Pyramid Inter-Attention for High Dynamic Range Imaging

Sensors

卷:20

Sungil Choi¹  Kwanghoon Sohn¹  Jaehoon Cho¹  Wonil Song¹  Jihwan Choe²  Jisung Yoo² 

[1] Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea;

[2] Samsung Electronics, Suwon 16677, Korea;

关键词: HDR imaging;    attention mechanisms;    optical flow;   

DOI  :  10.3390/s20185102

来源: DOAJ

【 摘 要 】

This paper proposes a novel approach to high-dynamic-range (HDR) imaging of dynamic scenes to eliminate ghosting artifacts in HDR images when in the presence of severe misalignment (large object or camera motion) in input low-dynamic-range (LDR) images. Recent non-flow-based methods suffer from ghosting artifacts in the presence of large object motion. Flow-based methods face the same issue since their optical flow algorithms yield huge alignment errors. To eliminate ghosting artifacts, we propose a simple yet effective alignment network for solving the misalignment. The proposed pyramid inter-attention module (PIAM) performs alignment of LDR features by leveraging inter-attention maps. Additionally, to boost the representation of aligned features in the merging process, we propose a dual excitation block (DEB) that recalibrates each feature both spatially and channel-wise. Exhaustive experimental results demonstrate the effectiveness of the proposed PIAM and DEB, achieving state-of-the-art performance in terms of producing ghost-free HDR images.

【 授权许可】

Unknown