Texture segmentation using wavelet transform
Pattern Recognition Letters
IEEE Transactions on Computers
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The paper is devoted to the use of Wavelet transform for feature extraction associated with image pixels and their classification in comparison with the watershed transform. Since watershed algorithm was applied to an image segmentation then it will have over clusters in segmentation. To solve this first we applied wavelet transform then watershed algorithm was applied to segment the image and then applying the inverse of wavelet transform to get the segmented image with high resolution. A specific attention is paid to the use of Haar transform as a tool for image compression and image pixels feature extraction. Wavelets provide a mathematical way of encoding information in such a way that it is layered according to level of detail.