相对颜色空间下梯度分层重构的分水岭分割

为了改善传统分水岭算法中的过分割现象,考虑到反射亮光对图像的干扰,提出了一种相对颜色空间下的梯度分层重构的分水岭分割算法。首先将彩色图像由RGB空间转换到与反射亮光无关的相对颜色空间；其次结合图像信息熵获得彩色图像的梯度图像；然后根据梯度直方图的分布信息,对梯度图像进行分层重构；随后采用形态学极小值标定技术对合并后的梯度图像进行强制标定；最后对修正后的图像进行分水岭分割。对不同类型的图像进行分割实验,实验结果显示该算法相比其他3种典型的分水岭算法在分割区域个数、运行时间及区域间差异性指标(DIR)上的表现都较为突出。该算法更符合人眼对图像的感知,分割效果和性能较好,具有较高的鲁棒性和实用性。

Watershed Segmentation by Gradient Hierarchical Reconstruction under Opponent Color Space

In order to improve the over-segmentation in the traditional watershed algorithm,a watershed segmentation algorithm of gradient hierarchical reconstruction was proposed under opponent color space,considering the interference of reflected light on the image.Firstly,the color image is converted from RGB space to the opponent color space which has nothing to do with the reflected light.Secondly,the gradient image of the color image is obtained by combining the image information entropy.Thirdly,the gradient image is hierarchically reconstructed according to the distribution information of the gradient histogram.Then morphological minimum calibration technique is used to calibrate the combined gradient image.At last,watershed segmentation is applied to the corrected image.Experiments on different types of images were carried out.The experimental results show that the proposed algorithm is more prominent than the three classic watershed algorithms in the number of divided regions,running time and the DIR.The new algorithm is more in line with human perception of the image,the segmentation and performance are better,and it has higher robustness and practicality.