用3D查找表实现手机端实时超高清多曝光融合。
Multi-Exposure Image Fusion via Distilled 3D LUT Grid with Editable Mode
- 用教师-学生网络建模曝光不确定性，提升3D查找表泛化能力。
- 在资源受限设备上实现超高清图像实时融合，速度优于现有方法。
- 支持可编辑模式，适配不同应用场景需求。
随着手持设备成像分辨率不断提升，现有多曝光图像融合算法难以在资源受限设备上实时生成超高清（UHD）高动态范围图像。同时，实际应用对算法可管理性和可编辑性提出更高要求。为此，本文引入3D LUT技术，在低功耗设备上实现实时超高清图像增强。针对不同曝光率图像融合中存在信息不确定的问题，该不确定性显著挑战3D LUT网格的泛化能力，本文提出基于教师-学生网络的模型，以构建鲁棒的学习空间。此外，通过隐式表示函数实现可编辑模式，灵活匹配多样化应用需求。大量实验表明，所提方法在效率与精度上均具有较强竞争力。
原文摘要 · Abstract (English)
With the rising imaging resolution of handheld devices, existing multi-exposure image fusion algorithms struggle to generate a high dynamic range image with ultra-high resolution in real-time. Apart from that, there is a trend to design a manageable and editable algorithm as the different needs of real application scenarios. To tackle these issues, we introduce 3D LUT technology, which can enhance images with ultra-high-definition (UHD) resolution in real time on resource-constrained devices. However, since the fusion of information from multiple images with different exposure rates is uncertain, and this uncertainty significantly trials the generalization power of the 3D LUT grid. To address this issue and ensure a robust learning space for the model, we propose using a teacher-student network to model the uncertainty on the 3D LUT grid.Furthermore, we provide an editable mode for the multi-exposure image fusion algorithm by using the implicit representation function to match the requirements in different scenarios. Extensive experiments demonstrate that our proposed method is highly competitive in efficiency and accuracy.
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