近年来,高光谱遥感图像的分割作为地物识别和异常目标探测等应用的基础工作而受到重视,而高光谱遥感图像的海量数据和复杂结构使其分割技术成为一项挑战性的工作。在对海岸带高光谱遥感图像的光谱特性进行分析的基础上,提出一种基于光谱特性的海岸带水、陆区域分割的偏微分方程活动轮廓模型:首先以高光谱海岸带图像的海域像元光谱信息为参照点,构建海岸带高光谱图像的能量偏差矩阵;在此基础上建立适应该能量偏差矩阵的水、陆区域分割的活动轮廓模型。模型通过引入基于梯度的边缘引导函数,提升了对水、陆区域边缘的捕捉能力和抗噪声干扰能力。实验结果表明,与传统活动轮廓模型相比,本文模型不仅能够保证水、陆区域分割的精度,而且具有更快的计算速度。

In recent years,the segmentation of coastal hyperspectral remote sensing image which combines ground objects identification with anomaly target detection, is receiving more attention. Moreover, it is a challenge for the massive data and complex construction of hyperspectral image. This paper presents a partial differential equation for active contour models based on the spectral characteristic of coastal terraqueous region segmentation for reference. First, the pixel spectral information of coastal hyperspectral remote sensing image is used as the reference point to construct an energy deviation matrix. Then, using this energy deviation matrix, a new active contour model of terraqueous region segmentation is proposed. It improves the capture and anti-noise capacities of terraqueous marginal region, based on the edge guide function of gradient. The experimental results, compared with that of traditional active contour models, demonstrate that the proposed approach not only yields accurate segmentation but enhances the calculation speed as well.