改进多尺度融合结合小波域HMT模型的遥感图像分割

Modified multiscale fusion combing wavelet-domain HMT modelfor remote sensing image segmentation

提出了一种结合权值背景融合的小波域多尺度图像分割方法。首先通过小波域隐马尔可夫树模型获得图像各个尺度上的初始分割,然后为各个尺度上每一分割像素点分别赋予权值,并建立一种融合父子尺度信息的新背景模型,最后利用权值背景融合各个尺度图像初始分割结果,得到像素级分割。仿真结果表明,该方法可得到优于已有文献的分割效果。

A modified multiscale fusion method combining context based on weight values for image segmentation is introduced. After the implement of the raw multiscale segmentation based on wavelet-domain hidden Markov tree model, weights for individual dyadic square of the image under consideration at each different scale are set. Finally, raw multiscale segmentation results are fused with the context based on the corresponding weight values. Experimental results show that the method can gain a better performance than the existing technique.