Texture-Sensitive Superpixeling and Adaptive Thresholding for Effective Segmentation of Sea Ice Floes in High-Resolution Optical Images

Texture Segmentation of SAR Sea Ice Imagery

Texture Discrimination of SAR Sea Ice Imagery The di erentiation of textures is a critical aspect of SAR sea ice image segmen tation Provision of images that identify pertinent ice types is important for the operational ice breakers ships oil platforms and scienti c ie global warming monitoring communities Although a human is readily able to visually segment any textured image no unsupervised m...

Multi Resolution Fuzzy Segmentation of Satellite Images

Graph-based Method for Multitemporal Segmentation of Sea Ice Floes from Satellite Data

Automated segmentation of the sea ice evolution would allow scientists studying climate change to build accurate models of the sea ice meltdown process, which is a sensitive climate indicator. In this paper, we propose a novel approach which uses shape analysis and graph-based optimization for segmentation of a multiyear ice floe from time series of satellite images. Differently of the state-of...

Preserving Texture Boundaries for SAR Sea Ice Segmentation

Texture analysis has been used extensively in the computer–assisted interpretation of SAR sea ice imagery. Provision of maps which distinguish relevant ice types is significant for monitoring global warming and ship navigation. Due to the abundance of SAR imagery available, there exists a need to develop an automated approach for SAR sea ice interpretation. Grey level co-occurrence probability ...

Characterizing the size and shape of sea ice floes

Monitoring drift ice in the Arctic and Antarctic regions directly and by remote sensing is important for the study of climate, but a unified modeling framework is lacking. Hence, interpretation of the data, as well as the decision of what to measure, represent a challenge for different fields of science. To address this point, we analyzed, using statistical physics tools, satellite images of se...