We present a high dynamic range (HDR) imaging algorithm that utilizes a modern rank minimization framework. Linear dependency exists among low dynamic range (LDR) images. However, global or local misalignment by camera motion and moving objects breaks down the low-rank structure of LDR images. The proposed algorithm simultaneously estimates global geometric transforms to align LDR images and detects moving objects and under-/over-exposed regions using a rank minimization approach. In the HDR composition step, structural consistency weighting is proposed to generate an artifact-free HDR image from an user-selected reference image. We demonstrate the robustness and effectiveness of the proposed method with real datasets.
High Dynamic Range Imaging by a Rank-1 Constraint
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|저 자||Tae-Hyun Oh, Joon-Young Lee, In So Kweon|
|학 회||IEEE International Conference on Image Processing (ICIP)|
|Notes||Acknowledgement : NCRC|