基于遗传算法优化的神经网络自适应开关加权滤波研究

Neural Network Adaptive Switch Weighted Filter Based on Genetic Algorithm Optimization

针对传统滤波算法对高噪声密度椒盐噪声污染的图像去噪效果不佳的劣势,采用遗传算法优化BP神经网络后对图像中的椒盐噪声进行自适应开关加权滤波处理。与几种相关方法的对比实验表明,本方法神经网络泛化性能强、椒盐噪声检测的准确率高、经过滤波处理后图像还原度高、图像细节信息保护效果较理想。

For the poor performance of conventional filtering algorithms in removing salt and pepper noise from digital images under high noise density,an adaptive switching weighted mean filter algorithm based on BP neural network optimized by genetic algorithm(GA)is proposed to detect and remove salt and pepper noise from images.The contrastive experiments of several related methods show that the proposed algorithm significantly outperforms the others and efficiently removes salt and pepper noise from digital images without distorting image details and texture.