Published July 22, 2012
| Version v1
Conference paper
Shape-constrained segmentation approach for Arctic multiyear sea ice floe analysis
Contributors
Others:
- Models of spatio-temporal structure for high-resolution image processing (AYIN) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- NASA Goddard Space Flight Center (GSFC)
- IEEE
Description
The melting of sea ice is correlated to increases in sea surface temperature and associated climatic changes. Therefore, it is important to investigate how rapidly sea ice floes melt. For this purpose, a new TempoSeg method for multitemporal segmentation of multiyear ice floes is proposed. The microwave radiometer is used to track the position of an ice floe. Then, a time series of MODIS images are created with the ice floe in the image center. A TempoSeg method is performed to segment these images into two regions: Floe and Background. First, morphological feature extraction is applied. Then, the central image pixel is marked as Floe, and shape-constrained best merge region growing is performed. The resulting two-region map is post-filtered by applying morphological operators. We have successfully tested our method on a set of MODIS images and estimated the area of a sea ice floe as a function of time.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-00729033
- URN
- urn:oai:HAL:hal-00729033v1
Origin repository
- Origin repository
- UNICA