一种光谱信息保持的影像融合算法研究

在介绍遥感图像融合中IHS变换和小波包分析的基础上,提出了一种基于光谱特征保持的IHS变换与小波包分析相结合的图像融合算法。该方法可以最大限度地保留待融合图像的光谱信息,同时融合图像的清晰度和空间分辨率有了很大提高,图像纹理信息也得到了很好的保持。通过对SAR图像与Landsat(TM)多光谱图像的融合实验,证明了该方法的有效性。     

Fusion of IKONOS Satellite Imagery Using IHS Transform and Local Variation

The intensity-hue-saturation (IHS) technique is a well-known merging approach for its computational efficiency and spatial definition holding. However, it results in color distortion particularly for the remote sensing images of IKONOS and QuickBird as some other fusion methods, such as principal component analysis, and Brovey transform. Although wavelet-based image fusion approaches can provide a better tradeoff between spatial and spectral quality, the fused images with these methods often have a spatial resolution that is less than that of the IHS-based algorithm. A remote sensing image fusion algorithm based on IHS transform and local variation and its modified approach with low computational complexity are proposed. Visual effect and quantity evaluation results show that the proposed simple algorithm outperforms the conventional image fusion methods in the spectral domain with the spatial quality similar to that of the undecimated wavelet transform-based scheme. The proposed modified method can obtain the similar spatial resolution of the merged image with the IHS-based fusion algorithm and the better spectral quality in the green vegetation areas.      

a'Trous小波与HIS变换相结合的遥感影像融合分析

采用a'trous小波与HIS变换相结合的方法对Aster多光谱影像和资源二号全色影像进行融合实验和评价,并与传统的HIS变换和小波变换融合方法加以对比.结果表明:a'trous小波与HIS变换相结合的融合效果最好,吸取了两种单一融合方法的优点,不仅较大程度上提高了原始影像的空间细节表达能力,而且很好地保留了原始影像的...     

基于小波包变换距离特征选取的遥感影像融合

介绍了基于小波包变换和距离特征选取的影像融合方法：首先对多光谱影像做IHS变换;其次对多光谱影像的亮度分量和全色影像做小波包变换并分别采用加权平均法和距离特征选取法融合低频部分和高频部分;最后通过小波包重构和IHS逆变换得到最终的融合影像。以ERDAS8．5软件自带的影像文件为例对这种方法进行了实验,并利用信息熵等标准与其他融合方法进行了比较,实验结果表明该方法能得到更好的融合效果。     

基于区域统计特性的IHS-小波遥感影像融合

在遥感影像融合过程中,为了更好地避免经典IHS算法造成的光谱扭曲,文章提出了一种基于统计特性的IHS和提升小波结合的影像融合方法。该方法对小波变换后的1分量和高分辨率影像的高频和低频系数,根据不同的区域统计特性分别选取不同的融合策略进行融合,然后进行小波逆变换和色彩空间转化,得到融合影像。实验表明,此方法与IHS变换、高通滤波法和小波变换等传统算法相比,在提高多光谱影像空间分辨率的同时,能更好地保持影像的光谱质量。     

基于小波统计特性的遥感图像像素与特征联合最优融合方法

遥感影像的IHS融合方法由于匹配误差导致光谱畸变和退化,而小波变换在变换域具有良好的分频特性,小波系数的统计特性反映了遥感影像的边缘、线和区域等显著特征。提出了基于小波统计特性的遥感影像的像素和特征联合最优融合方法,在IHS空间,对强度分量I的高频部分利用多分辨率小波融合方法进行影像的高频细节特征融合,低频部分选取光谱信息和空间分辨率评价指标作为融合权系数求优指标,进行像素级最优融合,实验结果证明了该方法的有效性。     

利用小波变换对影像进行融合的研究

基于小波变换可以对影像进行正交分解 ,而不丢失原来信号所包含的信息。提出了一种Wallis变换、小波变换和IHS变换相结合用于融合的方法 ,该方法可以有效地提高多光谱影像的空间分辨率 ,同时保持原来多光谱影像的色调。     

基于小波包变换区域方差的遥感影像融合

介绍了基于小波包变换和区域方差的遥感影像融合方法.利用IHS变换和小渡包变换把全色影像和多光谱影像的相应分量分解为低频部分和高频部分,并分别采用加权平均法和区域方差法融合低频部分和高频部分,然后通过小波包重构和IHS逆变换得到最终的融合影像;最后采用MATLAB语言实现了这种方法.实验结果表明,这种方法在提高影像的清晰度、突出影像细节信息以及保留原始影像的光谱特征方面效果较好.     

