Efficient NCC-Based Image Matching in Walsh-Hadamard Domain
Abstract
In this paper, we proposed a fast image matching algorithm based on the normalized cross correlation (NCC) by applying the winner-update strategy on the Walsh-Hadamard transform. Walsh-Hadamard transform is an orthogonal transformation that is easy to compute and has nice energy packing capability. Based on the Cauchy-Schwarz inequality, we derive a novel upper bound for the cross-correlation of image matching in the Walsh-Hadamard domain. Applying this upper bound with the winner update search strategy can skip unnecessary calculation, thus significantly reducing the computational burden of NCC-based pattern matching. Experimental results show the proposed algorithm is very efficient for NCC-based image matching under different lighting conditions and noise levels.
Cite
Text
Pan et al. "Efficient NCC-Based Image Matching in Walsh-Hadamard Domain." European Conference on Computer Vision, 2008. doi:10.1007/978-3-540-88690-7_35Markdown
[Pan et al. "Efficient NCC-Based Image Matching in Walsh-Hadamard Domain." European Conference on Computer Vision, 2008.](https://mlanthology.org/eccv/2008/pan2008eccv-efficient/) doi:10.1007/978-3-540-88690-7_35BibTeX
@inproceedings{pan2008eccv-efficient,
title = {{Efficient NCC-Based Image Matching in Walsh-Hadamard Domain}},
author = {Pan, Wei-Hau and Wei, Shou-Der and Lai, Shang-Hong},
booktitle = {European Conference on Computer Vision},
year = {2008},
pages = {468-480},
doi = {10.1007/978-3-540-88690-7_35},
url = {https://mlanthology.org/eccv/2008/pan2008eccv-efficient/}
}