| Autor: |
Ke Xu, Qin Wang, Huangqing Xiao, Kelin Liu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Neurorobotics, Vol 16 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1662-5218 |
| DOI: |
10.3389/fnbot.2022.846580 |
| Popis: |
High-dynamic-range (HDR) image has a wide range of applications, but its access is limited. Multi-exposure image fusion techniques have been widely concerned because they can obtain images similar to HDR images. In order to solve the detail loss of multi-exposure image fusion (MEF) in image reconstruction process, exposure moderate evaluation and relative brightness are used as joint weight functions. On the basis of the existing Laplacian pyramid fusion algorithm, the improved weight function can capture the more accurate image details, thereby making the fused image more detailed. In 20 sets of multi-exposure image sequences, six multi-exposure image fusion methods are compared in both subjective and objective aspects. Both qualitative and quantitative performance analysis of experimental results confirm that the proposed multi-scale decomposition image fusion method can produce high-quality HDR images. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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