Evaluation of fusion methods for GF-6 aiming to water body observation

Abstract

Gaofen-6 (GF-6) has the advantages of wide coverage, multiple resolutions, and multiple bands, and can provide richer information for remote sensing interpretation. Image fusion method is the key process in high resolution remote sensing application. Guangdong-Hong Kong-Macao Greater Bay Area was selected as experiment area and four image fusion methods of HPF (High-Pass Fliter), NND (Nearest Neighbor Diffusion), GS (Gram-Schmidt) and Pansharp were employed to process panchromatic and multispectral imaging. In order to evaluate the result performances, firstly, four kinds of fusion results were evaluated by visual，and then established mean, standard deviation, entropy, average gradient, correlation coefficient and spectral distortion for quantitative evaluation of fusion results. The results demonstrated that The Pansharp algorithm and the GS algorithm have the best comprehensive evaluation of the GF-6 satellite fusion effect, taking into account the color effect of the image and the enhancement of spatial details, which can meet most fusion requirements. For land-based fusion areas, the Pansharp fusion method can be selected, and the GS fusion method can better reflect the water body information and is the most suitable fusion method for GF-6 satellite water body information enhancement among the four algorithms.

The spatial-temporal consistency of chlorophyll-a and fishery resources in the water of the Zhoushan archipelago revealed by high resolution remote sensing

“…Image fusion was performed using the Nearest Neighbor Diffusion (NNDiffuse) Pan Sharpening fusion algorithm, which resulted in good retention of image color, texture features, and spectral information. The fused images have a resolution of 2 m to facilitate subsequent image analysis studies (Wang et al, 2021).…”

“…GaoFen-6 satellite (GF-6) is a low-orbiting optical remote sensing satellite that is equipped with a panchromatic and multispectral sensor (PMS) and a wide field-of-view (WFV) sensor. The PMS sensor has a high resolution of 2 m, which can be well applied to the observation of small-scale features (Wang et al, 2021).…”