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In this letter, a new strategy based on nonnegative matrix factorization (NMF) is proposed for polarimetric ship detection. This method utilizes the sparse feature of nonnegative eigenvalues, and the sparse degree is proposed to be estimated from the histogram which can reveal the sparse distribution of eigenvalues. Combining the nonnegative and sparse features, the NMF-based ship detection method can be implemented flexibly and efficiently. It has been carried out on the C-band quad polarimetric synthetic aperture radar (PolSAR) and dual PolSAR ocean data sets to validate its effectiveness. Unlike a constant-false-alarm-rate detector, the NMF method does not depend on target size and therefore offers improved detection performance under low-signal-to-clutter-ratio conditions.