Combining deblurring and denoising for handheld HDR imaging in low light conditions

This paper proposes a probability formulation that unifies both single-image deblurring and multi-image denoising using variational inference. The proposed formulation is based on a theoretical analysis that compares denoising and deblurring in the same probabilistic framework, and supported by a practical approach that deal with general motion that creates HDR images in the presence of spatially varying motion. Based on this formulation, a new algorithm for deblurring a noisy and blurry image pair is presented. Besides, we provide also an approach that combines existing optical flow and image denoising techniques for High Dynamic Range imaging.

(a, b) Tone mapped image of (a); (c) Our output; (d) The ground truth for comparison.Figure optionsDownload as PowerPoint slideHighlights
► A probability formulation that unifies both single-image deblurring and multi-image denoising using variational inference.
► A new algorithm for deblurring a noisy and blurry image pair.
► An approach that combines existing optical flow and image denoising techniques for High Dynamic Range imaging.