Abstract
Low-light image enhancement is crucial for a myriad of applications, from night vision and surveillance, to autonomous driving. However, due to the inherent limitations that come in hand with capturing images in low-illumination environments, the task of enhancing such scenes still presents a formidable challenge. To advance research in this field, we introduce our Low Exposure Night Vision (LENVIZ) Dataset, a comprehensive multi-exposure benchmark dataset for low-light image enhancement comprising of over 230K frames showcasing 24K real-world indoor and outdoor, with-and without human, scenes. Captured using 3 different camera sensors, LENVIZ offers a wide range of lighting conditions, noise levels, and scene complexities, making it the largest publicly available up-to 4K resolution benchmark in the field. LENVIZ includes high quality human-generated ground truth, for which each multi-exposure low-light scene has been meticulously curated and edited by expert photographers to ensure optimal image quality. Furthermore, we also conduct a comprehensive analysis of current state-of-the-art low-light image enhancement techniques on our dataset and highlight potential areas of improvement.
Abstract (translated)
低光图像增强对于夜视、监控和自动驾驶等多种应用至关重要。然而，由于在低光照环境下拍摄照片时会遇到固有的局限性，提高这些场景质量的任务仍然充满挑战。为了推动该领域的研究进展，我们推出了《低曝光夜视（LENVIZ）数据集》，这是一个全面的多曝光基准数据集，专门用于低光图像增强，包含超过230,000帧的真实世界室内和室外场景，涵盖有人与无人的情况，总计展示出24,000多个场景。该数据集使用三种不同的相机传感器采集而成，并提供了广泛的不同光照条件、噪声水平及场景复杂度的样本，使其成为目前公开可用的最大规模低光图像增强基准数据集之一，最高可达4K分辨率。 LENVIZ数据集包括高质量的人工生成的真实标注，每个多曝光低光场景均由专业摄影师精心策划和编辑，以确保最佳图像质量。此外，我们还在我们的数据集上对当前最先进的低光图像增强技术进行了全面分析，并指出了潜在的改进领域。
URL
https://arxiv.org/abs/2503.19804
