An advanced algorithm for fusing Gaofen multispectral satellite data with drone imagery

Common image fusion methods used to merge remotely sensed data of varying spatial and spectral information as provided by different air-, and space-borne sensors often do not provide the optimal reachable information. This paper proposes a novel fusion method for pansharpening using a multi-resolution analysis (MRA) based on Chinese Gaofen (GF-1/2) satellite data and corresponding drone data as an example. The novel fusion method is named droesharpening fusion method, which addresses common poor spatial and spectral feature issues of fusion results. The droesharpening fusion method designed several separate computing steps based on wavelets and a pulse-coupled neural network (PCNN) to calculate low-resolution drone (LDRO) images and an injection weight (g ₖ) for significantly improved results. The droesharpening fusion method includes a new algorithm for reducing the MDRO image dimensions (RDA). The proposed new algorithm calculated image feature (IFA), and the proposed algorithm of calculating the gk (IWA). ARD is used to reduce the dimensionalities of a drone (MDRO) image to a new single-band drone (SDRO) image. Then, we applied an improved ‘à trous’ Wavelet Transform (ATWT) to SDRO images to extract LDRO images and an improved PCNN for the multispectral (MS) images. Additionally, edge processing is deployed to the PCNN segmented images. The IFA is then used to calculate the spatial characteristics of the SDRO images based on the ATWT decomposed image and the spectral features of the MS images based on the PCNN segmented images. In the next step, the IMA calculates the gk based on the spatial and spectral characteristics. The detailed spatial information of the MDRO images is then injected into the MS images by using the gk to obtain the fused drone/multispectral satellite imagery. Additional experimental results using several drone/multispectral satellite images proved that the proposed method achieves high spectral fidelity and simultaneously improves the spatial resolution of fused images.