An Efficient C-V Model with Wavelets

Jifei Liu, L. Min
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Abstract

We propose an efficient C-V model with wavelet transform to speed up the C-V model evolution. Firstly, the image is decomposed into the downsizing and approximation sub-image with wavelet transform. Then the sub-image composed with the approximation wavelet coefficient matrix is pre-segmented using C-V model to get an approximation curve in a short time. Thirdly, in order to get a fine segmentation, the original image is segmented subtly using C-V model again, of which the initial curve is reconstructed by the result of pre-segmentation. The experimental results validate the effectiveness and feasibility of this model.
带小波的高效C-V模型
为了加快C-V模型的演化速度,提出了一种基于小波变换的高效C-V模型。首先,用小波变换将图像分解为缩小和逼近子图像;然后利用C-V模型对由近似小波系数矩阵组成的子图像进行预分割,在短时间内得到近似曲线。再次利用C-V模型对原始图像进行精细分割,利用预分割结果重构初始曲线,得到精细分割结果。实验结果验证了该模型的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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