Scale Selection of Adaptive Kernel Regression by Joint Saliency Map for Nonrigid Image Registration

3 Mar 2013Zhuangming ShenJiuai SunHui ZhangBinjie Qin

Joint saliency map (JSM) [1] was developed to assign high joint saliency values to the corresponding saliency structures (called Joint Saliency Structures, JSSs) but zero or low joint saliency values to the outliers (or mismatches) that are introduced by missing correspondence or local large deformations between the reference and moving images to be registered. JSM guides the local structure matching in nonrigid registration by emphasizing these JSSs' sparse deformation vectors in adaptive kernel regression of hierarchical sparse deformation vectors for iterative dense deformation reconstruction... (read more)

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