A New Image Scaling Algorithm Based on the Sampling Theorem of Papoulis and Application to Color Images
A New Image Scaling Algorithm Based on the Sampling Theorem of Papoulis and Application to Color Images
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DOI：
10.1007/978-3-540-74260-9_1
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发表时间：
2007-08
期刊：
影响因子：
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通讯作者：
Alain Horé;D. Ziou;F. Deschênes
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文献类型：
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作者：
Alain Horé;D. Ziou;F. Deschênes
本文提出了一种新的基于Papoulis广义抽样定理的图像缩放算法。其主要思想在于在缩放过程中使用图像的一阶导数和二阶导数。这些导数包含在调整大小过程中应该保留的有关边缘和不连续点的信息。利用Papoulis抽样定理对这些信息进行组合。我们将我们的算法与八种最常见的缩放算法进行比较，并使用了两种质量度量：用于评估模糊的标准偏差和用于评估混叠的曲率。实验结果表明，该算法得到的图像混叠少，对比度好，边缘保持好，模糊少。
We present in this paper a new image scaling algorithm which is based on the generalized sampling theorem of Papoulis. The main idea consists in using the first and second derivatives of an image in the scaling process. The derivatives contain information about edges and discontinuities that should be preserved during resizing. The sampling theorem of Papoulis is used to combine this information. We compare our algorithm with eight of the most common scaling algorithms and two measures of quality are used: the standard deviation for evaluation of the blur, and the curvature for evaluation of the aliasing. The results presented here show that our algorithm gives the best images with very few aliasing, good contrast, good edge preserving and few blur.