Name
Abstract | ||
|---|---|---|
The irradiance range of the real-world scene is often beyond the capability of digital cameras. Therefore, High Dynamic Range (HDR) images can be generated by fusing images with different exposure of the same scene. However, moving objects pose the most severe problem in the HDR imaging, leading to the annoying ghost artifacts in the fused image. In this paper, we present a novel HDR technique to address the moving objects problem. Since the input low dynamic range (LDR) images captured by a camera act as static linear related backgrounds with moving objects during each individual exposures, we formulate the detection of foreground moving objects as a rank minimization problem. Meanwhile, in order to eliminate the image blurring caused by background slightly change of LDR images, we further rectify the background by employing the irradiances alignment. Experiments on image sequences show that the proposed algorithm performs significant gains in synthesized HDR image quality compare to state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11042-018-6625-x | Multimedia Tools and Applications |
Keywords | Field | DocType |
High dynamic range imaging, Multi-exposure fusion, Rank minimization, Optical flow, Motion blur, Ghost removal | Computer vision,Pattern recognition,Computer science,Low dynamic range,Image quality,Motion blur,Artificial intelligence,Rank minimization,High-dynamic-range imaging,Optical flow,High dynamic range | Journal |
Volume | Issue | ISSN |
78.0 | 9 | 1573-7721 |
Citations | PageRank | References |
5 | 0.41 | 29 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan, Q. | 1 | 70 | 7.01 |
| Yu Zhu | 2 | 88 | 12.65 |
| Yanning Zhang | 3 | 1613 | 176.32 |