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SIRA - An efficient method for retrieving stereo images from anaglyphs
Signal Processing: Image Communication ( IF 3.5 ) Pub Date : 2020-04-22 , DOI: 10.1016/j.image.2020.115866
Lucas Felipe Kunze , Rudinei Goularte , Elaine Parros Machado de Sousa

Anaglyph reversion aims to recover the best possible approximation of a stereo pair of images from an anaglyph. Possible applications include a range of practical situations like enabling visualization of legacy anaglyphs on the Web, saving storage/transmission bandwidth by encoding stereo pairs as anaglyphs before stereo visualization or enabling users to enjoy stereo visualization using any available device. The recovering process faces a challenging issue: the anaglyphic stereo matching. Different from regular stereo images, corresponding pixels in the left and right views of an anaglyph have dissimilar intensity values, lowering photometric consistency and thus turning the usual stereo matching algorithms not suitable. In this work we propose SIRA, an efficient method for anaglyph reversion, introducing a novel approach to find stereo correspondences based on a pixel descriptor developed to deal with anaglyphic photometric differences. The descriptor core idea is to model stereo pairs as time series, extracted from both views of an anaglyph. The series are then compared through a time series matching algorithm, providing a faster, yet accurate, pixels alignment. Occlusions are dealt with using a colorization strategy based on the nearest neighbor search. We evaluate SIRA’s computational efficiency and both objective and subjective image quality on the well-known Middlebury dataset. We also compared SIRA with state of the art related methods. The results show SIRA achieves equivalent image quality while consuming 26 times less computational resources, on average. Therefore, SIRA shows up as an effective and efficient method to convey anaglyph reversion, advantaging the aforementioned applications.



中文翻译:

SIRA-从立体浮雕检索立体图像的有效方法

浮雕还原的目的是从浮雕中恢复图像的立体声对的最佳近似。可能的应用包括一系列实际情况,例如启用Web上的旧浮雕的可视化,通过在立体可视化之前将立体对编码为浮雕来节省存储/传输带宽或使用户能够使用任何可用的设备来欣赏立体可视化。恢复过程面临一个具有挑战性的问题:浮雕立体匹配。与常规立体图像不同,立体图的左视图和右视图中的对应像素具有不同的强度值,从而降低了光度学一致性,因此使常规的立体匹配算法变得不合适。在这项工作中,我们提出了SIRA,一种有效的浮雕还原方法,引入了一种新颖的方法,该方法基于为处理浮雕光度学差异而开发的像素描述符来查找立体对应关系。描述符的核心思想是将立体对建模为时间序列,从立体图的两个视图中提取。然后通过时间序列匹配算法比较序列,从而提供更快但准确的像素对齐。使用基于最近邻居搜索的着色策略来处理遮挡。我们在著名的Middlebury数据集上评估SIRA的计算效率以及客观和主观图像质量。我们还将SIRA与相关技术水平进行了比较。结果表明,SIRA可以实现同等的图像质量,同时平均减少26倍的计算资源。因此,

更新日期:2020-04-22
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