Abstract
Due to the influence of atmospheric turbulence, a time-variate video of an observed object by using the astronomical telescope drifts randomly with the passing of time. Thereafter, a series of images is obtained snapshotting from the video. In this paper, a method is proposed to improve the quality of astronomical images only through multiframe image registration and superimposition for the first time. In order to overcome the influence of anisoplanatism, a specific image registration algorithm based on multiple local homography transformations is proposed. Superimposing registered images can achieve an image with high definition. As a result, signal-to-noise ratio, contrast-to-noise ratio, and definition are improved significantly.
Highlights
Anisoplanatism continuously hinders the performance of spatial object observation by ground-based telescopes
The object spot keeps invariant in the scope of isoplanatic angle, and it has the same systematic point spread function (PSF), while if the imaging angle is out of the isoplanatic angle scope, the PSF is deemed to be varying with spatial position changes
Dan [13] proposed estimating the Journal of Sensors transformation model among short-exposure images with anisoplanatic effect based on neural networks, and the anisoplanatism is reduced by using image registration
Summary
Anisoplanatism continuously hinders the performance of spatial object observation by ground-based telescopes. Jin et al [3] proposed a method to restore the extended spatial target phase by using bispectra, and the bispectra method is spatially invariant compared with the crossspectra method. Ayers and Dainty [4] innovatively proposed an image restoration concept by using blind deconvolution algorithm in the spatial target observation field. The image restoration performance is impaired severely after the process of spot imaging or blind deconvolution. Thereafter, multiple frame superimposition was adopted instead of long-term exposure imaging to reduce the effect of anisoplanatism, and image definition was improved [10]. Dan [13] proposed estimating the Journal of Sensors transformation model among short-exposure images with anisoplanatic effect based on neural networks, and the anisoplanatism is reduced by using image registration
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