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随着遥感技术的快速发展以及遥感数据的广泛应用,影像的融合处理已成为多源遥感影像信息聚合、获取高质量空间影像的有效途径。基于SPOT全色和多光谱、TM多光谱遥感数据,运用IHS和小波变换相结合的融合方法,进行了不同来源影像融合、融合图像质量对小波分解层数的响应以及这种响应对研究区域面积的敏感性分析。结果表明,多源影像之间的IHS和小波变换相结合的融合方法明显地改善了影像的质量;融合图像质量与原始影像空间分辨率相关,如经1层小波变换融合,TM,SPOT融合图像熵值的增幅分别为20.95%,0.19%。小波融合图像质量对小波分解的层数的敏感性较强,在小波分解层数为2,3或4时,都能获得高质量的融合图像;小波分解层数等于或大于5时融合图像质量下降,7是大幅下降的临界层数。融合图像质量对小波分解层数的响应特性对面积大小变化是敏感的,特别是小面积图像,为此,实际应用中需特别注意最佳分解层数问题。
With the rapid development of remote sensing technology and the extensive application of remote sensing data, the fusion of images has become an effective way to aggregate multi-source remote sensing images and obtain high-quality spatial images. Based on the SPOT panchromatic and multispectral TM multispectral remote sensing data and the fusion method of IHS and wavelet transform, the fusion of image from different sources and the response of fusion image quality to the wavelet decomposition layer number were studied. Sensitivity analysis. The results show that the fusion method of combining IHS and wavelet transform between multi-source images can obviously improve the image quality. The fusion image quality is related to the spatial resolution of the original image, such as the fusion of 1-layer wavelet transform, TM, SPOT fusion image The increase of entropy value is 20.95% and 0.19% respectively. Wavelet fusion image quality is highly sensitive to the number of layers of wavelet decomposition, and high quality fused images can be obtained when the number of wavelet decomposition layers is 2, 3, or 4. When the number of wavelet decomposition layers is equal to or greater than 5, the fusion image quality Decline, 7 is a sharp decline in the number of critical layers. The response characteristic of fusion image quality to wavelet decomposition layer is sensitive to the change of area size, especially for small area images. Therefore, in practice, special attention should be paid to the optimal decomposition level.