论文标题
simpatch：图像补丁之间最近的邻居相似性匹配
SimPatch: A Nearest Neighbor Similarity Match between Image Patches
论文作者
论文摘要
测量图像中贴片之间的相似性是各种任务中的基本构建块。自然，贴片大小对匹配质量以及随之而来的应用程序性能有重大影响。我们尝试使用大型补丁而不是相对较小的补丁，以便每个补丁包含更多信息。我们使用不同的特征提取机制来提取每个单独的图像贴片的特征，该特征形成一个特征矩阵，并找出图像中最近的邻居补丁。使用本文中的两个不同的邻居算法计算最近的贴片，以查询给定图像，并在本文中证明了结果。
Measuring the similarity between patches in images is a fundamental building block in various tasks. Naturally, the patch-size has a major impact on the matching quality, and on the consequent application performance. We try to use large patches instead of relatively small patches so that each patch contains more information. We use different feature extraction mechanisms to extract the features of each individual image patches which forms a feature matrix and find out the nearest neighbor patches in the image. The nearest patches are calculated using two different nearest neighbor algorithms in this paper for a query patch for a given image and the results have been demonstrated in this paper.
