NDLI: A new maximum likelihood classification technique for multitemporal SAR and multiband optical images

Content Provider	IEEE Xplore Digital Library
Author	Pellizzeri, T.M. Lombardo, P. Oliver, C.J.
Copyright Year	2002
Description	Author affiliation: INFOCOM Dept., Rome Univ., Italy (Pellizzeri, T.M.; Lombardo, P.; Oliver, C.J.)
Abstract	In this paper we devise a new fusion technique for a sequence of multitemporal single-channel SAR images of a given area with a single multiband optical image. Unlike for SAR, the availability of optical images is largely affected by atmospheric conditions, so that this is a case of practical interest. First, a statistical model for the joint distribution of SAR and optical data is provided. Then the corresponding joint maximum likelihood (ML) classifier is derived, and lower and upper bounds to classification performance are introduced. An optimized technique for ML joint image segmentation and classification is proposed, showing results close to the upper bound. Finally the effectiveness of fusion of SAR and optical images is investigated quantitatively, showing a consistent performance improvement with respect to using either sensor alone.
Sponsorship	IEEE IEEE Geosci. & Remote Sensing Soc. Canadian Remote Sensing Soc. Univ. Waterloo Natural Resources Canada (NRCan) Canadian Space Agency (CSA) Environ. Canada NASA Nat. Oceanic & Atmos. Adm. (NOAA) Office of Naval Res.(ONR) Nat. Space Dev. Agency of Japan (NASDA) Nat. Polar-orbiting Environ. Satellite Syst. (NPOESS)
Starting Page	908
Ending Page	910
File Size	786793
Page Count	3
File Format	PDF
ISBN	078037536X
DOI	10.1109/IGARSS.2002.1025725
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-06-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optical sensors Adaptive optics Optical scattering Optical noise Upper bound Image sensors Sensor phenomena and characterization Speckle Earth Electronic mail
Content Type	Text
Resource Type	Article

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