@inproceedings{c8f74d4ad7174a8a91adbcb09cae0dd9,
title = "Infrared satellite precipitation estimate using wavelet-based cloud classification and radar calibration",
abstract = "We have developed a methodology to enhance an infrared-based high resolution rainfall retrieval algorithm by intelligently calibrating the rainfall estimates using space-based observations. Our approach involves the following four steps: 1) segmentation of infrared cloud images into patches; 2) feature extraction using a wavelet-based method; 3) clustering and classification of cloud patches; and 4) dynamic application of brightness temperature (Tb) and rain rate relationships, derived using satellite observations. The results show that using wavelet features along with other features increase the performance of rainfall estimate in terms of quantitative rain/no rain area estimates. In addition, using lightning data as a feature improves the estimates as well.",
keywords = "Clustering methods, Curve fitting, Neural networks, Wavelet transforms",
author = "Majid Mahrooghy and Anantharaj, {Valentine G.} and Younan, {Nicolas H.} and Petersen, {Walter A.} and Turk, {F. Joseph} and James Aanstoos",
year = "2010",
doi = "10.1109/IGARSS.2010.5649049",
language = "English",
isbn = "9781424495658",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2345--2348",
booktitle = "2010 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010",
note = "2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010 ; Conference date: 25-07-2010 Through 30-07-2010",
}