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Multiresolution-based watersheds for efficient image segmentation
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DOI：10.1016/S0167-8655(02)00270-2.png)
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This paper presents an efficient method for image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region merging and region projection. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, region merging merges the segmented regions using the third-order moment values of the wavelet coefficients. Finally, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation. In addition, we applied our method to human face detection with accurate and closed boundaries. (C) 2002 Elsevier Science B.V. All rights reserved.
Keyword:
image segmentation
watershed image segmentation
wavelet transform
multiresolution image analysis
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3.3
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