将单光子相机的黑白图像转为彩色高动态范围图像
Transforming Single Photon Camera Images to Color High Dynamic Range Images
- 用先进模型将SPAD传感器的单色图像转为彩色HDR图
- 在多分辨率下验证效果,显著提升视觉质量与动态范围
- 适合做高动态范围成像、低光摄影的研究者参考
传统CMOS传感器在极端光照条件下动态范围受限,低光时受电子噪声影响,高照度时易饱和。现有高动态范围(HDR)成像方法多针对CMOS设计,通过多曝光融合缓解问题,但在动态场景中常引入鬼影和闪烁伪影,且在极端动态范围内信噪比不均。近年来,单光子雪崩二极管(SPAD)传感器,即单光子相机(SPC),凭借直接探测单个光子并具备高时间精度的优势,超越了传统传感器。与先将光能转为模拟电流再数字化的CMOS不同,SPAD实现直接光子检测,对极端光照更鲁棒。其非线性响应曲线使其在弱光与强光环境下均能有效捕捉光子,适用于高动态范围成像。然而,SPAD图像通常噪声大、视觉效果差。为此,我们评估了当前最先进的架构,用于将不同分辨率下的单色SPAD图像转换为彩色高动态范围图像。评估涵盖定性和定量分析,聚焦各转换阶段的有效性。
原文摘要 · Abstract (English)
Traditional CMOS sensors suffer from restricted dynamic range and sub optimal performance under extreme lighting conditions. They are affected by electronic noise in low light conditions and pixel saturation while capturing high illumination. Recent High Dynamic Range (HDR) Imaging methods, often designed for CMOS Sensors, attempt to address these issues by fusing multiple exposures. However, they frequently introduce artifacts like ghosting and light flickering in dynamic scenarios and non-uniform signal-to-noise ratio in extreme dynamic range conditions. Recently, Single Photon Avalanche Diodes (SPADs), also known as Single Photon Camera (SPC) sensors, have surpassed CMOS sensors due to their capability to capture individual photons with high timing precision. Unlike traditional digital cameras that first convert light energy into analog electrical currents and then digitize them, SPAD sensors perform direct photon detection, making them less susceptible to extreme illumination conditions. Their distinctive non-linear response curve aids in capturing photons across both low-light and high-illumination environments, making them particularly effective for High Dynamic Range Imaging. Despite their advantages, images from SPAD Sensors are often noisy and visually unappealing. To address these challenges, we evaluate state-of-the-art architectures for converting monochromatic SPAD images into Color HDR images at various resolutions. Our evaluation involves both qualitative and quantitative assessments of these architectures, focusing on their effectiveness in each stage of the conversion process.
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