Abstract
This paper presents an improved image segmentation method based on multi-resolution analysis of wavelet transform and watershed transformation. In the marked-controlled watershed segmentation, we not only enhance the contours of low-resolution input image to acquire segmentation function image, but also use minima imposition technology to apply filters to input image to acquire marked function image. In order to improve segmentation accuracy, we use regional fusion and coarse-fine segmentation in wavelet inverse transform. The experimental results show that the proposed image segmentation method can efficiently reduce over-segmentation, as well as improve the effect of image segmentation. In addition, the proposed method is robust.
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