首页> 外文会议>2011 International Conference on Electric Information and Control Engineering >Thresholding of a sonar image from a small underwater object using the maximum entropy of the one-dimensional bound histogram
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Thresholding of a sonar image from a small underwater object using the maximum entropy of the one-dimensional bound histogram

机译:使用一维绑定直方图的最大熵对来自小型水下物体的声纳图像进行阈值处理

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The concept of the one-dimensional bound histogram was given. It is the one-dimensional histogram bound by some prior knowledge, and it can make some image processing methods be simple and feasible. Furthermore, a thresholding method based on the maximum entropy of the one-dimensional bound histogram is proposed. In the method, Pun entropy function is established by means of the bound histogram instead of the usual one. In applying the method to thresholding a sonar image of a small underwater object, the bound set is constructed according to the restriction in the gray-level values of both pixels and their neighborhood averages, and the one-dimensional bound histogram corresponding to that bound set is established according to the concept of the one-dimensional bound histogram. The experimental results show that the proposed method can succeed in thresholding a sonar image of a small underwater object. The proposed method is applicable to the image in which there is prior knowledge.
机译:给出了一维边界直方图的概念。它是受某些先验知识约束的一维直方图,它可以使某些图像处理方法简单可行。此外,提出了一种基于一维有界直方图的最大熵的阈值化方法。在该方法中,Pun熵函数是通过绑定直方图而不是通常的直方图来建立的。在将该方法应用于对小的水下物体的声纳图像进行阈值处理时,根据两个像素的灰度级值及其邻域平均值的限制以及与该边界集相对应的一维边界直方图来构造边界集。根据一维边界直方图的概念建立。实验结果表明,该方法可以成功地对水下小物体的声纳图像进行阈值处理。所提出的方法适用于具有先验知识的图像。

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