HDRTransDC: High Dynamic Range Image Reconstruction with Transformer Deformation Convolution
| Autor: | Shang, Shuaikang, Kang, Xuejing, Ming, Anlong |
|---|---|
| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | High Dynamic Range (HDR) imaging aims to generate an artifact-free HDR image with realistic details by fusing multi-exposure Low Dynamic Range (LDR) images. Caused by large motion and severe under-/over-exposure among input LDR images, HDR imaging suffers from ghosting artifacts and fusion distortions. To address these critical issues, we propose an HDR Transformer Deformation Convolution (HDRTransDC) network to generate high-quality HDR images, which consists of the Transformer Deformable Convolution Alignment Module (TDCAM) and the Dynamic Weight Fusion Block (DWFB). To solve the ghosting artifacts, the proposed TDCAM extracts long-distance content similar to the reference feature in the entire non-reference features, which can accurately remove misalignment and fill the content occluded by moving objects. For the purpose of eliminating fusion distortions, we propose DWFB to spatially adaptively select useful information across frames to effectively fuse multi-exposed features. Extensive experiments show that our method quantitatively and qualitatively achieves state-of-the-art performance. Comment: We request to withdraw our manuscript due to identified issues: inaccuracies in the description of a submodule's composition, principles, and functionality in Section 3.2, and potential problems in metric calculation in Sections 4.2 and 4.3. To prevent the spread of misleading information, we believe it is necessary to temporarily withdraw the manuscript for further research and verification |
| Databáze: | arXiv |
| Externí odkaz: |
|