基于区域的多尺度全色遥感图像分割

针对边缘信息不足导致的图像误分割问题,提出一种基于区域的多尺度全色遥感图像分割方法.首先,利用曲波变换对图像进行多尺度分析,获取多尺度分解图像;然后,利用规则划分技术将其图像域划分成一系列子块,结合统计方法,建立基于区域的多尺度统计分割模型;接着设计可逆变马尔可夫链蒙特卡罗(RJMCMC)算法求解该分割模型;最后,利用所提出方法对全色遥感图像进行分割实验,实验结果表明,所提出方法能够有效解决图像误分割问题,并较好地实现图像分割.

Region-based multiscale segmentation of panchromatic remote sensing image

For incorrect segmentation caused by the lack of boundary information, a region-based multiscale segmentation method of panchromatic remote sensing image is proposed. Firstly, curvelet transform based multiscale analysis is used to obtain the multiscale decomposed image. Then its image domain is partitioned into a set of blocks by regular tessellation, and a multiscale statistics based segmentation model united with region is built by using the statistic method. Furthermove, a reversible jump Markov chain Monte Carle(RJMCMC) algorithm is designed to simulate the segmentation model. The proposed approach is used to segment panchromatic remote sensing images, and the results show that the proposed approach can effectively solve incorrect segmentation and segment the image well.