Description: 基于小波变换的图像融合，采用的是区域的6种算法-based on wavelet transform image fusion, using the region's six algorithms Platform: |
Size: 3072 |
Author:赵志强 |
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Description: 利用小波变换方法进行多卫星遥感图像数据融合，分析不同长度的小波基对融合图像的影响，从信息的保持性、视觉效果及运用灵活性等方面与IHS、PCA 融合算法进行了比较，从而探讨这一新算法在遥感图像分析应用中的可行性。-Using wavelet transform methods of multi-satellite remote sensing image data fusion, analysis of different wavelet bases on the length of the impact of image fusion, from the maintenance of information, visual effects and the use of flexibility with the IHS, PCA fusion algorithm are compared in order to explore the This new algorithm in the application of remote sensing image analysis feasibility. Platform: |
Size: 65536 |
Author:lieutenant |
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Description: dctcom.m文件利用DCT变换完成对输入图像进行压缩；imagecbe.m完成对输入的两幅RGB图像用小波分析的方法进行图像融合 imagecom.m完成对输入的RGB图像用小波分析的方法进行自动降噪，得到高频系数阈值，降噪效果百分比和结果 wavelet1D.m完成对输入的一维信号进行多尺度离散小波分解 wavelet2D完成对输入的二维信号进行多尺度离散小波分解；zigzag.m完成对输入的8*8矩阵按照zigzag排列抽取数据.-document the use of DCT transform dctcom.m completion of the input image compression imagecbe.m completion of the two RGB input image with wavelet analysis method of image fusion imagecom.m completion of the input RGB image using wavelet analysis method automatically drop noise, the threshold of high-frequency coefficient, noise reduction effect and the results of the percentage of wavelet1D.m completion of the input signals of one-dimensional discrete wavelet multi-scale decomposition wavelet2D completion of the input signals of two-dimensional discrete wavelet multi-scale decomposition zigzag.m completed the input of 8* 8 matrix of data collected in accordance with the zigzag order. Platform: |
Size: 3072 |
Author:zhouhao |
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Description: 图像的小波去噪,给灰度图像加上一定量的高斯噪声,再采用小波变换的方法去噪.-Wavelet Denoising image to gray image coupled with a certain amount of Gaussian noise, and then using the method of wavelet transform de-noising. Platform: |
Size: 1024 |
Author:李大 |
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Description: 本文借助多尺度分析为手段，
研究医学图像配准与融合过程中医学图像的增强、插值、配准、融合和分割等
关键问题的理论方法研究，扩展了尺度的含义，使其不再局限在通常的小波分
析和形态学两个方面。-In this paper, using multi-scale analysis as a means to study the medical image registration and fusion process of medical image enhancement, interpolation, registration, integration and division of such key issues as the theoretical study of the meaning of the expansion of the scale so that it no longer confined to wavelet analysis in the usual two aspects and morphology. Platform: |
Size: 2545664 |
Author:媛媛 |
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Description: 种基于图像质量因子的图像融合客观评价方法。该方法利用熵加权和均方根图像融合质量因子对融合图像与源图像间的相关性、 亮度失真和对比度失真进行综合评价,因而在不同融合方法和不同源图像的条件下,可获得标准的评估统计量。采用加权平均、 拉普拉斯塔形分解及基于小波变换的图像融合法为例,通过对多传感器图像进行融合评价实验,证明了该方法的有效性和鲁棒性。-Factor based on image quality of the image fusion method of objective evaluation. This method is the use of entropy and the weighted root-mean-square image fusion quality factor of the fused image and the source of the correlation between image brightness and contrast distortion of a comprehensive evaluation of distortion, which fusion in different ways and different sources of image conditions, the availability of standards assessment statistics. Using the weighted average, Laplacian pyramid and wavelet transform-based image fusion method as an example of multi-sensor image fusion evaluation experiments show that the method is effective and robust. Platform: |
Size: 730112 |
Author:storm |
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Description: 小波变换方法实现一般彩色图像的融合算法，采用三层小波变换-Wavelet transform method to achieve a general color image fusion algorithm using wavelet transform three-tier Platform: |
Size: 2048 |
Author:陈羿辰 |
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Description: 基于matlab小波变换的图像融合，采用的是区域的6种算法-Matlab wavelet transform based image fusion, using the region of six kinds of algorithms Platform: |
Size: 4096 |
Author:高飞 |
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Description: 提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和Ekman“面部表情图片”数据库上的实验，证实
了所提方法的有效性。-Proposed based on feature fusion and fuzzy kernel discriminant analysis (FKDA) facial expression recognition. First, face images of each piece of hand-set
Bit 34 basis points, as the geometric features of facial expression images, while using Gabor wavelet transform method to transform the images of each piece of expression, and extraction-based