小波变换用于高分辨率全色影像与多光谱影像的融合研究

将小波的多分辩率分析与ＩＨＳ变换相结合,提出了叠加融合的新方法。它先对高分辨率影像进行了小波分解,得到的各小波面叠加到多光谱影像经ＩＨＳ变换后的强度Ｉ影像像中,使得融合影像最大限度地保留了多光谱影像的光谱信息,保持了原多光谱影像的反差,同时提高了它的清晰度和空间分辨率。     

FFT-enhanced IHS transform method for fusing high-resolution satellite images

Existing image fusion techniques such as the intensity–hue–saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information.     

基于经验模态分解的高分辨率影像融合(英文)

High resolution image fusion is a significant focus in the field of image processing. A new image fusion model is presented based on the characteristic level of empirical mode decomposition （EMD）. The intensity hue saturation （IHS） transform of the multi-spectral image first gives the intensity image. Thereafter, the 2D EMD in terms of row-column extension of the 1D EMD model is used to decompose the detailed scale image and coarse scale image from the high-resolution band image and the intensity image. Finally, a fused intensity image is obtained by reconstruction with high frequency of the high-resolution image and low frequency of the intensity image and IHS inverse transform result in the fused image. After presenting the EMD principle, a multi-scale decomposition and reconstruction algorithm of 2D EMD is defined and a fusion technique scheme is advanced based on EMD. Panchromatic band and multi-spectral band 3,2,1 of Quickbird are used to assess the quality of the fusion algorithm. After selecting the appropriate intrinsic mode function （IMF） for the merger on the basis of EMD analysis on specific row （column） pixel gray value series, the fusion scheme gives a fused image, which is compared with generally used fusion algorithms （wavelet, IHS, Brovey）. The objectives of image fusion include enhancing the visibility of the image and improving the spatial resolution and the spectral information of the original images. To assess quality of an image after fusion, information entropy and standard deviation are applied to assess spatial details of the fused images and correlation coefficient, bias index and warping degree for measuring distortion between the original image and fused image in terms of spectral information. For the proposed fusion algorithm, better results are obtained when EMD algorithm is used to perform the fusion experience.     

IHS变换和小波变换相结合的遥感影像融合

本文针对低分辨率多光谱影像与高分辨率全色影像的融合，提出了一种IHS变换和小波变换相结合的遥感影像融合方法。方法首先对多光谱影像作IHS正变换，得到亮度I、色度H和饱和度S三个分量：然后利用小波变换融合方法，融合多光谱影像的亮度分量与全色影像，并用融合后的影像替代多光谱影像的亮度分量；最后，利用IHS反变换得到新的多光谱影像。试验结果分析表明，新方法的性能优于IHS变换融合方法、小波变换融合方法，在增强融合影像的空间细节表现能力的同时，很好地保留了多光谱影像的光谱信息。     

改进IHS变换的图像融合方法研究

经典的IHS变换融合以其快速、简单的特点得到广泛应用,但该方法在显著提高图像空间分辨率的同时引起了严重的光谱失真.本文分析了IHS变换引起光谱失真的原因,并总结了已有的针对光谱失真的IHS变换改进算法,提出基于小波的IHS变换融合,利用小波分解尽可能地保留了原I分量中的光谱信息,在提高空间分辨率的同时减少了光谱失真.实...     

