For sea ice monitoring , automatic classification of SAR image has great signification. Due of coherence, adjacent pixels of the gray would change randomly in rader echo signals,which causes traditional features can’t work well in SAR sea ice classification. The energy of coherent speckle noise is concentrated in the high frequency. The wavelet transform can decompose signal into different components in the frequency domain, which providing an opportunity to analyze the signal locally.In this paper, a mothod of sea ice classification is adopted, which is based on low-frequency sub-band wavelet feature. The result shows this method reduces the noise influence and improves inaccurate classification caused by noise.