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Conference Papers Year : 2022

LAKE DETECTION WITH SENTINEL-1 DATA USING A GRAB-CUT METHOD AND ITS MULTI-TEMPORAL EXTENSION

Abstract

This paper presents a semi-guided method to detect lakes in Sentinel-1 SAR data. The proposed approach is an adaptation of the grab-cut framework developed in [1]. Starting from a coarse bounding box around the lake, an accurate segmentation is extracted using a Conditional Random Field formalism and a graph-cut based optimization. Then an extension of this approach to process jointly a stack of multi-temporal data is presented. A temporal regularization term is introduced to control the joint segmentation. The proposed approach is evaluated on Sentinel-1 datasets. Qualitative and quantitative results demonstrate the interest of the proposed framework and its robustness to the initialization polygon of the lake.
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Dates and versions

hal-03756052 , version 1 (22-08-2022)

Identifiers

  • HAL Id : hal-03756052 , version 1

Cite

Nicolas Gasnier, Loïc Denis, Roger Fjørtoft, Frédéric Liege, Florence Tupin. LAKE DETECTION WITH SENTINEL-1 DATA USING A GRAB-CUT METHOD AND ITS MULTI-TEMPORAL EXTENSION. IGARSS, 2022, Kuala Lumpur, Malaysia. ⟨hal-03756052⟩
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