Techniques for Correction of Atmospheric Artifacts in Sentinel 2 Images

Remote sensing imagery is of utmost importance for overseeing alterations in the environment, assisting in the preservation of natural resources, and deepening our comprehension of worldwide carbon budgets and the consequences of climate change. However, these images are susceptible to various artifacts that can impact their quality and interpretation. One such artifact is sun glint, which refers to the reflection of light from water surfaces and poses a significant challenge when remotely sensing water column properties. The presence of atmospheric artifacts in remote sensing images can greatly influence the quality of the data and the resulting analysis. This project focuses on investigating two techniques, namely the Cox- Munk and Hedley methods, for effectively correcting these artifacts. These methods are employed to rectify surface reflectance and obtain precise information about the underlying features. The study also involves an analysis that compares these methods to evaluate their efficiency in rectifying atmospheric artifacts in remote sensing images. Real-life remote sensing data is utilized to demonstrate the implementation of these techniques, and a comprehensive analysis is conducted on the obtained results. The findings of this study can provide valuable insights for researchers and professionals working with remote sensing data, particularly those involved in atmospheric correction and image processing