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A structure-based image similarity measure using homogeneity regions

机译:使用均匀性区域的基于结构的图像相似性度量

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Comparing two similar images is often needed to evaluate the effectiveness of an image processing algorithm. But, there is no one widely used objective measure. In many papers, the mean squared error (MSE) or peak signal to noise ratio (PSNR) are used. These measures rely entirely on pixel intensities. Though these measures are well understood and easy to implement, they do not correlate well with perceived image quality. This paper will present an image quality metric that analyzes image structure rather than entirely on pixels. It extracts image structure with the use of a recursive quadtree decomposition. A similarity comparison function based on contrast, luminance, and structure will be presented.
机译:通常需要比较两个相似的图像以评估图像处理算法的有效性。但是,没有一种被广泛使用的客观措施。在许多论文中,均方均误差(MSE)或峰值信噪比(PSNR)被使用。这些措施完全取决于像素强度。尽管这些措施已广为人知且易于实施,但它们与感知的图像质量并没有很好的关联。本文将提出一种图像质量指标,该指标可以分析图像结构,而不是完全基于像素。它使用递归四叉树分解提取图像结构。将给出基于对比度,亮度和结构的相似度比较功能。

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