Multi-image sparse motion-invariant photography

Bart Kofoed, Eric Janssen, Peter H.N. de With

Research output: Contribution to journalConference articlepeer-review


In this paper we describe and verify a method, called SMIP, to circumvent the trade-off between motion blur and noise, specifically for scenes with predominantly two distinct linear motions (sparse motion). This is based on employing image stabilization hardware to track objects during exposure while capturing two images in quick succession. The two images are combined into a single sharp image without segmentation or local motion estimation. We provide a theoretical analysis and simulations to show that the Signal-to-Noise Ratio (SNR) increases up to 20 dB over conventional short-exposure photography. We demonstrate that the proposed method significantly improves the SNR compared to existing methods. Furthermore, we evaluate a proof-of-concept using modified off-the-shelf optical image stabilization hardware to verify the effectiveness of our method in practice, showing a good correspondence between the simulation and practical results.

Original languageEnglish
Article numberDPMI-030
Number of pages6
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Publication statusPublished - 1 Jan 2016
EventDigital Photography and Mobile Imaging XII 2016 - San Francisco, United States
Duration: 14 Feb 201618 Feb 2016


Dive into the research topics of 'Multi-image sparse motion-invariant photography'. Together they form a unique fingerprint.

Cite this