Study of optical microscanning reconstruction

Abstract

Infrared images provide valuable information for many applications. However, compared to a visible image, the image quality is poor and its spatial resolution is limited due to the focal plane arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency, which consequently leads to image blurring. Optical micro-scanning technique has been proven to be an effective method to increase the resolution of images. This technique is able to produce high resolution (HR) images from a set of optically shifted images of low-resolution (LR). Over the last decade, optical micro-scanning technique has become one of the active topics of research, among this, the super-resolution (SR) reconstruction algorithms are the focus. This paper starts with the basic principle of SR reconstruction. Then several methods of high-precision movement registration algorithm and SR reconstruction algorithms were introduced. This study particularly focuses on the more recent development in motion estimation methods. Furthermore, an algorithm based on sub-pixel image registration that estimates the displacements of the LR image is presented. The critical steps in image registration are collecting feature points and estimating a spatial transformation especially when outliers are present. In this paper, the Harris corner detector is used to find the feature points and then the point feature is described by the neighborhood difference in order to reduce the sensitivity to illumination variations. Moreover, the Random Sample Consensus(RANSAC) algorithm is employed to build a transformation model. Simulation results demonstrate that the method can estimate the displacements accurately.