基于云模型的图像面状地物表达分析

针对图像处理中需要对分割区域进行表达的问题,在云理论基础上,提出对象云表达图像面状地物的方法.在图像二维论域中,不确定边界的面状地物可以借助松弛迭代法提取其定性语言值表达特征,作为云模型的云核部分.对于不确定边界过渡区域,根据其像素特征获取云模型的云滴,借助逆向云发生器,生成图像面状地物的对象云.这样,对象云作为图像面状地物表达模型,不确定边界的面状地物就可以通过对象云的数字特征来表达.最后以遥感图像为例证明了该方法能够很好地表达图像中面状地物.

Representation of Uncertain Area in Image Based on Cloud-model

Aiming at the problem of representation of regions in the process of image processing, the paper presents a method applied to representation of spatial uncertain area in image based on Cloud-model. In two-dimension universe of discourse of image, the linguistic term of the polygons, which have uncertain edge, can be accomplished by relaxation iteration. The linguistic term of the polygons can be considered Cloud-core of Cloud-model. Based on the characteristics of pixels of transition region of fuzzy edge, Object-clouds of polygons can be constructed by Backward-cloud-generator. So Object-cloud can be representation model of spatial uncertain area and spatial uncertain area in image can be represented by digital characteristics of Object-cloud. Experiments testify the method. It enriches the cloud theory, and proposes a new idea for image comprehending and analyzing, especially remote sensing image.