  Nowadays, due to advanced digital imaging technologies and internet
accessibility to the public, the number of generated digital images has
increased dramatically. Thus, the need for automatic image enhancement
techniques is quite apparent. In recent years, deep learning has been used
effectively. Here, after introducing some recently developed works on image
enhancement, an image enhancement system based on convolutional neural networks
is presented. Our goal is to make an effective use of two available approaches,
convolutional neural network and bilateral grid. In our approach, we increase
the training data and the model dimensions and propose a variable rate during
the training process. The enhancement results produced by our proposed method,
while incorporating 5 different experts, show both quantitative and qualitative
improvements as compared to other available methods.
