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基于最小核值相似区算法的高分辨率遥感图像分割方法

DOI: 10.6046/gtzyyg.2011.04.07, PP. 37-41

Keywords: 最小核值相似区算法(SUSAN),分水岭变换(WT),QuickBird图像,图像分割

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Abstract:

采用最小核值相似区算法(SmallestUnivalueSegmentAssimilatingNucleus,SUSAN)计算QuickBird图像的梯度,并采用标记控制的分水岭变换(WatershedTransform,WT)算法分割图像,取得了较好的结果。SUSAN方法能有效地检测图像梯度,对噪声不敏感;梯度值范围明确,不因图像而改变,为后续处理相关参数的选择提供了便利;亮度阈值容易确定,模板半径可选,具有很大的灵活性;适合于采用WT的遥感图像的分割。采用基于SUSAN梯度和NDVI的标记图像,利用形态学灰度图像重建方法修改梯度图像,能够有效地抑制梯度图像中大量的局部灰度极小值,提高WT图像分割的精度。

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