Method for Remote Sensing Oil Spill Applications Over Thermal and Polarimetric Imagery

Several oil spill disasters have been reported in the last decade, posing a major threat to the marine ecosystem, damaging marine life, vital for protecting the environment, and reducing economic losses. In order to reduce or clean the oil spill, one needs to create a cost-effective oil spill detection system, including its source, the spill extent, the quantity estimate, the range of probable transport paths, and weather and sea conditions. Thermal and polarimetric imagery are emerging sensing modalities that show the potential for enhanced contrast in situations where conventional imaging, such as microwave, hyper-spectral, and visible imaging, has recently been researched. There is a need to compare existing thermal and polarimetric images since there is little work and data in this area. Current studies have shown some improvement in oil spill technique development. Even with the additional availability of new techniques, these steps are limited by cloud cover and lack of contrast. This article will investigate thermal and polarimetric cameras' usage for tracking 3-D oil spills in the sea by developing robust unsupervised oil sensing algorithms. It involves introducing: 1) an oil spill segmentation framework designed for thermal and polarimetric imagery; 2) a multidensity oil spill region enhancement and 3-D thickness visualization algorithm; and 3) a qualitative and quantitative oil spill analysis approach. Comparisons with existing algorithms demonstrate the effectiveness of the proposed algorithms.