Study on remote sensing image classification based on fractal theory and ridgelet neural network

Through comprehensively utilizing color spectrum, texture and shape feature of the remote sensing images, a novel method of image classification is presented based on the fractal theory and ridgelet neural network. The blue, green and red band spectrums is used as three-band-spectral characteristics, the DBC dimension and multi-fractal dimension calculated by fractal theory as two texture characteristics, the average unchanged moment as one shape feature, and the ridgelet neural network with a strong ability to identify the direction of curve is used as classifier in the proposed method. The experimental results indicated that the method used in color image classification has a high accurate rate and a strong antinoise ability.