一种改进的分水岭图像分割算法

针对分水岭图像分割算法普遍存在受噪声影响大和过分割的问题,提出了一种基于梯度修正和相邻区域边缘强度合并的改进分水岭图像分割算法。首先对图像采用形态学开闭重建滤波,消除噪声对图像的干扰;其次,使用多尺度算子计算形态梯度,充分利用大结构元素和小结构元素的各自优点,获得更准确的形态学梯度;再用粘性形态学运算对梯度图像修正,有效去除产生过分割的局部极小梯度值;分水岭变换后,定义出相邻区域的边缘强度值,并基于相邻区域边缘强度合并过分割区域,进一步消除图像过分割,改进分割效果。实验表明:该方法不仅能够有效地去除图像噪声干扰,而且能够消除过分割区域,同时还具有较强的区域轮廓定位能力,有效提高了图像分割效果。

An Image Segmentation Method Based on Improved Watershed Algorithm

To overcome the shortcomings such as the existence of over-segmentation in and the great influence of noise on the traditional watershed segmentation, an improved novel watershed image segmentation method is proposed. Firstly, the open-close reconstruction filter is adopted to remove the image noise. Secondly, multi-scale structure elements are used to calculate morphological gradient which can overcome the shortcomings of other conventional gradient operators and produce a gradient map suitable for watershed segmentation. Furthermore, the morphological gradient is modified by viscous morphological operators to remove the most irregular local minimums. After the standard watershed transforming, the region merging method based on neighbor regions edge value is employed to improve the segmentation result. Experiments show that this method can not only effectively remove the noise but also avoid the over-segmentation of watershed and preserve the positions of regional contours.