SU, Xin; DELEDALLE, Charles-Alban; TUPIN, Florence; SUN, Hong

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SU, Xin
Département Traitement du Signal et des Images [TSI]

DELEDALLE, Charles-Alban
Institut de Mathématiques de Bordeaux [IMB]

TUPIN, Florence
Département Traitement du Signal et des Images [TSI]

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This paper presents a likelihood ratio test based method of change detection and classification for synthetic aperture radar (SAR) time series, namely NORmalized Cut on chAnge criterion MAtrix (NORCAMA). This method involves three steps: 1) multi-temporal pre-denoising step over the whole image series to reduce the effect of the speckle noise; 2) likelihood ratio test based change criteria between two images using both the original noisy images and the denoised images; 3) change classification by a normalized cut based clustering-and-recognizing method on change criterion matrix (CCM). The experiments on both synthetic and real SAR image series show the effective performance of the proposed framework.< Leer menos

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NORCAMA: Change Analysis in SAR Time Series by Likelihood Ratio Change Matrix Clustering

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