分类： 计算机科学 >> 计算机应用技术 提交时间： 2020-04-14
摘要： Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the enhancement pipeline. In this work, we propose an adaptive low-light raw image enhancement network to avoid parameter-handcrafting and to improve image quality. The proposed method can be divided into two sub-models: Brightness Prediction (BP) and Exposure Shifting (ES). The former is designed to control the brightness of the resulting image by estimating a guideline exposure time t 1 . The latter learns to approximate an exposure-shifting operator ES, converting a low-light image with real exposure time t 0 to a noise-free image with guideline exposure time t 1 . Additionally, structural similarity (SSIM) loss and Image Enhancement Vector (IEV) are introduced to promote image quality, and a new Campus Image Dataset (CID) is proposed to overcome the limitations of the existing datasets and to supervise the training of the proposed model. In quantitative tests, it is shown that the proposed method has the lowest Noise Level Estimation (NLE) score compared with BM3D-based low-light algorithms, suggesting a superior denoising performance. Furthermore, those tests illustrate that the proposed method is able to adaptively control the global image brightness according to the content of the image scene. Lastly, the potential application in video processing is briefly discussed.
分类： 心理学 >> 认知心理学 提交时间： 2020-04-14
摘要： 高级语义信息是否能被无意识地感知和加工一直是整个心理学界广泛探讨并具有争议的问题。研究针对2004年Tsuchiya提出的用于研究阈下加工的新范式——连续闪烁抑制范式(CFS, continuous flash suppression)，探究了高级语义信息在这一范式中的加工情况，并对比了该范式的两项变式，CFS下启动效应和突破-连续闪动抑制(b-CFS)。研究结果发现，就CFS范式来看，语义加工存在于无意识情景中，这一结果与Van den Bussche等(2009)的元分析结果一致，但CFS下启动范式的元分析结果并不与先前研究一致。我们推测，这是由于CFS虽然增长了无意识加工的时间，但是实际上干扰了正常的无意识加工过程，导致实际的效应没有启动范式强。
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