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 |
Hits:
Description: 实现图像之间的数据融合，主要方法有基于HIS变换的，基于PCA变换的，基于加权变换的。-Between image data fusion, the main methods of transformation based on the HIS, based on the PCA transform, based on the weighted transform Platform: |
Size: 5120 |
Author:芯琪 |
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Description: 本文阐述了基于主元分析的拉普拉斯金字塔图像融合的原理和方法:首先对原图像分别进行拉普拉斯
金字塔分解,然后分别对高频部分采用主元分析（PCA）法融合,对低频部分采用平均梯度法进行融合,最后对
拉普拉斯金字塔做反变换得到最终的融合图像。通过对可见光与红外图像的融合，以及对不同焦距图像融合
的结果分析，该算法比单纯的PCA和拉普拉斯图像融合能得到具有更多有用信息的高对比度的融合图像-In this paper, principal component analysis based on the Laplacian pyramid image fusion of theory and method: First, the original image, respectively Laplacian pyramid decomposition, and then were used for high-frequency part of the principal component analysis (PCA) fusion method for The average gradient method using low-frequency part of the fusion, the last of the Laplacian pyramid to do the inverse transform to get the final fused image. Through the integration of visual and infrared images, as well as the results of image fusion of different focal length of the algorithm than the simple PCA and Laplacian image fusion can get more useful information with the integration of high-contrast images Platform: |
Size: 81920 |
Author:redxuech |
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Description: The fusion of high-spectral/low-spatial resolution
multispectral and low-spectral/high-spatial resolution panchromatic
satellite images is a very useful technique in various
applications of remote sensing. Recently, some studies showed
that a wavelet-based image fusion method provides high quality
spectral content in fused images. However, most wavelet-based
methods yield fused results with spatial resolution that is less
than that obtained via the Brovey, IHS, and PCA fusion methods.
In this paper, we introduce a new method based on a curvelet
transform, which represents edges better than wavelets. Since
edges play a fundamental role in image representation, one
effective means to enhance spatial resolution is to enhance the
edges. The curvelet-based image fusion method provides richer
information in the spatial and spectral domains simultaneously.
We performed Landsat ETM+ image fusion and found that the
proposed method provides optimum fusion results. Platform: |
Size: 1464320 |
Author:shaik |
Hits:
Description: The fusion of high-spectral/low-spatial resolution
multispectral and low-spectral/high-spatial resolution panchromatic
satellite images is a very useful technique in various
applications of remote sensing. Recently, some studies showed
that a wavelet-based image fusion method provides high quality
spectral content in fused images. However, most wavelet-based
methods yield fused results with spatial resolution that is less
than that obtained via the Brovey, IHS, and PCA fusion methods.
In this paper, we introduce a new method based on a curvelet
transform, which represents edges better than wavelets. Since
edges play a fundamental role in image representation, one
effective means to enhance spatial resolution is to enhance the
edges. The curvelet-based image fusion method provides richer
information in the spatial and spectral domains simultaneously.
We performed Landsat ETM+ image fusion and found that the
proposed method provides optimum fusion results. Platform: |
Size: 478208 |
Author:shaik |
Hits:
Description: The fusion of high-spectral/low-spatial resolution
multispectral and low-spectral/high-spatial resolution panchromatic
satellite images is a very useful technique in various
applications of remote sensing. Recently, some studies showed
that a wavelet-based image fusion method provides high quality
spectral content in fused images. However, most wavelet-based
methods yield fused results with spatial resolution that is less
than that obtained via the Brovey, IHS, and PCA fusion methods.
In this paper, we introduce a new method based on a curvelet
transform, which represents edges better than wavelets. Since
edges play a fundamental role in image representation, one
effective means to enhance spatial resolution is to enhance the
edges. The curvelet-based image fusion method provides richer
information in the spatial and spectral domains simultaneously.
We performed Landsat ETM+ image fusion and found that the
proposed method provides optimum fusion results. Platform: |
Size: 5374976 |
Author:shaik |
Hits:
Description: The fusion of high-spectral/low-spatial resolution
multispectral and low-spectral/high-spatial resolution panchromatic
satellite images is a very useful technique in various
applications of remote sensing. Recently, some studies showed
that a wavelet-based image fusion method provides high quality
spectral content in fused images. However, most wavelet-based
methods yield fused results with spatial resolution that is less
than that obtained via the Brovey, IHS, and PCA fusion methods.
In this paper, we introduce a new method based on a curvelet
transform, which represents edges better than wavelets. Since
edges play a fundamental role in image representation, one
effective means to enhance spatial resolution is to enhance the
edges. The curvelet-based image fusion method provides richer
information in the spatial and spectral domains simultaneously.
We performed Landsat ETM+ image fusion and found that the
proposed method provides optimum fusion results. Platform: |
Size: 540672 |
Author:shaik |
Hits:
Description: 用于特征降维，特征融合，相关分析等,是学习PCA特征提取的很好的学习资料，解耦，恢复原信号，数据模型归一化，模态振动，有均匀线阵的CRB曲线，连续相位调制信号(CPM)产生，在MATLAB中求图像纹理特征，时间序列数据分析中的梅林变换工具。- For feature reduction, feature fusion, correlation analysis, Is a good learning materials to learn PCA feature extraction, Decoupling, restore the original signal, Normalized data model, modal vibration, There ULA CRB curve, Continuous phase modulation signal (CPM) to produce, In the MATLAB image texture feature, Time series data analysis Mellin transform tool. Platform: |
Size: 8192 |
Author:azicx |
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Search - PCA transform in image fusion