Destriping and evaluating FY-3D MERSI-2 data with the moment matching method based on synchronous reference image

Abstract

Medium Resolution Spectral Imager II (MERSI-2) is a payload of the China meteorological satellite FY-3D. The sensor bands 24 (10.3 to 11.3 μm) and 25 (11.5 to 12.5 μm) images, which are most suitable for land surface temperature (LST) retrieval, have higher spatial resolution than that of similar sensors. However, bands 24/25 images with spatial resolution of 250 m (hereafter bands 24/25 250-m images) have considerable horizontal stripe noise caused by the limitation of the sensor imaging system’s multi-detector parallel scanning and the multiple interferences from space. Thus, the application value of LST retrieval using bands 24/25 250-m images is severely affected. At present, existing methods used to remove stripe noise often cannot retain the spectral information of the original image. Our research considers that MERSI-2 bands 24/25 images with spatial resolution of 1000 m (hereafter bands 24/25 1000-m images) and no stripe noise can provide reasonable reference statistics for bands 24/25 250-m images. Thus, the moment matching method considering synchronous reference image is applied to remove the stripe noise of bands 24/25 250-m images in the land area. Results shows that the moment matching method considering the synchronous reference image can effectively remove the stripe noise in the land area. In addition, quantitative evaluation criteria, such as information entropy H, mean-absolute-error (MAE), and peak signal-to-noise ratio, are better than those of the traditional moment matching method. After destriping, the LST values using MERSI-2 data are retrieved with better effect and decrease by 0.339 and 0.504 K using MAE and root-mean-square error, respectively, in contrast to the Moderate Resolution Imaging Spectroradiometer LST product.