Selection-Based Subpixel-Shifted Images Super-Resolution

Abstract

The subpixel-shifted (SPS) images acquisition method based on imaging system has the limitations of complex structure, difficult production and high cost. Therefore, this paper proposes an image super-resolution reconstruction method based on registration. In the first phase, the registration algorithm is used to select the SPS images. In order to improve the accuracy of the registration algorithm, a registration algorithm combining SIFT-FLANN and misregistration points elimination (SFME) is proposed. In the second phase, an interpolation of nonuniformly spaced samples based on pixel gray correction is proposed to get the high resolution (HR) image. Experiments show that the images selection method can obtain higher-precision SPS images, and the reconstruction method can reconstruct HR image with better visual and higher spatial resolution. Finally, the image magnification factor and the number of SPS images used in the reconstruction process are analyzed to describe the practical application value of the methods proposed in this paper.