Super-resolution reconstruction method for single-frame images on basis of pre-amplification non-negative neighbor embedding

The invention discloses a super-resolution reconstruction method for single-frame images on the basis of pre-amplification non-negative neighbor embedding. The super-resolution reconstruction method includes steps of constructing high-resolution training image sets; blurring the high-resolution training image sets and performing down-sampling on the high-resolution training image sets to obtain temporary low-resolution image sets; pre-amplifying the temporary low-resolution image sets twice to obtain low-resolution training image sets; constructing low-resolution training block sets; constructing high-resolution training image block sets; pre-amplifying input low-resolution images twice; constructing low-resolution input image block sets; representing the low-resolution input image block sets by the aid of non-negative neighbor embedding to solve reconstruction coefficients; acquiring high-resolution output images by the aid of the high-resolution training image block sets and the solved coefficients. The super-resolution reconstruction method has the advantages that non-local similarity of image blocks is utilized, a novel process for constructing training examples is provided, and accordingly neighbor numbers K can be effectively selected by the aid of non-negative neighbor embedding; as shown by experiment simulation, the images reconstructed by the aid of the super-resolution reconstruction method have sharp edges and rich textures and are close to real images.