College of Mathematics and Computer, Xinyu University, Xinyu, 338004, China.
School of Economics and Management, Xinyu University, Xinyu, 338004, China.
Sci Rep. 2023 Apr 27;13(1):6882. doi: 10.1038/s41598-023-33574-5.
Pansharpening integrates the high spectral content of multispectral (MS) images and the fine spatial information of the corresponding panchromatic (PAN) images to produce a high spectral-spatial resolution image. Traditional pansharpening methods compensate for the spatial lack of the MS image using the PAN image details, which easily causes spectral distortion. To achieve spectral fidelity, a spectral preservation model based on spectral contribution and dempendence with detail injection for pansharpening is proposed. In the proposed model, first, an efficacy coefficient (CE) based on the spatial difference between the MS and PAN images is designed to suppress the impact of the detail injection on the spectra. Second, the spectral contribution and dependence (SCD) between the MS bands and pixels are considered to strengthen the internal adaptation of the spectra. Finally, a spectrally preserved model based on CE and SCD is designed to force the fused image fidelity in spectra when the MS image is pansharpened with the details of the PAN image. Experimental results show that the proposed model is effective.
融合处理将多光谱（MS）图像的高光谱含量和相应全色（PAN）图像的精细空间信息结合起来，生成高光谱空间分辨率图像。传统的融合处理方法使用 PAN 图像细节来补偿 MS 图像的空间不足，这容易导致光谱失真。为了实现光谱保真度，提出了一种基于光谱贡献和细节注入的光谱保持模型进行融合处理。在提出的模型中，首先，设计了一种基于 MS 和 PAN 图像之间空间差异的功效系数（CE），以抑制细节注入对光谱的影响。其次，考虑了 MS 波段和像素之间的光谱贡献和相关性（SCD），以增强光谱的内部适应性。最后，设计了一个基于 CE 和 SCD 的光谱保持模型，当用 PAN 图像的细节对 MS 图像进行融合处理时，该模型迫使融合图像在光谱上保持保真度。实验结果表明，所提出的模型是有效的。
