摘要
Division of focal plane (DoFP) polarization imaging detector are composed of integrated micro-polarizer array on a focal plane array sensor, which make the DoFP polarimeters capture the polarization information real-time. However, it is difficult to perform the DoFP demosaicking and reconstruct the polarization information due to noise. A PCA-based spatial-temporal adaptive denoising method was presented to work directly on the DoFP videos. For each DoFP patch to be denoised, similar patches were selected within a local spatial-temporal neighborhood. The principal component analysis was performed on the selected patch to remove the noise. The spatial-temporal information of DoFP video was used to construct the sample patches. The proposed method worked directly on the DoFP video without explicit motion estimation. And then a fast bilateral filtering algorithm was used to remove the residual noise in different polarization channels of DoFP images. The experimental results on simulated and real noisy DoFP sequences demonstrate that the proposed denoising method can significantly reduce the noise-caused polarization artifacts and outperform other denoising methods.
投稿的翻译标题 | PCA-based spatial-temporal adaptive denoising of DoFP video for microgrid polarimeters |
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源语言 | 繁体中文 |
文章编号 | 1026001 |
期刊 | Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering |
卷 | 48 |
期 | 10 |
DOI | |
出版状态 | 已出版 - 25 10月 2019 |
关键词
- Division of focal plane polarization imaging
- Image processing
- Principal component analysis
- Video denoising