A novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS)

Underwater image segmentation becomes a difficult and challenging task due to various perturbations present in the water. In this paper we propose a novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS). The M-band wavelet transform captures the texture of the underwater image by decomposing the image into sub bands with different scales and orientations. The proper sub bands for segmentation are selected depending on the HVS. The HVS imitates the original visual technique of a human being and it is used to divide each sub band into Weber, De-Vries Rose and Saturation regions. A sub band is selected for segmentation depending on those three regions. The performance of the proposed method is found to be superior than that of the stare-of-the-art methods for underwater image segmentation on standard data set.