Patch-based multiple view image denoising with occlusion handling

Shiwei Zhou; Yu Hen Hu; Hongrui Jiang

ICASSP 2017accepted0 citations

Patch-based multiple view image denoising with occlusion handling

Abstract

A novel patch-based multi-view image denoising algorithm is proposed. This method leverages the 3D focus image stacks structure to exploit self-similarity and image redundancy inherent in multiple view images. Then a depth-guided adaptive window and dynamic view selection criterion is developed to aid proper selection of most consistent patches for the multi-view image denoising. Extensive experiments have been performed. Comparing the outcomes against those of state of the art image denoising algorithms, our proposed algorithm demonstrates significant performance advantage.

BibTeX

@inproceedings{icassp2017_patchbasedmultip,
  title = {Patch-based multiple view image denoising with occlusion handling},
  author = {Shiwei Zhou and Yu Hen Hu and Hongrui Jiang},
  booktitle = {ICASSP 2017},
  year = {2017}
}