关键词: 小波变换, 阈值法, 图像去噪, PSO算法

Abstract: A new wavelet threshold function is proposed for images of strong Gaussian noise. The traditional soft threshold de-noising method has a significant effect, but not ideal effect of strong Gaussian noise. In the soft threshold function, this paper constructs a new wavelet threshold function；the function contains the threshold value[λ], adjustable factor [t] and [n], which can adjust to the adaptive threshold changes. The experiment adopts the noised image and de-noised image Peak Signal to Noise Ratio（PSNR） criterion of maximize, based on Particle Swarm Optimization（PSO） using function selection parameters. The simulation results show that this method can not only effectively remove the noise, but also to avoid the loss of high frequency information useful to improve the signal to noise ratio. Especially in the strong Gaussian noise, the proposed method can relatively improve PSNR 6~7 dB than soft threshold method, it shows that this proposed threshold method can effectively reduce strong Gaussian noise on images.

Key words: wavelet transform, threshold, image de-noising, PSO algorithms