Object-oriented remote sensing image segmentation based on automatic multiseed region growing algorithm
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摘要: 在遙感影像分割分類中,種子區域生長算法是一種常見的分割算法.傳統的種子區域生長算法只能提取單一連續的、紋理簡單的目標地物,而對具有復雜紋理和多光譜特征的遙感影像,分割時存在分割效果差、不能同時有效地提取多個地物的問題.針對以上問題,本文提出了一種改進的面向對象的自動多種子區域生長算法.該方法適用于同時提取多個目標地物,且分割效果好.該方法首先使用一種改進的中值濾波對影像進行平滑處理,使目標內部一致性更高,同時保留紋理信息.然后通過一定的準則進行自動種子選取并進行生長,最后對生長后的區域進行碎斑合并處理,最終得到多種對象的分割結果.本文采用三組不同大小的1 m空間分辨率的航空影像進行實驗,通過與分水嶺以及傳統單種子區域生長算法的多組實驗對比,發現該方法可以面向全局對象,自動選取覆蓋各種地物類型的種子,同時對多種地物目標進行分割處理,可為后續面向對象影像分析和應用提供可靠的數據基礎.Abstract: For the segmentation of a remote sensing image, the seeded region growing algorithm is a common method. The traditional single-seed region growing algorithm can only segment a remote sensing image in a single, continuous object with simple texture. However, in the case of a high-resolution remote sensing image with complex texture and multispectral features, the segmentation result of this algorithm is unsatisfactory, as it cannot segment multiple objects simultaneously and effectively. To solve this problem, this paper proposes an improved object-oriented automatic multiseed region growing algorithm, which is suitable for simultaneously extracting multiple target objects and its segmentation result is also good. The method first uses an improved median filter to smooth the image, making the interior of the multiple target objects homogeneous, while preserving their texture. Then, it automatically selects the multiple seed regions through a certain criterion and finally, processes the grown regions and combines them. Thus, this paper obtains the segmentation results of various objects. The paper uses three sets of aerial images with different spatial resolutions to carry out experiments. Compared with watershed algorithm and traditional single-seed region growing algorithm, this method can be used for global objects. It can automatically select different types of seeds with multiple features and can simultaneously segment multiple target objects, thus providing a reliable data for the object-oriented image analysis and application.
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Key words:
- automatic seed selection /
- seed region growing /
- image segment /
- object-oriented
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參考文獻
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