A fast computation of charlier moments for binary and gray-scale images

M. Sayyouri, A. Hmimid, H. Qjidaa
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引用次数: 18

Abstract

The discrete orthogonal moments have been shown that they represent the image better than the continuous orthogonal moments. A problem concerning the use of moments as descriptors is the highest cost of calculation. In this paper, we present the reconstruction of binary and gray-scale images by Charlier moments. The calculations of these discrete orthogonal polynomials discussed in this task, including the recurrence relation with respect to variable x and order n, we propose an efficient computation of Charlier moments for binary and gray-scale images by using image block representation IBR for binary image and PIBR for gray-scale image. The moments of image can be obtained from the moments of all blocks, thus, it can accelerate the computational efficiency since the number of blocks is less than the size of the image. Finally, the performances of Charlier moments in describing images were measured in terms of the image reconstruction error.
二值图像和灰度图像的charlier矩的快速计算
离散正交矩比连续正交矩更能代表图像。关于使用矩作为描述符的一个问题是最高的计算成本。本文提出了利用查利叶矩重建二值图像和灰度图像的方法。在本任务中讨论了这些离散正交多项式的计算,包括关于变量x和阶n的递归关系,我们提出了一种有效的计算二值和灰度图像的Charlier矩的方法,该方法使用图像块表示IBR(二值图像)和PIBR(灰度图像)。图像的矩可以从所有块的矩中得到,因此,由于块的数量小于图像的大小,可以加快计算效率。最后,用图像重建误差来衡量查利叶矩在描述图像中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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