RAFT-HDR: FACE AWARE DEGHOSTING ALGORITHM FOR HIGH DYNAMIC RANGE IMAGING

2023-9-11
Suğur, Barış
Creating a high dynamic range (HDR) image from differently exposed images is a complex problem, especially for dynamic scenes. Most existing algorithms often match the luminance of frames to a reference image and merge exposure-matched frames into a single HDR image. However, due to the motion in the exposure bracket, this process produces artifacts such as ghosting or tearing in the merged image. These issues not only degrade the perceptual quality of the final result but also affect the accuracy of face recognition algorithms. In this thesis, we propose a face-aware optical flow-based deghosting algorithm for HDR imaging using multiple images with different exposures. We focus on preserving the facial features across the exposure bracket and in the merged HDR results. The proposed approach leverages a previous learning-based optical flow method for image alignment before merging, significantly improving facial recognition accuracy while maintaining real-time performance.
Citation Formats
B. Suğur, “RAFT-HDR: FACE AWARE DEGHOSTING ALGORITHM FOR HIGH DYNAMIC RANGE IMAGING,” M.S. - Master of Science, Middle East Technical University, 2023.