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Improved structural similarity metric for the visible quality measurement of images

机译:改进的结构相似性度量,用于图像的可见质量测量

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The visible quality assessment of images is important to evaluate the performance of image processing methods such as image correction, compressing, and enhancement. The structural similarity is widely used to determine the visible quality; however, existing structural similarity metrics cannot correctly assess the perceived human visibility of images that have been slightly geometrically transformed or images that have undergone significant regional distortion. We propose an improved structural similarity metric that is more close to human visible evaluation. Compared with the existing metrics, the proposed method can more correctly evaluate the similarity between an original image and various distorted images. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.
机译:图像的可见质量评估对于评估图像处理方法(例如图像校正,压缩和增强)的性能很重要。结构相似性被广泛用于确定可见质量。但是,现有的结构相似性度量标准无法正确评估经过略微几何变换的图像或经历了重大区域失真的图像的感知人类可见性。我们提出了一种改进的结构相似性度量,该度量更接近于人类可见的评估。与现有度量相比,该方法可以更正确地评估原始图像与各种失真图像之间的相似度。 (C)作者。由SPIE根据Creative Commons Attribution 3.0 Unported License发布。

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