A novel multi-scale segmentation algorithm for high resolution remote sensing images based on wavelet transform and improved JSEG algorithm |
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Authors: | Chao Wang Ai-Ye Shi Xin Wang Fang-ming Wu Feng-Chen Huang Li-Zhong Xu |
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Affiliation: | 1. College of Computer and Information Engineering, Hohai University, Nanjing, China;2. Institute of Communication and Information System Engineering, Hohai University, Nanjing, China;3. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China |
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Abstract: | Considering the difficulties in image segmentation caused by the complexity of diverse ecological environments and various artificial targets in high resolution remote sensing images, especially in city scene, and in order to overcome the limitations existing in the traditional segmentation algorithm, JSEG (J-Segmentation), for high resolution remote sensing image segmentation and to further improve the segmentation accuracy, WJSEG (Wavelet-JSEG), a novel multi-scale segmentation algorithm based on wavelet transform, is proposed, which is an improved JSEG algorithm. WJSEG is an improved form of JSEG in relation to three aspects, including color quantization, multi-scale segmentation and region merging by introducing the multi-scale analysis tool based on wavelet transform. Experiments have been conducted on high resolution SPOT 5 pan-sharpened multispectral image and IKONOS panchromatic image. These experimental results were compared with those gained by the traditional JSEG algorithm and the famous commercial software named eCognition, which validated the effectiveness and reliability of the proposed WJSEG algorithm. |
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Keywords: | Image segmentation Wavelet transform JSEG High resolution remote Sensing image |
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