Abstract
This paper proposes a restoration method for JPEG and blurred images based on ensemble learning algorithm. Such as a median filter, various restoration filters for these images have been already proposed and applied in real images. However, when images have edge and non-edge regions, it is difficult for single filter having fixed coefficients to reduce both blocky and mosquito noises adequately. Here, new restoration methods for JPEG and blurred images are proposed by introducing multiple muliti-layered neural networks. Each neural network can be adapted for edge, flat, and texture regions in images by ensemble learning. From experimental results, the proposed method can obtain good restoration accuracy compared with conventional filters. Moreover, we have confirmed that the proposed method could automatically assign restoration tasks to each neural network according to the characteristics of each region in given distorted images.
