Spatial Quality Enhancement for Wide View Angle Images: A Sensor-Specific Pre-processing Algorithm Case Study on FY-3D MERSI-II

In recent decades, medium-resolution satellites have played a pivotal role in ecosystem research, providing global daily coverage. The Moderate-Resolution Spectral Imager (MERSI), a key component of Fengyun-3 (FY-3) series, exhibits excellent data continuity over three generations, delivering large-scale spatial-continuous documents. However, images from sensors with wide-view angles often exhibit considerable artifacts due to restriction of multi-detector parallel scanning system and multi-interferences from space. Furthermore, MERSI introduces known observation redundancy across pixels and tracks, presenting significant yet-untapped potential for image quality optimization and restoration from Level-1 to downstream products. We proposed a spatial quality enhancement algorithm (SPQE) for MERSI-like sensors. It has demonstrated effectiveness in generating detailed spatial information images without artifacts while retaining spectral information with four main procedures: (1) atmospheric correction inspired by Moderate-Resolution Imaging Spectroradiometer (MODIS); (2) optimization of geolocation sample methods through linear extrapolation, elimination of bow-tie effect through empirical screening; (3) utilization of observation redundancy from adjacent pixels through an restoration algorithm based on Thomas method; (4) exploitation of observation redundancy from adjacent tracks via relative registration and information stack sampling. To illustrate the effectiveness and robustness of SPQE, the widely-used MERSI-II images are tested. Examples of SPQE-derived surface reflectance imagery across global scenarios are provided. We evaluate the potential effect of SPQE on reflectance and ecological applications. Extensive validation demonstrates downstream products generated by SPQE-derived images exhibit a stronger correlation with classic products and public datasets compared to non-enhanced images. Given its performance and versatility, we anticipate the widespread use of SPQE for similar sensors.