Super-resolution image reconstruction method based on space-time transformation technology

Abstract

The invention discloses a super-resolution image reconstruction method based on a space-time transformation technology. The method includes dividing an image into an R component, a G component and a Bcomponent; respectively forming vectors lR, lG and lB by R, G and B components of each low-resolution image sequence; constructing contribution matrixes AR, AG and AB of each high-resolution spatio-temporal point corresponding to the low-resolution spatio-temporal points by utilizing a spatio-temporal transformation technology; obtaining vectors hR, hG and hB of the high-time-resolution image sequence by utilizing a linear formula Ah = 1 of high-resolution elements through conjugate gradient algorithm operation; reconstructing the spatial super-resolution by using an iterative back projectionmode according to the numerical values of hR, hG and hB to obtain XR, XG and XB corresponding to R, G and B components in the super-resolution image sequence; and synthesizing the XR, the XG and theXB to obtain a super-resolution image. According to the image reconstruction method, the problems of low image reconstruction resolution, low accuracy, complex calculation and the like can be effectively solved, so that an image with good quality is obtained; the invention is simple to operate, low in cost and high in robustness.

Description

technical field [0001] The invention relates to the technical field of image reconstruction, in particular to a super-resolution image reconstruction method based on space-time transformation technology. Background technique [0002] Pixel resolution is a direct factor affecting image quality, and higher resolution is more conducive to further processing and synthesis of images. Super-resolution image reconstruction refers to combining several lower-resolution images to reconstruct an ultra-high-resolution image. Here "ultra" means that the super-resolution image reconstruction method can break through the existing sampling frequency control of traditional sensing devices. The resolution of a digital image not only represents the pixels of the image, but also represents the resolution ability of the image details. Image resolution is a key factor in measuring image detail. Image interpolation can arbitrarily enlarge or reduce the proportion of an image, but it does not me...

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Problems solved by technology

[0006] In view of the above existing problems, the present invention aims to provide a super-resolution image reconstruction method based on spatio-temporal transformation technology, which can effectively solve the problems of low image reconstruction resolution, low accuracy, and complex calculations, thereby obtaining excellent image quality

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