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Complex Wavelet Structural Similarity: A New Image Similarity Index

机译:复小波结构相似性:新的图像相似性指标

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We introduce a new measure of image similarity called the complex wavelet structural similarity (CW-SSIM) index and show its applicability as a general purpose image similarity index. The key idea behind CW-SSIM is that certain image distortions lead to consistent phase changes in the local wavelet coefficients, and that a consistent phase shift of the coefficients does not change the structural content of the image. By conducting four case studies, we have demonstrated the superiority of the CW-SSIM index against other indices (e.g., Dice, Hausdorff distance) commonly used for assessing the similarity of a given pair of images. In addition, we show that the CW-SSIM index has a number of advantages. It is robust to small rotations and translations. It provides useful comparisons even without a preprocessing image registration step, which is essential for other indices. Moreover, it is computationally less expensive.
机译:我们介绍了一种新的图像相似性度量,称为复杂小波结构相似性(CW-SSIM)指标,并展示了其作为通用图像相似性指标的适用性。 CW-SSIM背后的关键思想是某些图像失真会导致局部小波系数出现一致的相位变化,并且系数的一致相移不会改变图像的结构内容。通过进行四个案例研究,我们证明了CW-SSIM指数优于通常用于评估给定图像对相似性的其他指数(例如Dice,Hausdorff距离)。此外,我们证明CW-SSIM索引具有许多优点。它对于较小的旋转和平移具有鲁棒性。即使没有预处理图像配准步骤,它也可以提供有用的比较,这对于其他索引来说是必不可少的。而且,它在计算上更便宜。

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