Image segmentation with wavelet transform based on spatial multi-resolution analysis

A method based on spatial multi-scale analysis is put forward. Firstly, an image is divided into sub-domains with different sizes by analyzing the energy projection distribution on rows and columns of the image, and the sizes are adjusted adaptively according to both holistic and local features. Then, wavelet transform to each sub-image is adopted and the statistics which reflect the local features are extracted. Finally, an improved fuzzy c-means (FCM) method is adopted to cluster the eigenvectors, thus the image segmentation is realized. Experimental results have proved that the proposed method can speed up operation as well as improve the segmentation results.