李树涛
博士研究生 教授
湖南大学 电气与信息工程学院
近年来一直从事机器学习、模式识别、信息融合、生物信息学方面的研究工作。
个性化签名
- 姓名:李树涛
- 目前身份:在职研究人员
- 担任导师情况:
- 学位:
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学术头衔:
博士生导师
- 职称:高级-教授
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学科领域:
自动控制技术
- 研究兴趣:近年来一直从事机器学习、模式识别、信息融合、生物信息学方面的研究工作。
李树涛,1972年10月生,辽宁凌海市人。1995年6月和1998年6月分别在湖南大学获得工业自动化学士和理论电工专业硕士学位。2001年7月在湖南大学获控制理论与控制工程专业博士学位,博士学位论文被评为湖南省优秀博士学位论文。2001年9月至2004年5月任湖南大学电气与信息工程学院副教授,2004年6月至今任教授,2006年6月被遴选为博士生导师。2001年5月至2001年10月在香港科技大学计算机科学系进行博士后研究, 2002年11月至2003年11月在英国伦敦大学皇家霍洛威学院计算机科学系进行博士后研究,2005年4月至2005年6月在香港科技大学计算机科学系任访问教授。
近年来一直从事机器学习、模式识别、信息融合、生物信息学方面的研究工作,先后主持了国家自然科学基金、教育部新世纪优秀人才计划、教育部留学回国人员科研启动基金、湖南省杰出青年基金、湖南省自然科学基金、湖南省优秀博士学位论文基金等课题,作为主要研究人员参加了国家自然科学基金、欧盟第五框架、香港RGC基金等多项课题的研究。获得国家科学技术进步二等奖2项、部省级科技进步一、二等奖3项,在IEEE Transactions on Neural Networks、Pattern Recognition、Pattern Recognition Letters、Information Fusion、Pattern Recognition and Image Analysis、电子学报、自动化学报、IJCNN、ICPR、ICANN、ICONIP、IGARSS等国内外主要学术刊物和会议上发表科研论文50余篇,其中SCI(E)收录12篇次,EI、ISTP收录38篇次。
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主页访问
3232
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0
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成果阅读
804
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成果数
10
【期刊论文】Multifocus Image Fusion using Aritificial Neural Networks
李树涛, Shutao Li, , James T. Kwok, Yaonan Wang
,-0001,():
-1年11月30日
Optical lenses, particularly those with long focal lengths, suffer from the problem of limited depth of field. Consequently, it is often difficult to obtain good focus for all objects in the picture. One possible solution is to take several pictures with different focus points, and then combine them together to form a single image. This paper describes an application of artificial neural networks to this pixel level multifocus image fusion problem based on the use of image blocks. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach, particularly when there is a movement in the objects or misregistration of the source images.
Image fusion, Neural networks, Probabilistic neural networks, Radial basis function networks
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98浏览
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【期刊论文】Texture classification using the support vector machines
李树涛, Shutao Li, , James T. Kwok, Hailong Zhu, and Yaonan Wang
S. Li et al. Pattern Recognition 36 (2003) 2883-2893,-0001,():
-1年11月30日
In recent years, support vector machines (SVMs) have demonstrated excellent performance in a variety of pattern recognition problems. In this paper, we apply SVMs for texture classification, using translation-invariant features generated from the discrete wavelet frame transform. To alleviate the problem of selecting the right kernel parameter in the SVM, we use a fusion scheme based on multiple SVMs, each with a different setting of the kernel parameter. Compared to the traditional Bayes classifier and the learning vector quantization algorithm, SVMs, and, in particular, the fused output from multiple SVMs, produce more accurate classification results on the Brodatz texture album.
Texture classification, Support vector machines, Discrete wavelet frame transform
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【期刊论文】Comparison and fusion of multiresolution features for texture classification
李树涛, Shutao Li, , John Shawe-Taylor
S. Li, J. Shawe-Taylor. Pattern Recognition Letters 26 (2005) 633-638,-0001,():
-1年11月30日
In this paper, we investigate the texture classification problem with individual and combined multiresolution features, i.e., dyadic wavelet, wavelet frame, Gabor wavelet, and steerable pyramid. Support vector machines are used as classifiers. The experimental results show that the steerable pyramid and Gabor wavelet classify texture images with the highest accuracy, the wavelet frame follows them, the dyadic wavelet significantly lags behind. Experimental results on fused features demonstrated the combination of two feature sets always outperformed each method individually. And the fused feature sets of multi-orientation decompositions and stationary wavelet achieve the highest accuracy.
Multiresolution analysis, Texture classification, Support vector machines
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【期刊论文】基于燃烧火焰图象特征的回转窑神经网络控制系统1)
李树涛, , 王耀南, 张昌凡
自动化学报2002年7月第28卷第4期/ACTA AUTOMATICA SINICA July, 2002, Vol. 28, No. 4,-0001,():
-1年11月30日
提出了一种基于燃烧火焰图象特征的回转窑神经网络控制系统。系统主要由两部分组成,一部分是回转窑煅烧带火焰燃烧状态识别系统,包括火焰图象获取、预处理、分割、特征提取与识别;另一部分是基于高斯基函数神经网络的控制系统。实际运行结果表明该系统的有效性和实用性。
视觉检测, 图象处理, 神经网络, 模糊逻辑, 回转窑
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58浏览
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【期刊论文】Commbination of images with diverse focuses using the spatial frequency
李树涛, Shutao Li, , James T. Kwok, Yaonan Wang
S. Li et al. Information Fusion 2 (2001) 169-176,-0001,():
-1年11月30日
Image fusion attempts to combine complementary information from multiple images of the same scene, so that the resultant image is more suitable for human visual pereption and computer-processing tasks such as segmentation, feature extraction and object recongnition. This paper presents an approach that fuses images with diverse focuses by first decomposing the source images into blocks and the combing them by the use of spatial frequency. The algorithm is computataionally simple and can be implemented in real-time applications. Experimental results show that the propsed method is superior to wavelet transform based methods in both objective and visual evaluations.
