一种QaR树的图像粒优化分解方法
QaR Tree Method for Optimal Image Particle Decomposing
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摘要: 首先提出图像粒的概念,然后将所提出的概念应用于QaR树进行图像分解,最后对基于QaR树分解的结果和其他算法进行评估和对比。实验结果表明,在冗余度和精度两个指标上,基于QaR树的图像粒分解结果均优于已有方法,能够提供更为贴近图像数据和图像空间的图像局部区域。Abstract: The novel definition of image particle is proposed firstly.Then procedure of image particle decomposing is accomplished via QaR tree.Finally,the optimal comparative evaluation from QaR tree to other classic algorithms is given.Experimental results reveal that on the basis of accuracy and redundancy,QaR tree method holds better effects than other existing methods,and its results are closer to local image regions consisting of image space and image data.
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