基于同态滤波与Curvelet变换的钻孔图像自适应增强  被引量:4

Borehole image adaptive enhancement based on homomorphic filtering and Curvelet transform

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作  者:何飞佳 李庆武[1,2] 韩辉[1] 张建清 谭显江 

机构地区:[1]河海大学物联网工程学院,江苏常州213022 [2]常州市传感网与环境感知重点实验室,江苏常州213022 [3]长江地球物理探测(武汉)有限公司,湖北武汉430010

出  处:《传感器与微系统》2017年第8期145-148,共4页Transducer and Microsystem Technologies

基  金:国家自然科学基金资助项目(41306089);江苏省重点研发计划资助项目(BE2016056);常州市科技支撑计划资助项目(CE20150068)

摘  要:针对岩石数字钻孔图像存在的光照不均、图像中岩石表面边缘细节模糊等情况,提出了一种钻孔图像自适应增强算法。对原图进行同态滤波;使用Curvelet变换分解原图与滤波后的图像,对两者的低频子带使用系数直方图匹配算法,将前者与后者的直方图进行匹配,改善光照不均的影响;对原图的高频子带使用自适应的阈值进行滤波,同时利用自适应增强函数进行增强;使用Curvelet反变换重构得到增强后的图像。实验结果表明:算法可以有效地改善钻孔图像光照不均的问题,增强图像中物体的边缘信息,在主观视觉效果和图像客观评价指标上相对于其他算法均有一定优势。To solve problems such as uneven illumination and fuzzy details of rock surface edge are shown in digital borehole images,an adaptive image enhancement algorithm is proposed. Firstly,homomorphic filtering is used to original image. Then,the original image and the filtered image are decomposed by Curvelet transform while the coefficient histogram matching algorithm is used for the low frequency subband of the two. The histogram of the former is matched with the latter to improve effect of illumination unevenness. Next,the high-frequency subband is filtered by an adaptive threshold and is enhanced with an adaptive enhancement function. Finally,the enhanced image is reconstructed by Curvelet inverse transform. The experimental results show that the illumination unevenness is improved effectively and the edge information is enhanced obviously. Certain advantages compared with other algorithms are shown in both subjective and objective evaluation indices.

关 键 词:钻孔图像 图像增强 CURVELET变换 系数直方图匹配 自适应增强 

分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]

 

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