基于非下采样Contourlet变换的遥感影像融合

根据非下采样Contourlet变换的特点,提出一种基于非下采样Contourlet变换和IHS变换相结合的遥感影像融合方法.该方法首先对金色影像和多光谱影像经IHS变换后的I分量分别进行非下采样Contourlet 变换;然后采取不同的融合策略分别对高低频系数进行融合:低频系数采用区域能量加权的方法进行融合,高频系数则利用八邻域梯度优先的原则进行融合;最后通过非下采样Contourlet逆变换和IHS逆变换得到融合影像.实验结果表明,该方法在提高融合影像空间分辨率的同时,能更好地保持影像的光谱质量.     

保持光谱信息的遥感图像融合方法研究

常用的遥感图像融合方法,如IHS变换法、Brovey变换法和主成分变换法等在实施图像融合时,均会有不同程度的光谱扭曲现象.探讨能有效保持光谱信息的EECN融合法.EECN融合法采用比值变换法,同时对参与融合的全色波段进行增强边缘,融合后的图像在光谱保持性能、分类精度等方面均较优.     

城市植被制图中SPOT5影像融合方法研究

不同的融合方法用于不同应用目的融合效果不同,本文采用主成分分析、HIS变换以及基于小波变换的主成分分析和HIS变换四种融合方法对SPOT5全色波段和多光谱波段进行融合,并针对城市植被制图特点对融合结果进行质量评价。结果表明,基于小波变换的PCA和HIS变换融合法光谱保持能力最好,但是空间结构特征较差,不适于城市植被零星分布的特点。主成分分析既有较好的空间结构特征,细小地物纹理清晰,同时又具有较好的光谱保持能力,最适合于城市植被制图研究。     

基于亮度相关矩的MODIS和SPOT影像融合研究

针对MODIS影像空间分辨率较低的问题，提出了一种基于亮度相关矩的多分辨率图像融合方法。该方法首先对SPOT影像进行小波分解，将MODIS影像构成的RGB颜色系统变换到IHS颜色系统；然后，根据强度分量和SPOT影像低频分量的均值和方差来定义图像亮度相关矩；最后，IHS逆变换和小波逆变换得到包含更多信息和有效特征的融合图像。试验结果证明该方法得到的融合图像在保留地物光谱信息和提高空间分辨率上都具有很好的效果。     

基于可操纵金字塔和IHS变换的遥感影像融合

提出了一种基于可操纵金字塔和IHS变换的遥感影像融合方法。对多光谱（MS）图像的强度分量和全色图像（PAN）分别进行可操纵金字塔分解,针对金字塔分解后的低频、高频和各带通子图像分别采取不同的融合规则获得融合子图像,再先后通过可操纵金字塔框架下的逆变换和IHS逆变换得到融合图像。实验结果表明,该方法在增强影像细节信息、保...     

A fast intensity-hue-saturation fusion technique with spectral adjustment for IKONOS imagery

Among various image fusion methods, intensity-hue-saturation (IHS) technique is capable of quickly merging the massive volumes of data. For IKONOS imagery, IHS can yield satisfactory "spatial" enhancement but may introduce "spectral" distortion, appearing as a change in colors between compositions of resampled and fused multispectral bands. To solve this problem, a fast IHS fusion technique with spectral adjustment is presented. The experimental results demonstrate that the proposed approach can provide better performance than the original IHS method, both in processing speed and image quality.     

Spectral and Spatial Quality Analysis in Pan Sharpening Process

Image fusion is a process to obtain new images containing more information by combining images obtained same or different sensors. With most of the earth observation satellites, high spatial resolution panchromatic images and low spatial resolution multispectral images are obtained. As an example of image fusion ??pan sharpening?? is a process of combining of high spatial resolution panchromatic images and low spatial resolution multispectral images. At the end of the fusion process both high spatial and spectral resolution new images are obtained. In this study, panchromatic and multispectral images gathered from Ikonos were used. Panchromatic and multispectral images belonging to the same sensor were combined by using different image fusion methods. As pan sharpening methods Brovey transform, Modified IHS, Principal Component Analysis (PCA), Wavelet PC transform and Wavelet A Trous transformation methods were used. Quality of fused products was evaluated from the point of view of both visual and statistical criteria. While wavelet based methods are succesfull in terms of protection of spectral quality of original multispectral images, the colorbased and statistical methods are giving better results within the improvement of spatial content.