| 光谱学与光谱分析 |
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| Farmland Parcel Extraction Based on High Resolution Remote Sensing Image |
| HU Tan-gao, ZHU Wen-quan*, YANG Xiao-qiong, PAN Yao-zhong, ZHANG Jin-shui |
| State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, School of Resource and Technology of Beijing Normal University, Beijing 100875, China |
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Abstract A new method of farmland parcel extraction from high resolution remote sensing image based on wavelet and watershed segmentation was proposed in the present paper. First, classification results were used to enhance the contrast of gray-scale value of typical pixels in the original image using the high resolution remote sensing image’s spectral information. Second, wavelet transform and watershed segmentation were applied to the enhanced image, then improved region merger algorithm was used to solve the problem of over-segmentation. Finally, inverse wavelet transform was taken to get the reconstructed image, then Canny operator was introduced to add the edge information, and the result of farmland parcel segmentation was obtained. To validate the proposed approach, experiments on Quickbird images were performed, we rapidly extracted the farmland parcel from the test image, and the results had a high accuracy. Despite it had a lot to do in extracting the small size parcels, on the whole the method this paper proposed had a very good robustness. Compared with the traditional methods, it had the following advantages: (1) it was an automatic extraction method, did not need too much manual intervention, and could extract the large area of farmland parcels accurately and effectively. (2) It was a very good solution to the problem of over-segmentation by using improved region merger algorithm, and improved the accuracy of the extraction. All these indicated that the proposed approach was an effective farmland parcel extraction method based on high resolution remote sensing image.
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Received: 2008-10-26
Accepted: 2009-01-28
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Corresponding Authors:
ZHU Wen-quan
E-mail: zhuwq75@ires.cn
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