Picture of person typing on laptop with programming code visible on the laptop screen

World class computing and information science research at Strathclyde...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by University of Strathclyde researchers, including by researchers from the Department of Computer & Information Sciences involved in mathematically structured programming, similarity and metric search, computer security, software systems, combinatronics and digital health.

The Department also includes the iSchool Research Group, which performs leading research into socio-technical phenomena and topics such as information retrieval and information seeking behaviour.

Explore

Segmentation of multispectral images and prediction of ChI-a concentration for effective ocean colour remote sensing

Ren, Jinchang and Zeng, Xuexing and McKee, David (2015) Segmentation of multispectral images and prediction of ChI-a concentration for effective ocean colour remote sensing. In: 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, Piscataway, NJ., pp. 2303-2306. ISBN 9781479979295 (In Press)

[img]
Preview
Text (Ren-etal-IEEE-IGARSS-2015-Segmentation-of-multispectral-images-and-prediction)
Ren_etal_IEEE_IGARSS_2015_Segmentation_of_multispectral_images_and_prediction.pdf - Accepted Author Manuscript

Download (630kB) | Preview

Abstract

With the development of new sensors and data processing techniques, ocean colour remote sensing has undergone rapid development in more accurately measurement of coastal shelf classification and concentration of chlorophyll. In this paper, multispectral images are employed to achieve these targets, using techniques including region-growing based segmentation for pixel classification and support vector regression for ChI-a prediction. Interesting results are reported to show the great potential in using state-of-the-art data analysis techniques for effective ocean colour remote sensing.