采用聚类分割和直方图均衡的图像增强算法
Image enhancement using clustering and histogram equalization
查看参考文献11篇
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文摘
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针对现有直方图均衡化算法难以兼顾图像细节增强和噪声抑制问题,提出了一种基于聚类分割和直方图均衡的图像增强算法。引入模糊C均值聚类(FCM)算法将低通滤波后的图像分成若干类,并利用原图的边缘信息和形态学操作修正聚类结果;根据各类的均值和标准差确定映射后的动态范围,对其进行直方图均衡化处理;采用平滑滤波方法消除类间的边界效应。实验结果表明:经过该算法处理后的图像,对比度得到明显增强,噪声得到有效抑制。该方法不但可用于图像增强,还可用于图像动态范围压缩,具有广泛的应用前景。 |
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其他语种文摘
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It was difficult for the conventional HE methods to give consideration to restraining noise while emphasizing features. A novel image enhancement technique based on image segment by clustering and histogram equalization was proposed to overcome the drawback. The input image was smoothed by a Gaussian filter, and the fuzzy C-means clustering algorithm was used to segment the low-pass image into several partitions, and then the edge information and morphological operations were used to fix the segmentation result. Each partition was assigned to a new dynamic range according to its mean and standard deviation. Based on the dynamic range, the histogram equalization process was applied independently to these partitions. Smooth filtering was applied to eliminate the blocking-effect. The results of experiments showed that been processed by the proposed algorithm, the contrast was significantly enhanced and noise was effectively suppressed. The proposed algorithm not only can be used for image enhancement, but also can be used for dynamic range compression, so it has broad application prospects. |
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来源
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红外与激光工程
,2012,41(12):3436-3441 【核心库】
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关键词
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图像增强
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图像分割
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直方图均衡
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模糊C均值聚类
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地址
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1.
中国科学院沈阳自动化研究所, 中国科学院光电信息处理重点实验室, 辽宁, 沈阳, 110016
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清华大学电子工程系, 北京, 100084
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语种
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中文 |
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ISSN
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1007-2276 |
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学科
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电子技术、通信技术 |
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基金
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国家973计划
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文献收藏号
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CSCD:4751041
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参考文献 共
11
共1页
|
|
1.
Gonzalez R C.
Digital Image Processing. (2nd ed),2002
|
被引
4
次
|
|
|
|
|
2.
Kaur M. Survey of contrast enhancement techniques based on histogram equalization.
International Journal of Advanced Computer Science and Applications,2011,2(7):138-141
|
被引
2
次
|
|
|
|
|
3.
曹聚亮. 基于自适应局部灰度修正的直方图均衡算法.
红外与激光工程,2004,33(5):513-515
|
被引
16
次
|
|
|
|
|
4.
Kim T K. Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering.
IEEE Trans on Consumer Electronics,1998,44(1):82-86
|
被引
38
次
|
|
|
|
|
5.
Kim J Y. An advanced contrast enhancement using partially overlapped sub-block histogram equalization.
IEEE Transactions on Circuits and Systems for Video Technology,2001,11(4):475-484
|
被引
124
次
|
|
|
|
|
6.
Cai W L. Fast and robust fuzzy c-means clustering algorithm incorporating local information for image segmentation.
Pattern Recognition,2007,40(7):825-838
|
被引
100
次
|
|
|
|
|
7.
刘尊洋. 塔型FCM和CIEDE2000的仿造迷彩主色提取方法.
红外与激光工程,2010,39(2):367-371
|
被引
6
次
|
|
|
|
|
8.
于天河. 结合人眼视觉特性的红外图像增强新技术.
红外与激光工程,2008,37(6):951-954
|
被引
13
次
|
|
|
|
|
9.
Land E. An alternative technique for the computation of the designator in the retinex theory of color vision.
Proc Nat Acad Sci,1986,83:3078-3080
|
被引
67
次
|
|
|
|
|
10.
Jobson D J. A multi-scale retinex for bridging the gap between color images and the human observation of scenes.
IEEE Transactions on Image Processing: Special Issue on Color Processing,1997,6(7):965-976
|
被引
332
次
|
|
|
|
|
11.
Karunasekera S A. A distortion measure for blocking artifacts in image based on human visual sensitivity.
IEEE Trans Image Processing,1995,4(6):713-724
|
被引
22
次
|
|
|
|
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