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Updated: May 7, 2026
26:43
Computer-Generated Animal Model Stimuli
Published on: July 29, 2007
10.5K
Hybrid patching for a sequence of differently exposed images with moving objects.
Summary
Synthesizing high dynamic range (HDR) images with moving objects is difficult due to ghosting. This study introduces a novel hybrid patching algorithm that corrects motion regions, effectively preventing ghosting artifacts in HDR images.
Area of Science:
- Computer Vision
- Image Processing
- Computational Photography
Background:
- Synthesizing High Dynamic Range (HDR) images from multiple Low Dynamic Range (LDR) images is challenging, especially with moving objects.
- Moving objects introduce ghosting artifacts in the synthesized HDR image, degrading visual quality.
Purpose of the Study:
- To develop a robust method for synthesizing artifact-free HDR images from LDR sequences containing motion.
- To address the ghosting artifact problem in HDR image reconstruction.
Main Methods:
- Formulated a new optimization problem to correct motion regions by enforcing spatial and temporal consistencies.
- Developed a hybrid patching scheme combining pixel-level intensity mapping for correction and block-level template matching for hole-filling.
- Ensured robustness against large intensity variations and over/underexposed regions.
Main Results:
- The proposed hybrid patching scheme effectively synchronizes moving objects across differently exposed images.
- Ghosting artifacts were successfully prevented in the final synthesized HDR image.
- The method demonstrated robustness in challenging imaging conditions.
Conclusions:
- The novel optimization-based hybrid patching scheme provides an effective solution for ghosting artifact removal in HDR image synthesis.
- This approach significantly improves the quality of HDR images generated from LDR sequences with dynamic scenes.
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