基于小波收缩的噪声图像恢复新型算法实现与验证

小波变换技术是近20年发展起来的新的信号处理技术,但对小波的研究由来已久。随着小波理论的不断完善,它以自身良好的时频特性在图像去噪领域受到越来越多的关注。图像去噪是信号处理中的一个经典问题,传统的去噪方法多采用平均或线性方法进行,但是其去噪效果不好,本文基于此目的,采用了连续两次半软阈值去噪的方法,来去除含噪图像的噪声,最后通过MATLAB软件仿真此方法的去噪效果,并与其它去噪方法进行比较,得出本文提出的方法去噪效果更优越。

Noise based on wavelet shrinkage algorithm for image restoration and verification

Wavelet transform is the new signal processing technology in the last 20 years developed, but the study of wavelet lasts for a long time. With the constant improvement of wavelet theory, it is payed more and more attention besause of its own good time-frequency characteristics in the field of image denoising. Image denoising is a classic signal processing problem, which means traditional denoising method often use the average or linear,without good denoising effect.This paper ,based on this purpose, successively twicely uses semi-soft thresholding way to remove the noisy image noise.Finally compares with other denoising methods through method de-noising effect of the MATLAB software simulation,obtaining the superior denoising result;