Image Compression Coding Algorithm Based On New Feature And Wavelet Transform

Image is a kind of similarity and vivid description of the objective world,which contains information about the object being described.The amount of data contained is very large,which brings difficulties to storage and transmission.Many experts and scholars collect,enhance and restore images.Image processing includes transformation,segmentation,coding,reconstruction,registration,mosaic,feature extraction and pattern recognition.Among them,fractal image compression coding algorithm breaks through the theoretical system of traditional methods and has received widespread attention.However,due to its high computational complexity and long encoding time,its application is limited.In view of these disadvantages,the following work has been done in this paper:(1)A fast fractal coding algorithm based on semi-cross-trace feature is proposed.Firstly,the sub-block pseudo-semi-fork feature is defined.Secondly,the relationship between the minimum mean square error and the sub-block pseudo-semi-fork feature is proved,and the rationality of using this feature to search is verified.The experimental results show that the proposed algorithm can effectively reduce the complexity of the data,and speed up the encoding process while ensuring the similarity between the reconstructed image and the original image.(2)An eight-point and feature fast coding algorithm is proposed.Firstly,the definitions of eight points and features are given,and then the relationship between them and the minimum mean square error is proved,and its rationality is verified.The simulation results show that the proposed algorithm not only speeds up the encoding speed,but also improves the peak signal-to-noise ratio(PSNR)under the premise of guaranteeing great structural similarity(3)A fractal image coding algorithm combining wavelet transform and imitation half-crossing features is proposed.Firstly,the related concepts of wavelet transform are given.Secondly,the original image is subjected to two-dimensional wavelet transform,and then the feature codec is obtained.Finally,the reconstructed image can be obtained by two-dimensional inverse wavelet transform.According to the experimental results,the hybrid coding algorithm is more efficient.