基于小波的图像边界配准

将碎片图像拼接成原始图像是一项非常有实用价值的应用,寻找匹配边是关健一环。首先对角点间边界L0变换为具有旋转不变性的曲线L1,利用小波包对L1进行分解和重构,获得不同分辨率下的边界曲线L2。然后,对L2进行离散余弦变换,得到一组特征矢量,求特征矢量间的欧氏距离D,D值最小的两个矢量对应的边界为相似边界,再对相似边界进行配准。从而达到拼接图像碎片恢复原始图像的目的。该算法具有识别相似边准确和旋转不变性的特点。

Wavelet-based image registration by using boundary features

Putting pieces of images together into the original image is a valuable application， one key step is to search the matched edges.First，we transform all the edges between two corners into curve L₁，which is rotationally invariant，then decomposite and reconstruct L₁ by using wavelet packet analysis to get the edge curve L₂ in different resolution.Then L₂ are transformed by DCT（Discrete Cosine Transformation） into feature vectors.The similar pairs of edges on different pieces are selected by calculating the minimal Euclidean distance between feature vectors，then the boundary registration can be done and the original image can be restored from the pieces.This algorithm can find alike edges accurately，is rotationally invariant.