Infrared image super-resolution reestablishing method based on compressed sensing theory
A super-resolution reconstruction, infrared image technology, applied in the direction of graphic image conversion, image data processing, instruments, etc., can solve the problems of lack of stability, high algorithm complexity, long calculation time and so on
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[0107] Example: see figure 1 -5. A super-resolution reconstruction method of infrared images based on compressed sensing theory. The image is collected to determine the size of the image block, that is, the value of the number of rows and columns m and n and the number of overlapping pixels k of the block, and then the image is analyzed. piece. Write out the downsampling matrix D and the sparse transformation matrix H according to the definition of the block size, so that the sensing matrix A is obtained by A=DH. The low-resolution image block Y is taken out and arranged into a column vector y, and the problem of high-resolution reconstruction of the image block is transformed into the solution of y=Ax′. According to the theory of compressed sensing, when x' has sparse characteristics, the sparse coefficient x' can be reconstructed according to y and A, and finally a high-resolution image block is obtained according to x=Hx', and all high-resolution image blocks are spliced ...
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