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, ITA, pp. 2303-2306. ISBN 9781479979295 (In Press) (https://doi.org/10.1109/IGARSS.2015.7326268)

[thumbnail of Ren-etal-IEEE-IGARSS-2015-Segmentation-of-multispectral-images-and-prediction]
Preview
Text. Filename: 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.