Quasi-point of the Gabor wavelet coefficients, as Gabor features of facial expression image second, using canonical correlation analysis on the geometric features and Gabor features into
Line feature fusion, as expression recognition of input features then, using fuzzy kernel discriminant analysis method to extract and further identification features of expression Finally, the most
Neighbor classifier to complete expression of the classification. International expression by JAFFE database and Ekman "facial image" database on the experiment, confirmed
The proposed method. Platform: |
Size: 375808 |
Author:MJ |
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Description: 提出了一种基于多通道 Gabo r滤波器和 FCM聚类的图像融合新方法。该方法先利用模糊
C2均值聚类算法在多通道 Gabo r滤波器形成的特征空间上对图像进行区域分割 再对待融合图像进行多尺度小波分解 在此基础上利用 Gabo r滤波器提取高频段纹理特征构造区域相似度 ,应用区域相似度及信息量构造加权因子 ,从而得到融合图像的小波系数 最后 ,利用小波逆变换得到融合图像.-Proposed a multi-channel Gabo r filter and FCM clustering for image fusion method. The method first C2 means clustering algorithm using the fuzzy multi-channel Gabo r filter in the formation of the image feature space segmentation re fused to treat multi-scale wavelet decomposition image on this basis, the use Gabo r filter from the high frequency structural similarity region texture features, application areas and the information structure similarity weighting factor, resulting in fusion of the wavelet coefficients Finally, the inverse wavelet transform fusion image. Platform: |
Size: 458752 |
Author:guoj |
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Description: 基于小波变换的图像融合源代码，利用的融合规则分别使用简单的模值取大和基于区域能量。-Image fusion based on wavelet transform source code, the use of fusion rule modulus were obtained using a simple large and region-based energy. Platform: |
Size: 98304 |
Author:葛宏 |
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Description: Image Fusion is the process of combining information of two or more images into a single image which can retain all important features of the all original images. Input to fusion is a set of images taken from different modalities of the same scene. Output is an image of better quality which quality depends on a particular application. The objective of fusion is to generate a resultant image which describes a scene better or even higher than any single image with respect to some relevant properties providing a highly informative image. These fusion techniques are especially beneficial in diagnosing and treating cancer in field of medicine. This paper focuses on the development of a different image fusion method using Dual Tree Complex Wavelet Transform. Experimental results show that the proposed algorithm has a better visual quality than the base methods. Also the result if the fused image has been evaluated using a set of quality metrics. -Image Fusion is the process of combining information of two or more images into a single image which can retain all important features of the all original images. Input to fusion is a set of images taken from different modalities of the same scene. Output is an image of better quality which quality depends on a particular application. The objective of fusion is to generate a resultant image which describes a scene better or even higher than any single image with respect to some relevant properties providing a highly informative image. These fusion techniques are especially beneficial in diagnosing and treating cancer in field of medicine. This paper focuses on the development of a different image fusion method using Dual Tree Complex Wavelet Transform. Experimental results show that the proposed algorithm has a better visual quality than the base methods. Also the result if the fused image has been evaluated using a set of quality metrics. Platform: |
Size: 16384 |
Author:sruthy78 |
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Description: The most widely used transform for image fusion at
multi scale is Wavelet Transform since it minimizes structural
distortions. But, wavelet transform suffers lack of shift
invariance & poor directionality. These disadvantages are
overcome by using our proposed method that is Un-decimated
Discrete Wavelet Transform.-The most widely used transform for image fusion at
multi scale is Wavelet Transform since it minimizes structural
distortions. But, wavelet transform suffers lack of shift
invariance & poor directionality. These disadvantages are
overcome by using our proposed method that is Un-decimated
Discrete Wavelet Transform. Platform: |
Size: 12288 |
Author:Naga Kishore |
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Search - image fusion using wavelet transform