Image fusion, Multisensor fusion, Spatial freqyency, Wavelet transform
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136浏览
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72下载
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【期刊论文】Skew detection using wavelet decomposition and projection profile analysis
李树涛, Shutao Li, Qinghua Shen, Jun Sun
S. Li et al. Pattern Recognition Letters 28 (2007) 555-562,-0001,():
-1年11月30日
In this paper, a novel document skew detection algorithm based on wavelet decompositions and projection profile analysis is proposed. First, the skewed document images are decomposed by the wavelet transform. The matrix containing the absolute values of the horizontal sub-band coefficients, which preserves the text’s horizontal structure, is then rotated through a range of angles. A projection profile is computed at each angle, and the angle that maximizes a criterion function is regarded as the skew angle. Experimental results show that this algorithm performs well on document images of various layouts and is also robust to different languages. The effects of various wavelet basis, number of decomposition levels, and parameters of the criterion function are investigated too.
Skew detection, D, o, c, u, m, e, n, t, analysis, Projection profile analysis, Wavelet transform
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92浏览
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694下载
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李树涛, 王耀南, 张昌凡
电子学报2001年12月第12期/ACTA ELECTRONICA SINICA Dec., 2001, Vol. 29, No. 12,-0001,():
-1年11月30日
本文提出了一种考虑人眼视觉系统特性的多聚焦图像融合算法。融合过程是首先将配准的源图像分割成若干个块,计算出每个块的对比度方差,作为图像均匀度参数,通过选取两幅图像中清晰的图像块形成融合图像。文中讨论了分解图像块的大小和阈值参数对融合性能的影响。实验结果表明本文提出的算法实时性好,对于严格配准的多聚焦图像能够达到甚至超过基于小波分解的融合算法。
图像融合, 对比度掩蔽, 视觉系统, 小波变换
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64浏览
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【期刊论文】Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images
李树涛, Shutao Li, , James T. Kwok, Yaonan Wang
S. Li et al. Information Fusion 3 (2002) 17-23,-0001,():
-1年11月30日
In this paper, we propose a pixel level image fusion algorithm for merging Landsat thematic mapper (TM) images and SPOT panchromatic images. The two source images are first decomposed using the discrete wavelet frame transform (DWFT), which is both aliasing free and translation invariant. Wavelet coefficients from TM’s approximation subband and SPOT’s detail subbands are then combined together, and the fused image is reconstructed by performing the inverse DWFT. Experimental results show that the proposed approach outperforms methods based on the intensity-hue-saturation transform, principal component analysis and discrete wavelet transform in preserving spectral and spatial information, especially in situations where the source images are not perfectly registered.
Multisensor fusion, Wavelet, Wavelet frame, Remote sensing, Image processing
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72浏览
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【期刊论文】Fusing Images With Different Focuses Using Support Vector Machines
李树涛, Shutao Li, James Tin-Yau Kwok, Ivor Wai-Hung Tsang, Yaonan Wang
IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 15, NO. 6, NOVEMBER 2004,-0001,():
-1年11月30日
Many vision-related processing tasks, such as edge detection, image segmentation and stereo matching, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasible as optical lenses, especially those with long focal lengths, only have a limited depth of field. One common approach to recover an everywhere-in-focus image is to use wavelet-based image fusion. First, several source images with different focuses of the same scene are taken and processed with the discrete wavelet transform (DWT). Among these wavelet decompositions, the wavelet coefficient with the largest magnitude is selected at each pixel location. Finally, the fused image can be recovered by performing the inverse DWT. In this paper, we improve this fusion procedure by applying the discrete wavelet frame transform (DWFT) and the support vector machines (SVM). Unlike DWT, DWFT yields a translation-invariant signal representation. Using features extracted from the DWFT coefficients, a SVM is trained to select the source image that has the best focus at each pixel location, and the corresponding DWFT coefficients are then incorporated into the composite wavelet representation. Experimental results show that the proposed method outperforms the traditional approach both visually and quantitatively.
Image fusion,, support vector machines,, wavelet transform.,
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117浏览
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【期刊论文】Page Segmentation Using Wavelet Frame and Morphology1
李树涛, S. Li, Y. Wang, Y. Li,
Pattern Recognition and Image Analysis, Vol. 14, No. 1, 2004, pp. 120-127.,-0001,():
-1年11月30日
In this paper, we present a novel algorithm for segmenting a document image into three types of regions: text, picture, and background. First, potential areas (blocks) are detected using the histogram feature of wavelet frame coefficients in the high-frequency band. Then, the intermediate segmentation results are morphologically processed to generate final results. The method has been tested on multilingual document page segmentation tasks, and the results of these tests are presented. They show good performance of the proposed method for different language texts and character sizes.
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