Spatial-Temporal Color Video Reconstruction from Noisy CFA Sequence

Single-sensor digital video cameras use a color filter array (CFA) to capture video and a color demosaicking (CDM) procedure to reproduce the full color sequence. The reproduced video frames suffer from the inevitable sensor noise introduced in the video acquisition process. This paper presents a spatial-temporal denoising and demosaicking scheme that works without explicit motion estimation. We first perform patch based denoising on the mosaic CFA video. For each CFA patch to be denoised, similar patches are selected within a local spatial-temporal neighborhood. The principal component analysis is performed on the selected patches to remove noise. We then apply an initial single-frame CDM to the denoised CFA data, and subsequently post-process the demosaicked frames by exploiting the spatial-temporal redundancy to reduce the color artifacts. The experimental results on simulated and real noisy CFA sequences demonstrate that the proposed spatial-temporal CFA video denoising and demosaicking scheme can significantly reduce the noise-caused color artifacts and effectively preserve the image edge structures.