6533b7dbfe1ef96bd12708e9

RESEARCH PRODUCT

Fast Image Restoration Algorithms Based on PDE Models Using Modified Hopfield Neural Network

Ishfaq AhmadYadong WuFan YangZhiqin LiuYu Sun

subject

Harmonic analysisPartial differential equationArtificial neural networkRate of convergenceComputer scienceSignal processing algorithmsTotal variation modelRule-based systemAlgorithmImage restoration

description

Two image restoration algorithms based on modified Hop field neural network and variational partial differential equations (PDE) were proposed in our previous work [1, 2]. But the convergence rate of the proposed algorithms was slow. In this paper, we develop a fast update rule based on modified Hop field neural network (MHNN) of continuous state change and two fast image restoration algorithms. Experimental results show that, when compared with the previous algorithms, our proposed algorithms have better performance both in convergence rate and in image restoration quality.

yearjournalcountryeditionlanguage
2010-10-012010 International Conference on Artificial Intelligence and Computational Intelligence
https://doi.org/10.1109/aici.2010.54