In this work, we show that an image reconstruction from a burst of individually demosaicked RAW captures propagates demosaicking
artifacts throughout the image processing pipeline. Hence, we propose a joint regularization scheme for burst denoising and demosaicking.
We model the burst alignment functions and the color filter array sampling functions into one linear operator. Then, we formulate the
individual burst reconstruction and the demosaicking problems into a three-color-channel optimization problem. We introduce a crosschannel
prior to the solution of this optimization problem and develop a numerical solver via alternating direction method of multipliers.
Moreover, our proposed method avoids the complexity of alignment estimation as a preprocessing step for burst reconstruction. It relies
on a phase correlation approach in the Fourier’s domain to efficiently find the relative translation, rotation, and scale among the burst
captures and to perform warping accordingly. As a result of these steps, the proposed joint burst denoising and demosaicking solution
improves the quality of reconstructed images by a considerable margin compared to existing image model-based methods.