利用粒子群算法实现水泥μCT图像灰度校准  

PSO based grayscale correction for cement paste image gathered by μCT

作　　者：齐鲁[1] 杨波[1] 王琳[2] 

机构地区：[1]济南大学信息科学与工程学院,山东济南250022 [2]山东大学计算机科学与技术学院,山东济南250101

出　　处：《山东大学学报（理学版）》2010年第11期16-20,31,共6页Journal of Shandong University(Natural Science)

基　　金：国家973计划前期研究专项基金项目(2010CB635117);国家自然科学基金资助项目(60873089;60573065;60673130;90818001;F020804);山东省自然科学杰出青年基金资助项目(JQ200820)

摘　　要：由于X射线源的发射能量不稳定等原因,导致μCT扫描仪在不同时间对同一水泥水化浆体扫描时,同一物质线性衰减系数不同产生灰度差异。依据水泥水化理论和图像处理相关原理,利用粒子群算法(particle swarm optimization,PSO)优化区间范围参数,将待校准的水泥图像灰度范围重映射到相关区间,再对原始的灰度直方图曲线进行拉伸变换,直到待校准图像直方图两个波峰区域与参考图像直方图两个波峰区域对齐为止,从而达到不同时间的水泥图像是同一物质灰度校准的目的。When the μCT scans the same cement paste at different times, the grayscale of the same matter are different because that causes the unstable X-ray＇s emitted energy the different linear attenuation coefficient. According to the cement hydration principle and the theory of image processing, and using the particle swarm optimization（PSO） algorithm to optimize interval parameters＇ range, the grayscale was redirected to another interval, then the original histogram figure was stretched until the two wave crests between the float image histogram and the reference image histogram were aligned. Finally the grayscale correction would be realized.

关 键 词：灰度校准 粒子群算法 波峰对齐 μCT水泥图像 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]