[1]沈瑜,党建武,王阳萍,等.基于MSTO的含噪声多传感器图像融合算法[J].东南大学学报(自然科学版),2017,47(6):1101-1106.[doi:10.3969/j.issn.1001-0505.2017.06.004]
 Shen Yu,Dang Jianwu,Wang Yangping,et al.Fusion algorithm with multi-sensor noisy image based on MSTO[J].Journal of Southeast University (Natural Science Edition),2017,47(6):1101-1106.[doi:10.3969/j.issn.1001-0505.2017.06.004]
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基于MSTO的含噪声多传感器图像融合算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
47
期数:
2017年第6期
页码:
1101-1106
栏目:
计算机科学与工程
出版日期:
2017-11-20

文章信息/Info

Title:
Fusion algorithm with multi-sensor noisy image based on MSTO
作者:
沈瑜党建武王阳萍王小鹏郭瑞
兰州交通大学电子与信息工程学院, 兰州 730070
Author(s):
Shen Yu Dang Jianwu Wang Yangping Wang Xiaopeng Guo Rui
School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
关键词:
多尺度顺序开关算子 Beamlet算子 融合 多传感器图像
Keywords:
multi-scale sequential toggle operator Beamlet operator fusion multi-sensor image
分类号:
TP391
DOI:
10.3969/j.issn.1001-0505.2017.06.004
摘要:
为了解决在含噪声多源传感器图像融合中,常规滤波存在图像边缘缺失、对比度差的缺点,提出了一种基于多尺度顺序开关算子(multi-scale sequential toggle operator, MSTO)和Beamlet保边滤波算子的含噪声红外与可见光图像融合算法.首先,将多源图像通过MSTO进行多尺度分解,得到能量分量和细节分量.对于细节分量采用Beamlet保边滤波算子进行处理,保持图像边缘细节的同时滤除噪声,采用MSTO计算出能量图像的亮边缘和暗边缘并融合叠加到细节分量中,进一步增强融合图像的边缘.对于能量分量采用基于灰度值取大的融合规则.最后根据MSTO反变换对融合后的能量分量和细节分量进行重构,得到结果图像.实验结果表明,融合后的图像不但滤除了噪声,而且对轮廓和边缘细节得到较完整的提取和增强.该图像融合算法在含噪声多源传感器的融合中取得较好的效果.
Abstract:
In the multi-sensor noisy image fusion, it was easy to obtain the fused images with loss of image edges and low image contrast based on the general filter methods. A novel fusion algorithm with noisy infrared and visible light images was proposed based on a multi-scale sequential toggle operator(MSTO)and an improved bilateral filter method. First, the energy component and the detail component were obtained by MSTO multi-scale decomposition. The detail component was processed by Beamlet operator to filter noises while keeping edge information on the images. Then, the bright edge image and dark edge image with the energy image were calculated by MSTO, and added to the detail component to enhance edges. The maximum rule was used in the energy component fusion. MSTO inverse transform was used to decompose the fused detail component and the energy component. The experimental results show that method filters the noise, and extracts and enhances the contour and the edge details. The image fusion algorithm is effective in the multi-sensor noisy image fusion.

参考文献/References:

