z-logo
open-access-imgOpen Access
Detection of marine fronts: a comparison between different approaches applied on the SST product derived from Sentinel-3 data
Author(s) -
Christiana Papoutsa,
Milto Miltiadou,
Vassilia Karathanassi,
Polychronis Kolokousis,
Virginie Lafon,
Dimitris Sykas,
Anastasia Sarelli,
Μαρία Προδρόμου,
Diofantos Hadjimitsis
Publication year - 2018
Publication title -
ktisis at cyprus university of technology (cyprus university of technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1117/12.2324126
Subject(s) - canny edge detector , edge detection , enhanced data rates for gsm evolution , image gradient , computer science , deriche edge detector , image (mathematics) , histogram , artificial intelligence , remote sensing , computer vision , pattern recognition (psychology) , geology , image processing
Fronts, which are sharp boundaries between distinct water masses, play a substantial role in managing biodiversity of marine species and preserving a resilient ecosystem. The overarching aim of this study is to compare different methodologies for detecting marine fronts. Many marine fronts are identifiable by their strong temperature gradient. For that reason, this study tests how two different edge detection methodologies (Laplacian and Canny) performs on detecting marine once applied on the Sea Surface Temperature (SST) product of the Sentinel-3 SLSTR instrument. In a few words, the results of this study showed that the Laplacian edge detection overestimates fronts, while the Canny Edge detection algorithm underestimates them. It worth highlighting though that the results are significantly improved using the appropriate filtering and/or image enhancements. The results of the Canny Edge detection algorithm were improved when a histogram equalisation image enhancement was applied before the Canny Edge and the results of the Laplacian detector were improved with median filtering.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom