Reconstruction of damaged data of pre-compressed image based on genetic algorithm
In order to increase the signal-to-noise ratio in the damaged area of the pre-compressed image,making the reconstructed image better fits the original image before compression,a genetic algorithm based reconstruction method for the damaged data of the pre-compressed image is proposed.The fitness evaluation criteria is selected according to the generated damaged node population,and the genetic data array is con-structed to complete the retrieval of damaged nodes in pre-compressed images based on genetic algorithm.The distribution function of the damaged data is established to calculate the actual value of the compression reconstruction ratio index,the damaged data of the pre compressed image is reconstructed realize the recon-struction of the damaged data of the pre-compressed image.The experiment results show that under the effect of genetic algorithm,the value of the signal-to-noise ratio of the data parameter in the damaged area of the pre-compressed image increases,which can promote the reconstruction image and the original image to complete a good fit.
genetic algorithmpre-compressed imagereconstruction of damaged dataadaptabilitysig-nal to noise ratio
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