[1] Ardeshir Goshtasby A, Nikolov S. Image fusion: Advances in the state of the art[J]. Information Fusion, 2007, 8(2): 114-118. DOI:10.1016/j.inffus.2006.04.001.
[2] Toet A, Hogervorst M A, Nikolov S G, et al. Towards cognitive image fusion[J]. Information Fusion, 2010, 1(2): 95-113. DOI:10.1016/j.inffus.2009.06.008.
[3] 李光鑫, 徐抒岩, 董吉洪. 结构优化型颜色传递融合方法[J]. 电子学报, 2011, 39(1): 213-218.
  Li Guangxin, Xu Shuyan, Dong Jihong. Architecture optimized version color transfer based fusion method[J]. Acta Electronica Sinica, 2011, 39(1): 213-218.(in Chinese)
[4] 郭峰, 杨静, 史健芳. 基于可控滤波器和空间频率的图像融合算法[J]. 计算机工程与设计, 2016,37(8): 2165-2169. DOI:10.16208/j.issn1000-7024.2016.08.035.
Guo Feng, Yang Jing, Shi Jianfang. Image fusion algorithm based on steerable filters and spatial frequency[J]. Computer Engineering and Design, 2016, 37(8): 2165-2169. DOI:10.16208/j.issn1000-7024.2016.08.035. (in Chinese)
[5] Mahbubur Rahman S M, Omair Ahmad M, Swamy M N S. Contrast-based fusion of noisy images using discrete wavelet transform[J]. IET Image Processing, 2010, 4(5): 374-384. DOI:10.1049/iet-ipr.2009.0163.
[6] Wang Xin, Wang Ying. A new focus measure for fusion of multi-focus noisy images[C]//International Conference on Computer, Mechatronics, Control and Electronic Engineering. Changchun, China, 2010:251-254.
[7] Cao J Z, Zhou Z F, Wang H, et al. Multifocus noisy image fusion algorithm using the contourlet transform[C]//2010 International Conference on Multimedia Technology. Ningbo, China, 2010: 1-4. DOI:10.1109/icmult.2010.5631461.
[8] Bekhtin Y S, Bryantsev A A, Malebo D P. Wavelet-based fusion of noisy multispectral images using Spatial Oriented Trees[C]// 2nd Mediterranean Conference on Embedded Computing. Budva, Montenegro, 2013: 113-116. DOI:10.1109/meco.2013.6601332.
[9] Srivastava R, Singh R, Khare A. Fusion of multifocus noisy images using contourlet transform[C]//2013 Sixth International Conference on Contemporary Computing. Noida, India, 2013: 497-502. DOI:10.1109/ic3.2013.6612246.
[10] 王昕, 魏有利, 李高略,等. 多源视频序列噪声抑制融合算法[J]. 中南大学学报(自然科学版),2013,44(S2):391-395.
  Wang Xin, Wei Youli, Li Gaolie, et al. Multi-source video sequence fusion algorithm restraining noise[J]. Journal of Central South University(Science and Technology), 2013, 44(S2): 391-395.(in Chinese)
[11] 沈瑜, 党建武, 王阳萍,等. 一种新的基于多尺度几何分析的图像融合方法[J]. 光电子·激光, 2013, 24(12): 2446-2451.
  Shen Yu, Dang Jianwu, Wang Yanping, et al. A novel medical image fusion method based on the multi-scale geometric analysis tool [J]. Journal of Optoelectronices·Laser, 2013, 24(12): 2446-2451.(in Chinese)
[12] 胡清平, 张晓晖, 刘超. 基于噪声评价的微光红外图像自适应融合方法[J]. 海军工程大学学报, 2017, 29(1):102-106. DOI:10.7495/j.issn.1009-3486.2017.01.020.
Hu Qingping, Zhang Xiaohui, Liu Chao. Adaptive fusion method of low light level and infrared image based on noise analysis[J]. Journal of Naval University of Engineering, 2017,29(1): 102-106. DOI:10.7495/j.issn.1009-3486.2017.01.020. (in Chinese)
[13] 严春满, 郭宝龙, 杨秀红. 一种抗噪声的高效多聚焦图像融合算法[J]. 西安电子科技大学学报(自然科学版), 2011, 38(3): 63-68. DOI:10.3969/j.issn.1001-2400.2011.03.011.
Yan Chunman, Guo Baolong, Yang Xiuhong. High efficiency algorithm with antinoise properties for multi-focus image fusion[J]. Journal of Xidian University(Natural Science), 2011, 38(3): 63-68. DOI:10.3969/j.issn.1001-2400.2011.03.011. (in Chinese)
[14] Bai Xiangzhi, Zhou Fugen, Xue Bindang. Edge preserved image fusion based on multiscale toggle contrast operator[J]. Image and Vision Computing, 2011, 29(12): 829-839. DOI: 10.1016/j.imavis.2011.09.003.
[15] Bai Xiangzhi. Morphological infrared image enhancement based on multi-scale sequential toggle operator using opening and closing as primitives[J]. Infrared Physics & Technology, 2015, 68:143-151. DOI: 10.1016/j.infrared.2014.11.015.

备注/Memo

备注/Memo:
收稿日期: 2017-06-10.
作者简介: 沈瑜(1982—),女,博士生,副教授;党建武(联系人),男,教授,博士生导师,dangjw@mail.lzjtu.cn.
基金项目: 国家自然科学基金资助项目(61562057, 61761027,51541902, 51669010, 61202314)、甘肃省自然科学基金资助项目(17JR5RA101)、长江学者和创新团队发展计划资助项目(IRT_16R36)、甘肃省“十三五”教育科学规划课题资助项目(GS[2016]GHB0217)、兰州交通大学教学改革资助项目(101004 JGY201615).
引用本文: 沈瑜,党建武,王阳萍,等.基于MSTO的含噪声多传感器图像融合算法[J].东南大学学报(自然科学版),2017,47(6):1101-1106. DOI:10.3969/j.issn.1001-0505.2017.06.004.
更新日期/Last Update: 2017-11-20