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针对àtrous小波分解过程中的细节损失以及融合结果边缘模糊等问题,提出一种基于高提升滤波和àtrous小波分解的遥感图像融合算法.首先,利用àtrous小波变换得到第一层小波面,然后将获取的小波面作为非锐化模板进行高提升滤波,最后将滤波后的影像作为高频分量参与àtrous小波重构得到融合图像.基于北京地区的高分一号影像进行了算法验证,结果表明本算法优于传统小波域中的图像融合算法,对于城镇等建筑密度比较高的地区,融合后的影像保留了更多的细节信息,可以更好地支持城市变化检测和城市土地利用分析等方面的应用研究.
Aiming at the loss of detail in the àtrous wavelet decomposition and the fuzzy edge of the fusion result, a remote sensing image fusion algorithm based on high lifting filter and àtrous wavelet decomposition is proposed.Firstly, the first wavelet layer is obtained by àtrous wavelet transform, Wavelet transform is used as unsharp template to enhance the filter.Finally, the filtered image is converted to a high-frequency component by àtrous wavelet reconstruction to obtain a fusion image.An algorithm based on the high score of Beijing image is verified, and the results show that this algorithm Which is superior to the traditional image fusion algorithm in wavelet domain. For areas with relatively high building densities such as urban areas, the fused images retain more detailed information and can better support the application of urban change detection and urban land use analysis the study.