基于粒子群优化算法的图像小波阈值去噪研究

An Image Denoising Method Based on Wavelet Transform and Particle Swarm Optimization

将粒子群优化算法应用于图像小波阈值去噪,从理论上分析了小波去噪基本原理,并采用PSO的算法求小波变换各子带的最优阈值,讨论了粒子数目、噪声大小、小波基的选择对本算法效果的影响。实验结果表明,与普通小波阈值去噪方法相比,该算法能获得较好的图像效果,提高信噪比。

Presents an image denoising method based on wavelet transform and particle swarm optimization,analyzes the basic principle of wavelet threshold denoising theoretically,and uses PSO to get the best thresholds of every wavelet subband. Also discusses the effect of the method when partlcles,noises and wavelet basses are different through experiment. The experimental results showed that compared with other common wavelet threshold desnoising methods, the presented method can improve the visual effect and increase SNR of the denoised image.