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基于图像算法的超分辨率重建技术可以提高光学遥感图像的空间分辨率,能够更加有效地利用现有数据并降低成本。以滇西北香格里拉市小中甸坝为实验区,以2009年的TM影像为数据源,开展遥感图像超分辨率重建实验研究。首先分析其中造成图像退化的各项因素并经过双线性插值、维纳逆滤波、卷积等处理;然后通过小波分解得到描述各个方向上不同尺度的高低频信息的小波系数,并多次试验推导出满足预期条件的加权因子。再将多时段的低分辨率图像小波系数以小波重构的方式重建。通过实验可以看出,重建图像能提供更多的细节信息,图像质量有了明显提高。
The super-resolution reconstruction technology based on image algorithm can improve the spatial resolution of optical remote sensing images, make more effective use of existing data and reduce the cost. Taking Xiaodiandiba Shangri-La City in northwestern Yunnan as an experimental area and the 2009 TM image as data source, an experimental study of remote sensing image super-resolution reconstruction was carried out. First of all, we analyze the factors that cause the image degradation, and then deal with them through bilinear interpolation, Wiener inverse filtering, convolution and so on. Then we can get the wavelet coefficients that describe the high and low frequency information of different scales in all directions, The weighting factor that satisfies the expected condition is deduced. Then reconstruct the low-resolution image wavelet coefficients of multi-period in the way of wavelet reconstruction. It can be seen from the experiment that the reconstructed image can provide more detail information and the image quality has been obviously improved.