基于HSV色彩模型与区域生长法的水文图像分割

摘要

针对水文监测过程中视频图像信噪比高、观测目标颜色特征明显以及目标区域位置关系特定等特点,提出一种改进的水文图像分割方法.通过将HSV色彩模型划分为量化区间,三维颜色信息转换成一维数组,对HSV模型的明度分量进行二次量化,从而根据颜色区域进行优化分割.在此基础上,利用改进的区域生长法得到当前水位值,实现水文图像的分割.实验结果表明,该方法能够快速分割出目标区域,并且解决了水文图像像素间的连通性和邻近性问题.%Aiming at the characteristics of the hydrological monitoring video images,such as the high Signal to Noise Ratio(SNR),obvious color differences among targets and the specific location of target regions,an improved method for segmenting the hydrological image is proposed.By dividing the HSV color model into quantization intervals,the three-dimensional color information is changed into a one-dimensional array.To optimize the segmentation results based on the color only,the secondary quantizing of the Value component of HSV model takes place.Based on this,the current water level is obtained by using the improved region growing method.Finally,the segmentation of hydrological image is realized.The experimental results show that the method can segment the target area quickly and solve the connectivity and proximity problems between pixels in the hydrological image.