Wavelet-based Watershed for Image Segmentation Algorithm

A watershed image segmentation method based on wavelet transform is proposed. Firstly, source image was filtered by multi-scale morphological filtering and the filtered image was decomposed by wavelet, then the low-frequency approximate image was segmented into many small regions by watershed algorithm and these regions were merged according to some region mergence rules to get the original segmentation image. Finally, the original segmentation image was projected into a full-resolution image by inverse-wavelet transform to get the final segmentation image. Utilizing multi-scale morphological filtering and the multi-resolution characteristic of wavelet transform, this method solves effectively the problems of sensitizing to noises and over-segmentation phenomenon of watershed algorithm, and the computing speed is improved