不规则子采样中边的重要性

Alexander Stoffel, Anissa Zergaïnoh-Mokraoui, C. Kulcsár, J. Astruc
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引用次数: 0

摘要

重建图像的质量,从一组非常弱的不规则间隔像素,很大程度上取决于像素在图像网格上的定位。两种不同的子采样方法表明,像素的分布与图像的特征密切相关。第一种方法基于第二代小波,将原始图像分解为多个子集。属于每个子集的像素根据阈值进行分布。第二种方法选择重构图像均方误差最小的子集。重建方法是一种二维统计插值方法。两种方法提供的像素子集具有相似的特征。实验结果表明,大多数像素点位于锐边缘区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The importance of edges in irregular subsampling
The quality of the reconstructed image, from a very weak set of irregularly spaced pixels, depends strongly on the localization of pixels on the image grid. Two different subsampling methods show that the distribution of the pixels is closely linked to the characteristics of the image. The first method, based on the second generation of wavelets decomposes the original image in several subsets. Pixels belonging to each subset are distributed according to a threshold. The second method chooses the subset minimizing the mean square error of the reconstructed image. The reconstruction method is a two-dimensional statistical interpolation method. Both subsets of pixels, provided by the two methods, have similar characteristics. Experimental results are provided and show that most of pixels are located in sharp edge regions.
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