High Dynamic Range Video Synthesis Using Superpixel-Based Illuminance-Invariant Motion Estimation

Tu Van Vo, Chul Lee

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We propose a robust high dynamic range (HDR) video synthesis algorithm using the superpixel-based illuminance-invariant motion estimation technique. The proposed algorithm first selects an input frame in an alternating exposed input video as the reference. Then, the correspondences between two adjacent frames are estimated by employing a feature descriptor, which is robust against illuminance variation, and a superpixel segmentation technique. Next, the input frames are warped to the reference frame using the estimated motion maps. Finally, the final HDR frame is synthesized by constructing a weight map, which can handle complex motions and poor exposures by considering the underlying structures in the input frames. Experimental results on real test sequences show that the proposed algorithm can provide high-quality HDR videos compared with those obtained by state-of-the-art algorithms in terms of both subjective and objective evaluations.

Original languageEnglish
Article number8977532
Pages (from-to)24576-24587
Number of pages12
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • HDR imaging
  • High dynamic range (HDR) video synthesis
  • motion estimation

Fingerprint

Dive into the research topics of 'High Dynamic Range Video Synthesis Using Superpixel-Based Illuminance-Invariant Motion Estimation'. Together they form a unique fingerprint.

Cite this