基于未消差旋转小波变换的卫星图像融合

R. G. Tambe, S. Talbar, S. Chavan
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引用次数: 1

摘要

本文提出了两种卫星图像融合算法,即抽取/下采样旋转小波变换(SSRWT)和非抽取/非下采样旋转小波变换(NSRWT),利用二维旋转小波滤波器从MS和PAN图像中提取相关和实用信息。在融合图像中识别出了三种主要的视觉伪影,即颜色失真、偏移效应和偏移失真。提出的NSRWT算法保留了源MS和PAN图像的空间和光谱特征,使融合图像具有更好的融合性能。最终的融合图像提供了比原始输入图像更丰富的信息(在空间和光谱质量方面)。实验结果表明,非消去融合算法(NSRWT)不仅比消去融合算法(SSRWT)性能更好,而且能提高融合图像的空间和光谱质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Satellite image fusion using undecimated rotated wavelet transform
This paper presents two satellite image fusion algorithms namely decimated/subsampled rotated wavelet transform (SSRWT) and undecimated/non-subsampled rotated wavelet transform (NSRWT) using 2D rotated wavelet filters for extracting relevant and pragmatic information from MS and PAN images. Three major visual artefacts such as colour distortion, shifting effects and shift distortion are identified in the fused images obtained using SSRWT which are addressed by using NSRWT. The proposed NSRWT algorithm preserves spatial and spectral features of the source MS and PAN images resulting fused image with better fusion performance. The final fused image provides richer information (in terms of spatial and spectral quality) than that of the original input images. The experimental results strongly reveal that undecimated fusion algorithm (NSRWT) not only performs better than decimated fusion algorithm (SSRWT) but also improves spatial and spectral quality of the fused images.
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