关键词: 粗集, 神经网络, 图像融合, 粗神经网络, 遗传算法

Abstract: Rough set theory can optimize data，but the fault-tolerant and promotion capabilities are relatively weak.Whereas neural network has strong self-organization and promotion capabilities，but can not optimize data.This paper combines rough set theory with neural network to exert their advantages，then applies them to image fusion and proposes a image fusion method based on rough neural network theory.The method uses a genetic algorithm to train the neural network.Simulation results show that，in the integration of features from the same number of images with the application of noise，the method is effective and feasible.

Key words: rough set, neural network, image fusion, rough neural network, genetic algorithm