Tensor voting for image correction by global and local intensity alignment

Abstract

This work presents a voting method to perform image correction by global and local intensity alignment. The key to our modeless approach is the estimation of global and local replacement functions by reducing the complex estimation problem to the robust 2D tensor voting in the corresponding voting spaces. No complicated model for replacement function (curve… (More)
DOI: 10.1109/TPAMI.2005.20

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@article{Jia2005TensorVF, title={Tensor voting for image correction by global and local intensity alignment}, author={Jiaya Jia and C. Q. Tang}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, year={2005}, volume={27}, pages={36-50} }