Title :
Integrated recurrent neural network for image resolution enhancement from multiple image frames
Author :
Salari, E. ; Zhang, S.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, OH, USA
Abstract :
The paper presents a new method for image resolution enhancement from multiple image frames using an integrated recurrent neural network (IRNN). The IRNN is a set of feedforward neural networks working collectively with the ability of having feedback of information from its output to its input. As such, it is capable of both learning and searching the optimal solution in the solution space for optimisation problems. In other words, it combines the advantages of both the Hopfield network and the multilayered feedforward network in solving the enhanced image reconstruction problem. Simulation results demonstrate that the proposed IRNN can successfully be used to enhance image resolution. The proposed neural network based method is promising for real-time applications, especially when the inherent parallelism of computation of the neural network is explored. Further, it can adapt itself to the various conditions of the reconstruction problem by learning
Keywords :
feedforward neural nets <image resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; image enhancement <resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; image reconstruction <resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; image resolution <enhanc. from multiple image frames, integr. recurrent neural net.>; learning (artificial intelligence) <image resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; optimisation <image resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; recurrent neural nets <image resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; search problems <image resoln. enhanc. from multiple image frames, integr. recurrent neural net.>; Hopfield network; IRNN; computation parallelism; enhanced image reconstruction; feedforward neural networks; image resolution enhancement; integrated recurrent neural network; learning; multiple image frames; optimal solution; optimisation; real-time applications; searching;
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
DOI :
10.1049/ip-vis:20030524