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Multi-scale and Multi-feature High Resolution Remote Sensing Image Segmentation

Qiang Zhao, Sheng Zhang, Shuling Huang

Abstract


With the development of the remote sensing technology, high resolution remote sensing image are widely penetrated into the common people. Traditional medium or low resolution image processing method based on pixel doesn't meet people’s requirement any more. In view of this, this paper puts forward a multi-scale and multi-feature high resolution remote sensing image segmentation method which is based on the traditional watershed algorithm and introduces two new concepts-wrong waterlogging basin and merging array. It firstly improves the immersion process of traditional algorithm, then optimizes the wrong water logging basin and the merging array of basin, and finally segments the high resolution remote sensing image at different scales and different features. The simulation experiments show that the improved watershed algorithm not only keeps the accurate segmentation effect of traditional algorithm, but also has much higher efficiency.

Keywords


remote sensing image segmentation, multi-scale and multi-feature, ponding basin optimization, immersion process optimization, improved Watershed Algorithm.

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