Disparity-based HDR imaging
This work addresses a domain-specific issue in computer vision for HDR imaging, but it appears incremental as it builds on prior disparity-based approaches.
The paper tackles the problem of acquiring high-dynamic range values for multi-stereo images by identifying limitations in existing disparity-based methods and proposing heuristic solutions for problematic cases.
High-dynamic range imaging permits to extend the dynamic range of intensity values to get close to what the human eye is able to perceive. Although there has been a huge progress in the digital camera sensor range capacity, the need of capturing several exposures in order to reconstruct high-dynamic range values persist. In this paper, we present a study on how to acquire high-dynamic range values for multi-stereo images. In many papers, disparity has been used to register pixels of different images and guide the reconstruction. In this paper, we show the limitations of such approaches and propose heuristics as solutions to identified problematic cases.