Research For Sparse Representation Algorithm Of Information And Its Application In Image Restoration

With the development of Scinece and Technology, and more and more increasing of the requirement, cloud data is its mainly characteristic in modern science and engineering. As we known, in general, the data as mentioned above are reduancy and dependence, a common question is to consider theory and method for sprase representation of information so as to decrease complexity of space and time used greatly.Image is a two-dimensional data used information transporation and processing with most commonly used and very improtatntly. In this paper, we study image restoration including super-solution, remove noise and deblurring.1. Combined bandelet in multiscaling geometry analysis and splitted Bregamn optimization algorithm, a type of super-solution mathematical model is developed. Using Bandelet achieves sparse representation of image, and efficiency splitted Bregman algorithm is used to accelerate th computation speed. Numerical examples shows that the quality of reconstruction image is superior known classical algorithm.2. Non-Local model via FFT algorithm for image noise removed and deblurring is proposed. By considering improved Total variation model of image, wo obtain optimization method for image noise removed and deblurring. Since FFT algorithm is used the computational complexity is decreased greatly. Experimenations showns the efficiency of the proposed methods.