论文标题
用于模糊图像检测的卷积神经网络作为拉普拉斯法的替代方法
Convolutional Neural Network for Blur Images Detection as an Alternative for Laplacian Method
论文作者
论文摘要
随着数码相机的流行，数字图像的数量迅速增加，这增加了对非手动图像质量评估的需求。尽管有许多方法被认为可用于检测模糊，但在本文中，我们提出并评估了一种使用深卷积神经网络的新方法，该方法可以确定图像是否模糊。实验结果证明了所提出的方案的有效性，并与使用混淆矩阵的确定性方法进行了比较。
With the prevalence of digital cameras, the number of digital images increases quickly, which raises the demand for non-manual image quality assessment. While there are many methods considered useful for detecting blurriness, in this paper we propose and evaluate a new method that uses a deep convolutional neural network, which can determine whether an image is blurry or not. Experimental results demonstrate the effectiveness of the proposed scheme and are compared to deterministic methods using the confusion matrix.
