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Image quality measure via a quadtree homogeneity analysis

机译:通过Quadtree同质性分析图像质量测量

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There are many uses of an image quality measure. It is often used to evaluate the effectiveness of an image processing algorithm, yet 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. 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 quadtree decomposition. A similarity comparison function based on contrast, luminance, and structure will be presented.
机译:图像质量测量有很多用途。 它通常用于评估图像处理算法的有效性,但没有一种广泛使用的客观度量。 在许多论文中,使用平均平方误差(MSE)或峰值信噪比(PSNR)。 虽然这些措施很好地理解,并且易于实施,但它们与感知的图像质量不好。 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。 它利用四叉树分解提取图像结构。 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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