Esearch On Regular Item Parameters And Algorithms In Image Restoration Model Based On Wavelet Frame

Image restoration has very important applications in many research fields.This study mainly focuses on the regularization parameters in the image restoration model and the singularity set detection the model solving algorithm,which allows for adaptable parameter changes,accelerates the algorithm’s operation,and enhances image restoration quality.(1)A wavelet frame-based technique for analyzing parameters in an image restoration model has been provided,as well as a random generating algorithm for the parameters.By first modeling the wavelet frame coefficients of the smooth areas and the singularity set of the picture to be restored as an Exponential distribution,and then incorporating the Bayesian estimation theory,this approach develops the two-part parameter estimation formula.The settings of the picture restoration method are self-adaptive.(2)We propose an image denoising algorithm for singularity set detection with random one-way mutation operation based on wavelet framework.This wavelet framework was based on the random search theory and genetic algorithm’s mutation operator.The new algorithm ensures the quality of image on the one hand,and effectively promotes the efficiency of restoration process on the other hand.