Robust multiscale stereo matching from fundus images with radiometric differences.
Robust multiscale stereo matching from fundus images with radiometric differences.
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DOI：
10.1109/tpami.2011.69
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发表时间：
2011-11
影响因子：
23.6
通讯作者：
Abràmoff MD
中科院分区：
文献类型：
--
作者：
Tang L;Garvin MK;Lee K;Alward WL;Kwon YH;Abràmoff MD
提出了一种鲁棒的多尺度立体匹配算法，用于在具有辐射差异的低对比度和弱纹理视网膜图像对之间找到可靠的对应关系。设计用于处理具有不同特征和朗伯反射率的分段平面表面的现有算法不适用于诸如包括立体视网膜图像的医学图像的3D重建的应用。在本文中，强大的像素特征向量制定的尺度空间中的噪声存在下，通过低频机制的响应改变和相互作用的高频机制的响应提取判别特征。该算法通过视差估计在尺度空间的演化来表征场景的深层结构，并将匹配模糊度沿着尺度分布，以获得全局一致的重建结果。我们收集的立体眼底图像集与地面真相，这已公开作为一个扩展的标准测试图像的性能评估的性能进行了验证，无论是定性的脸的有效性和定量。
A robust multiscale stereo matching algorithm is proposed to find reliable correspondences between low contrast and weakly textured retinal image pairs with radiometric differences. Existing algorithms designed to deal with piecewise planar surfaces with distinct features and Lambertian reflectance do not apply in applications such as 3D reconstruction of medical images including stereo retinal images. In this paper, robust pixel feature vectors are formulated to extract discriminative features in the presence of noise in scale space, through which the response of low-frequency mechanisms alter and interact with the response of high-frequency mechanisms. The deep structures of the scene are represented with the evolution of disparity estimates in scale space, which distributes the matching ambiguity along the scale dimension to obtain globally coherent reconstructions. The performance is verified both qualitatively by face validity and quantitatively on our collection of stereo fundus image sets with ground truth, which have been made publicly available as an extension of standard test images for performance evaluation.