. 2009, 43(6): 48-51+56.
DOI：

An Enhancement Method for X-Ray Image Using Rough Sets and Human Visual System[J]. 2009, 43(6): 48-51+56. DOI：

摘要

针对X射线图像的低亮度及噪声造成的图像对比度差和图像模糊的问题

提出了一种采用粗糙集理论和人眼视觉系统特性的图像增强算法(HREM). 先将原始图像进行灰度拉伸

再结合人眼视觉系统特性

利用粗糙集理论将图像分成边缘细节图像和平滑图像

然后对边缘细节图像做指数变换增强

对平滑图像做直方图均衡化

最后将处理好的两子图进行重叠

同时消除重叠后图像的随机脉冲噪声. 实验结果表明

HREM方法不仅能较好地保持图像的边缘细节信息

有效地增强原图像的对比度

而且消噪能力强

整体视觉效果好.

Abstract

The X-ray image from direct digital radiography system is captured in non-uniform and low illumination conditions

and is blurred by noise. A new enhancing method is proposed on the basis of rough set theory and human visual system(HREM). The grays of the original image are stretched

and then the stretched image is used to generate two new images(edge-detail image and smooth image)using the rough set theory and the human visual system. The edge-detail and smooth images are enhanced by the exponential transform and histogram equalization

respectively. Finally

the two enhanced images are overlapped into one image

and the random impulse noise in the overlapped image is reduced. Experimental results show that the HREM method can suppress noise while preserving edge and detail element

and enhance visual effect effectively.

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Keywords

references

Xi'an Xijing Optical & Electrical Instrument Co.Ltd.CCD-DDR system [EB/OL].(2006-03-06)[2008-10-15].http:∥www.xjoptics.com/product_list/PL_6.htm.

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

YANG Ying, MOU Xuanqin,ZHANG Min, et al. A technique for extending dynamic range of medical X-ray image[J]. Journal of Xi'an Jiaotong University, 2008,42(12):1468-1471.

刘鹏. 基于小波变换的X射线图像增强技术[J]. 中北大学学报(自然科学版), 2007,28(6): 552-555.

LIU Peng. An enhancement technology for X-ray images based on wavelet transform [J]. Journal of North University of China(Natural Science Edition), 2007,28(6): 552-555.

付丽琴, 韩焱, 桂志国. 射线图像的对比度增强方法[J]. 无损检测, 2005, 27(9):485-486.

FU Liqin, HAN Yan, GUI Zhiguo. Contrast enhancement algorithms for radiographic image[J]. Non-Destructive Testing, 2005, 27(9):485-486.

陈德刚,张文修. 粗糙集和拓扑空间[J]. 西安交通大学学报, 2001,35(12):1313-1315.

CHEN Degang, ZHANG Wenxiu. Rough sets and the topological space [J]. Journal of Xi'an Jiaotong University, 2001,35(12):1313-1315.

PAWLAK Z. Rough sets, rough relation and rough functions [J]. Fundament Informaticae,1996,27(8):2-3.

COMES S, MACQ B. Human visual quality criterion [C]∥ Proceedings of SPIE Visual Communication and Image Processing. Bellingham, WA, USA: The International Society of Optical Engineering, 1990:2-13.

KARUNASEKERA S A, KINGSBURG N G. A distortion measure for blocking artifacts in images based on human visual sensitivity [J]. IEEE Transactions on Image Processing,1995,4(6):713-724.

LI T L, SUNDAREHAN M K. Adaptive image contrast enhancement based on human visual properties[J]. IEEE Trans Medical Imaging,1994,13(4):573-586.

张雷,董德存.人眼视觉特性引入粗糙集图像增强的研究与仿真[J].计算机应用与软件,2004,21(12):72-74.

ZHANG Lei,DONG Decun. Study and simulations of vision performance applied in rough sets image enhancement [J]. Computer Applications and Software, 2004,21(12):72-74.

SCHULTE S, DE WITTEE V, NACHTEGAEL M, et al. Fuzzy random impulse noise reduction method [J]. Fuzzy Sets and Systems, 2007,158(3):270-283.

VQEG. Final report from the video quality experts group on the validation of objective models of video quality assessment [R/OL].(2000-04-01)[2008-08-25].http:∥www.its. bldrdoc. gov/vqeg/projects/frtv_phaseⅡ/downloads/VQEGⅡ_Final_ Peport.pdf.

周景超, 戴汝为,肖柏华. 图像质量评价研究综述[J]. 计算机科学,2008,35(7):1-4.

ZHOU Jingchao, DAI Ruwei,XIAO Baihua. Overview of image quality assessment research[J]. Computer Science,2008,35(7):1-4.

SHEIKH H R, SABIR M F, BOVIK A C, et al. A statistical evaluation of recent full reference image quality assessment algorithms [J]. IEEE Transactions on Image Processing, 2006,15(11):3441-3451.

韦学辉, 李均利, 陈刚.一种图像感知质量评价模型[J]. 计算机辅助设计与图形学学报,2007,19(12):1540-1545.

WEI Xuehu, LI Junli, CHEN Gang. A perception based image quality assessment mode [J]. Journal of Computer-Aided Design Computer Graphics, 2007, 19(12):1540-1545.

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