Progress in image recovery technology based on deep neural network
Jie Wang, Yiwei Shi, Lewen Liang · 2024
This paper presents the advancements in image restoration technology using deep neural networks. This paper introduces the application of deep learning in image processing, including the development of deep neural network, the advantages of convolutional neural network in image recovery, and the challenges and future trends of deep learning in image recovery. The advancements in image restoration algorithms are explored, covering the image recovery algorithm based on sparse representation, the image recovery algorithm using the variational model (VBM), and super-resolution reconstruction techniques leveraging deep learning. Through experiment and analysis, we show the effectiveness of image restoration technology based on deep neural network and compare the performance of different algorithms in image recovery. The results show that deep learning methods have better performance in image recovery tasks.