期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B4
页码：1171-1176
出版社：Copernicus Publications
摘要：Image segmentation is a valuable approach that performs an object-based rather than a pixel-based analysis of high-spatial resolution satellite image. A multiscale approach for segmenting the pan-sharpened multispectral QuickBird-2 image based on vector field model is proposed. The edge features are obtained using the first fundamental form of the multispectral bands. The response of log Gabor bank filtering of each band is fused as multiscale texture features based on first fundamental form. Then, the image segmentation is implemented based on texture-marked watershed transform. The segmentation accuracy is assessed using dis- crepancy measures between a reference map and the segmentation. The experimental results show that the proposed approach gives a better solution of integrating spectral and texture information for the segmentation of multispectral remotely sensed image
