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A Small-Space Algorithm for Removing Small Connected Components from a Binary Image

机译:一种从二进制图像中删除小的连通组件的小空间算法

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Given a binary image ∮ and a threshold t, the size-thresholded binary image ∮(t) denned by ∮ and t is the binary image after removing all connected components consisting of at most t pixels. This paper presents space-efficient algorithms for computing a size-thresholded binary image for a binary image of n pixels, assuming that the image is stored in a read-only array with random-access. With regard to the problem, there are two cases depending on how large the threshold t is, namely, Relatively large threshold where t = Ω(n~(1/2)), and Relatively small threshold where t = O(n~(1/2)). In this paper, a new algorithmic framework for the problem is presented. From an algorithmic point of view, the problem can be solved in 0(n) time and O(n) work space. We propose new algorithms for both the above cases which compute the size-threshold binary image for any binary image of n pixels in O(nlogn) time using only O(n~(1/2)) work space.
机译:给定一个二值图像∮和一个阈值t,由∮和t定义的尺寸阈值二值图像∮(t)是在除去所有最多由t个像素组成的连接分量之后的二值图像。本文提出了一种空间高效的算法,用于计算n像素二进制图像的尺寸阈值二进制图像,并假设该图像存储在具有随机访问权限的只读阵列中。关于该问题,根据阈值t的大小,存在两种情况,即,t =Ω(n〜(1/2))的阈值较大,而t = O(n〜(2)的阈值较小。 1/2))。本文提出了一种新的算法框架。从算法的角度来看,可以在0(n)时间和O(n)工作空间中解决问题。对于以上两种情况,我们提出了新的算法,这些算法仅使用O(n〜(1/2))个工作空间即可计算O(nlogn)时间中n个像素的任何二进制图像的尺寸阈值二进制图像。

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