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Synthetic aperture radar (SAR), ultrasound-B, laser, and sonar imagery are contaminated with speckle noise. The statistical modelling of such contamination is well described by the multiplicative model, which yields the G0 distribution. In particular, reliable image contrast measures are sought in order to discriminate targets. To that end, we present statistical methods based on stochastic divergences and on the Kolmogorov-Smirnov distance for G0 data. Their performance is quantified according to their test sizes and powers. A robustness analysis is also presented for several degrees of contamination. We show that the proposed tests based on triangular and arithmetic-geometric measures outperform the Kolmogorov-Smirnov distance.