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A structure-based image similarity measure using homogeneity regions

机译:基于结构的图像相似度测量使用均匀性区域

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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:比较两个类似的图像通常需要评估图像处理算法的有效性。但是,没有一种广泛使用的客观措施。在许多论文中,使用平均平方误差(MSE)或峰值信噪比(PSNR)。这些措施完全依赖于像素的强度。虽然这些措施很好地理解,但易于实施,但它们与感知的图像质量不好相关。本文将呈现图像质量指标,其分析图像结构而不是完全on像素。它利用递归四分之一分解提取图像结构。将呈现基于对比度,亮度和结构的相似性比较函数。

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