Sonar Image Classification Based on Directional Wavelet and Fuzzy Fractal Dimension

This paper presents a supervised classification method of sonar image, which takes advantages of both directional wavelet (DW) and fuzzy fractal dimension (FFD). The definition of FFD is an extension of the pixel-covering method by incorporating the fuzzy set. DW is used for the decomposition of original images. In the process of feature extraction, a feature set is obtained by estimating the FFD of the directional wavelet transform sub-images. In the part of classifier construction, the learning vector quantization (LVQ) network is adopted as a classifier. Experiments of sonar image classification have been carried out with satisfactory results, which verify the effectiveness of this method.