计算机科学 ›› 2016, Vol. 43 ›› Issue (2): 89-94.doi: 10.11896/j.issn.1002-137X.2016.02.020
• 2015年中国计算机学会人工智能会议 • 上一篇 下一篇
舒速,杨明
SHU Su and YANG Ming
摘要: 近年来,高光谱图像的分类受到了广泛的关注。许多机器学习的方法都在高光谱图像上得到了应用,如SVM、神经网络、决策树等。但光谱图像可能存在“同物异谱”和“同谱异物”的情况,这给高光谱图像的精确分类带来了一定挑战。针对该问题,提出了利用分水岭分割得到的空间信息与稀疏表示来得到更精确的分类结果。首先利用分水岭得到图像区域信息,然后以区域为单位,对每个区域的样本进行分类。在两幅图像上对该方法的有效性进行了验证,结果表明该方法优于其它一些同类方法。
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