Sub-Pixel Precision Image Matching for Sea Ice Drift Retrieval Using Maximum Cross-Correlation

Sea ice drift has significant impacts on climate change and navigation safety. Currently, various approaches have been employed to address quantization error and achieve subpixel precision in sea ice drift extraction using maximum cross-correlation (MCC). However, limited research has been conducted to compare these approaches. This study compares the performance of three approaches: image oversampling, subpixel similarity estimation, and the combination of both, for MCC-based Arctic sea ice drift extraction with subpixel precision at different time intervals. The research findings indicate that the combined approach of image oversampling and subpixel similarity estimation outperforms any single approach in terms of the accuracy of extracted sea ice drift. Additionally, this study provides recommended combinations of spatial resolutions (achieved through image oversampling) and subpixel similarity estimation methods for retrieving sea ice drift based on Fengyun-3D (FY-3D) Microwave Radiation Imager (MWRI) data at different time intervals.