CFA Bayer image sequence denoising and demosaicking chain
This addresses noise issues in image processing for applications like photography, but it is incremental as it builds on existing methods.
The paper tackles the problem of noise correlation and enhancement in demosaicking by proposing a novel imaging chain that denoises Bayer CFA and demosaicks image sequences simultaneously, resulting in superior performance with reduced artifacts and colored spots in final images.
The demosaicking provokes the spatial and color correlation of noise, which is afterwards enhanced by the imaging pipeline. The correct removal previous or simultaneously with the demosaicking process is not usually considered in the literature. We present a novel imaging chain including a denoising of the Bayer CFA and a demosaicking method for image sequences. The proposed algorithm uses a spatio-temporal patch method for the noise removal and demosaicking of the CFA. The experimentation, including real examples, illustrates the superior performance of the proposed chain, avoiding the creation of artifacts and colored spots in the final image.