The Research Of Image Denoising Method Based On Wavelet Transform And Swarm Intelligence Optimization Algorithm

The sense of vision is one of the important ways that the mankind obtain an outside information,and image is the most important visual information source.Therefore, the image is an important medium of information and means.However, images are easy to be polluted by all kinds of noise in its acquisition,transmission,processing or output,which degrades the quality of original images and lost some details.In order not to affect the effect of image communication,image denoising become an indispensable a preprocessing step of image subsequent processing.According to the characteristics of the image signal, denoising is the key to abate noise corresponding to the high frequency part,and to enhance the high frequency components of the edge.At present,wavelet analysis has been penetrated into all disciplines and can be applied to a very good image denoising processing.Because the wavelet theory has good low entropy,multiresolution analysis,choose the wavelet base is flexibility and the high de-correlation,etc,can be achieved for different high frequency component differently.The study of wavelet threshold denoising method show that the denoising effect is the key to select the proper threshold value and threshold function.To solve the problem of optimal threshold,this paper adopts intelligent optimization algorithms to search for the optimal threshold,aiming to maximize the efficiency and accuracy.Based on the theory of image denoising technique,wavelet transform,particle swarm optimization(PSO)and artificial fish swarm algorithm(AFSA) combined with wavelet threshold denoising algorithm,an effective method for separating noise is presented.Firstly,this report introduces the development of image denoising,research background,noise model and classification,image denoising effect evaluation standard. Secondly,it makes an introduction and analysis of correlated theories about wavelet transformation,including the theoretical basis and characteristics of wavelet transform and application in extraction of image characteristics,and discussed several classic wavelet threshold denoising algorithm,and through comparing various denoising algorithms,analyzed their respective advantages and limitations.In order to get the best threshold estimation,this paper gives a further study on group behaviors and parameters in the PSO and AFSA algorithms,and comparative analysis the parameters on the algorithm optimization effect using the MATLAB simulation results.Finally,a hybrid swarm intelligence optimization algorithm is proposed in this report,which can help to overcome the deficiencies of individual intelligence algorithm,and find the optimal value overall situation,so that it can get a better solution.