Abstract
Event cameras, with a high dynamic range exceeding $120dB$, significantly outperform traditional embedded cameras, robustly recording detailed changing information under various lighting conditions, including both low- and high-light situations. However, recent research on utilizing event data has primarily focused on low-light image enhancement, neglecting image enhancement and brightness adjustment across a broader range of lighting conditions, such as normal or high illumination. Based on this, we propose a novel research question: how to employ events to enhance and adaptively adjust the brightness of images captured under broad lighting conditions? To investigate this question, we first collected a new dataset, SEE-600K, consisting of 610,126 images and corresponding events across 202 scenarios, each featuring an average of four lighting conditions with over a 1000-fold variation in illumination. Subsequently, we propose a framework that effectively utilizes events to smoothly adjust image brightness through the use of prompts. Our framework captures color through sensor patterns, uses cross-attention to model events as a brightness dictionary, and adjusts the image's dynamic range to form a broad light-range representation (BLR), which is then decoded at the pixel level based on the brightness prompt. Experimental results demonstrate that our method not only performs well on the low-light enhancement dataset but also shows robust performance on broader light-range image enhancement using the SEE-600K dataset. Additionally, our approach enables pixel-level brightness adjustment, providing flexibility for post-processing and inspiring more imaging applications. The dataset and source code are publicly available at:this https URL.
Abstract (translated)
事件相机，其动态范围超过$120dB$，在各种光照条件下（包括低光和高光情况）记录详细变化信息方面远超传统嵌入式摄像头。然而，最近利用事件数据的研究主要集中在低光图像增强上，忽略了在整个更广泛的照明条件下的图像增强与亮度调节，如正常或高强度光线环境。基于此，我们提出一个新的研究问题：如何使用事件来增强并自适应地调整不同光照条件下捕捉到的图像亮度？为了解决这个问题，我们首先收集了一个新的数据集SEE-600K，该数据集中包含610,126张图像及其对应事件，覆盖了202个场景，每个场景平均包括四种照明条件，且光照变化范围超过千倍。随后，我们提出了一种框架，通过使用提示词有效利用事件来平滑地调整图像亮度。我们的框架通过传感器模式捕捉颜色，使用交叉注意力机制将事件建模为一个亮度字典，并调节图像的动态范围以形成广域光级表示（BLR），然后根据亮度提示在像素级别解码该表示。 实验结果显示，我们提出的方法不仅在低光照增强数据集上表现出色，在利用SEE-600K数据集进行广泛照明条件下的图像增强时也展现了强大的性能。此外，我们的方法还提供了像素级别的亮度调节功能，为后期处理提供灵活性，并激发了更多的成像应用可能性。该数据集和源代码可在此处公开获取：[此链接指向发布数据集和代码的网页]。
URL
https://arxiv.org/abs/2502.21120
