Iterative TFIDF algorithm belongs to hill-climbing algorithm, it has the common problem of converging to local optimal value and sensitive to initial point.
迭代tfidf算法属于爬山算法，初始值的选取对精度影响较大，算法容易收敛到局部最优值。
This method can approach local extreme value available, but it is not the optimal solution or optimal resolution.
用这种方法可以有效逼近解的局部极小点，但不一定能得到最佳解或最佳的分辨率。
We choose collage error as local self-similarity evaluation of the image, because collage error visually represents the similarity between value range blocks and optimal matching blocks.
在图像分形编码结果的所有元素中，拼贴误差最直观地表现了值域块与其最优匹配块之间的相似程度，因而我们选用它来作为图像的局部自相似性的度量。
We choose collage error as local self-similarity evaluation of the image, because collage error visually represents the similarity between value range blocks and optimal matching blocks.
在图像分形编码结果的所有元素中，拼贴误差最直观地表现了值域块与其最优匹配块之间的相似程度，因而我们选用它来作为图像的局部自相似性的度量。
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