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探讨了基于多进制小波变换与多维纹理特征融合相结合的遥感影像融合方法。在融合过程中,首先对高分辨率全色影像和多光谱影像进行多进制小波分解,再联合提取局部方差、局部梯度、局部能量和局部信息熵4维纹理特征,将高分辨率影像的高频分量分别与多光谱影像的高频分量以多维纹理特征进行多判据联合方法融合,形成新的高频分量,然后与多光谱影像的低频分量进行多进制小波逆变换,最后经RGB合成为彩色影像。试验选取淮南矿区SPOT10m与TM30m空间分辨率影像,从目视判读(定性评价)、地物光谱曲线分析、定量评价指标三方面对融合方法进行了评价。结果表明,该方法既保留了原影像的光谱信息,同时也改善了影像的清晰度和分辨率,利用融合后的影像进行矿区土地利用变化监测,效果明显提高。
This paper discusses the remote sensing image fusion method based on multi-dimension wavelet transform and multi-dimensional texture feature fusion. In the process of fusion, the multi-resolution wavelet decomposition of high-resolution panchromatic images and multispectral images is firstly carried out, then the 4-dimensional texture features of local variance, local gradient, local energy and local information entropy are extracted, High-frequency components and multi-spectral images of high-frequency components of multi-dimensional texture features multi-criteria fusion method to form a new high-frequency components, and then multi-spectral images with low-frequency components of multi-band wavelet inverse transform, Synthesized as a color image. The spatial resolution of SPOT10m and TM30m in Huainan mining area was selected experimentally, and the fusion method was evaluated from the three aspects of visual interpretation (qualitative evaluation), feature spectrum curve analysis and quantitative evaluation index. The results show that this method not only preserves the spectral information of the original image, but also improves the definition and resolution of the image. Using the fused image to monitor the change of land use in the mining area, the effect is obviously improved.